{"id":1760,"date":"2026-08-15T22:24:56","date_gmt":"2026-08-15T22:24:56","guid":{"rendered":"https:\/\/lean-app.com\/lean-vs-foodvisor\/"},"modified":"2026-09-05T10:54:09","modified_gmt":"2026-09-05T10:54:09","slug":"lean-vs-foodvisor","status":"publish","type":"post","link":"https:\/\/lean-app.com\/no\/lean-vs-foodvisor\/","title":{"rendered":"Lean vs Foodvisor: AI-fotoskanning mot det reelle forbruket ditt"},"content":{"rendered":"<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp\" fetchpriority=\"low\">\n<link rel=\"preload\" as=\"image\" href=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp\" 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.method h3{margin-top:0}\n#lvm-shell .method p{font-size:16px;color:var(--muted);line-height:1.7}\n\n#lvm-shell .cta-band{margin:40px 0;padding:26px 28px;background:var(--paper);border-radius:16px;display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;border:1px solid var(--rule-soft)}\n#lvm-shell .cta-band .l{font-family:var(--font-display);font-size:18px;line-height:1.35;font-weight:500;color:var(--ink);flex:1;min-width:240px;letter-spacing:-.01em}\n#lvm-shell .cta-band .stores{display:flex;gap:10px;align-items:center}\n#lvm-shell .cta-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .cta-band .stores a:hover{transform:translateY(-2px)}\n#lvm-shell .cta-band .stores img{height:42px;width:auto;border-radius:9px}\n\n#lvm-shell .pyramid{margin:30px auto;max-width:440px}\n#lvm-shell .pyramid .level{margin:6px auto;padding:13px 18px;border-radius:14px;color:#fff;font-family:var(--font-display);font-weight:500;font-size:15px;letter-spacing:-.01em;display:flex;justify-content:space-between;align-items:center;box-shadow:0 6px 18px rgba(0,0,0,.06)}\n#lvm-shell .pyramid .level .k{font-family:var(--font-mono);font-size:10px;text-transform:uppercase;letter-spacing:.08em;opacity:.75}\n#lvm-shell .pyramid .l1{background:#0E0E10;width:100%}\n#lvm-shell .pyramid .l2{background:#1D1D1F;width:84%}\n#lvm-shell .pyramid .l3{background:#3a3a3c;width:68%}\n#lvm-shell .pyramid .l4{background:var(--pink);width:52%}\n#lvm-shell .pyramid-cap{text-align:center;font-size:13px;color:var(--muted);margin-top:14px}\n\n\/* Section 7 honnetete : scorecard horizontal bars *\/\n#lvm-shell .scorecard{margin:30px 0 10px;border:1px solid var(--rule);border-radius:20px;padding:28px 26px;background:#fff}\n#lvm-shell .scorecard-head{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding-bottom:18px;margin-bottom:8px;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-head .h-crit{font-family:var(--font-mono);font-size:11px;font-weight:500;text-transform:uppercase;letter-spacing:.08em;color:var(--muted)}\n#lvm-shell .scorecard-head .h-brand{display:flex;align-items:center;gap:8px;font-family:var(--font-display);font-size:14px;font-weight:600;color:var(--ink)}\n#lvm-shell .scorecard-head .h-brand img{width:22px;height:22px;border-radius:5px;object-fit:cover}\n#lvm-shell .scorecard-row{display:grid;grid-template-columns:1.4fr 1fr 1fr;column-gap:28px;align-items:center;padding:14px 0;border-bottom:1px solid var(--rule-soft)}\n#lvm-shell .scorecard-row:last-child{border-bottom:0}\n#lvm-shell .scorecard-row .crit{font-size:14px;color:var(--ink);font-weight:500;padding-right:14px}\n#lvm-shell .scorecard-row .bar{display:flex;flex-direction:row-reverse;align-items:center;gap:10px}\n#lvm-shell .scorecard-row .bar .b{flex:1;height:8px;border-radius:99px;background:var(--rule-soft);overflow:hidden;position:relative}\n#lvm-shell .scorecard-row .bar .b > i{display:block;height:100%;border-radius:99px;transition:width 1s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .scorecard-row .bar.lean .b > i{background:var(--pink)}\n#lvm-shell .scorecard-row .bar.mfp .b > i{background:var(--mfp)}\n#lvm-shell .scorecard-row .bar .v{font-family:var(--font-mono);font-size:12px;font-weight:600;color:var(--ink);min-width:32px;text-align:left}\n\n\/* Section 8 pour qui : persona checklist *\/\n#lvm-shell .persona{margin:28px 0 10px;display:grid;grid-template-columns:1fr;gap:14px}\n#lvm-shell .persona-it{display:grid;grid-template-columns:54px 1fr;gap:16px;padding:22px 24px;background:#fff;border:1px solid var(--rule);border-radius:18px;align-items:center}\n#lvm-shell .persona-it.match{background:var(--pink-soft);border-color:rgba(255,45,110,.25)}\n#lvm-shell .persona-it .pic{width:54px;height:54px;border-radius:50%;display:flex;align-items:center;justify-content:center;background:var(--rule-soft);position:relative;font-family:var(--font-mono);font-size:13px;font-weight:600;color:var(--ink)}\n#lvm-shell .persona-it.match .pic{background:var(--pink);color:#fff}\n#lvm-shell .persona-it .pic svg{width:24px;height:24px}\n#lvm-shell .persona-it h4{margin:0 0 4px;font-size:17px;letter-spacing:-.01em}\n#lvm-shell .persona-it p{margin:0;font-size:14px;color:var(--muted);line-height:1.55}\n#lvm-shell .persona-it.match h4{color:var(--ink)}\n\n\/* Section 9 migration : timeline steps *\/\n#lvm-shell .steps{display:grid;grid-template-columns:repeat(5,1fr);gap:14px;margin:28px 0;position:relative}\n#lvm-shell .steps::before{content:\"\";position:absolute;top:14px;left:7px;right:calc(20% - 18px);height:1px;background:linear-gradient(90deg,var(--pink) 0%,var(--rule-soft) 100%);z-index:0}\n#lvm-shell .step{position:relative;padding-top:24px;z-index:1}\n#lvm-shell .step::before{content:\"\";position:absolute;top:8px;left:0;width:14px;height:14px;border-radius:50%;background:var(--pink);border:3px solid #fff;box-shadow:0 0 0 1px var(--rule)}\n#lvm-shell .step .sn{font-family:var(--font-mono);font-size:11px;color:var(--pink);font-weight:600;letter-spacing:.08em}\n#lvm-shell .step h4{margin:6px 0 6px;font-size:15px;letter-spacing:-.01em}\n#lvm-shell .step p{font-size:13px;color:var(--muted);line-height:1.5;margin:0}\n\n\/* Section 10 debloque : feature stack numbered XL *\/\n#lvm-shell .feat-stack{margin:30px 0 10px;border-top:1px solid var(--rule)}\n#lvm-shell .feat-it{display:grid;grid-template-columns:auto 1fr auto;gap:24px;padding:26px 0;border-bottom:1px solid var(--rule);align-items:center}\n#lvm-shell .feat-it .fn{font-family:var(--font-display);font-size:48px;font-weight:600;color:var(--pink);line-height:1;letter-spacing:-.04em;width:74px}\n#lvm-shell .feat-it .ft{font-family:var(--font-display);font-size:22px;font-weight:600;color:var(--ink);letter-spacing:-.015em;line-height:1.25;margin-bottom:6px}\n#lvm-shell .feat-it .fd{font-size:15px;color:var(--muted);line-height:1.55;margin:0}\n#lvm-shell .feat-it .fc{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--muted);font-weight:500}\n#lvm-shell .feat-it:last-child{border-bottom:0}\n\n#lvm-shell .faq{margin:22px 0}\n#lvm-shell .faq details{border-bottom:1px solid var(--rule);padding:20px 0}\n#lvm-shell .faq details:first-of-type{border-top:1px solid var(--rule)}\n#lvm-shell .faq summary{cursor:pointer;list-style:none;display:flex;justify-content:space-between;align-items:center;gap:18px;font-family:var(--font-display);font-size:20px;font-weight:500;letter-spacing:-.015em;color:var(--ink)}\n#lvm-shell .faq summary::-webkit-details-marker{display:none}\n#lvm-shell .faq summary::after{content:\"+\";font-size:24px;color:var(--muted);font-weight:300;line-height:1;transition:transform .25s, color .25s}\n#lvm-shell .faq details[open] summary::after{transform:rotate(45deg);color:var(--pink)}\n#lvm-shell .faq details[open] summary{color:var(--pink)}\n#lvm-shell .faq .ans{margin-top:14px;font-size:16px;color:var(--muted);line-height:1.65}\n\n#lvm-shell .get-band{background:var(--paper-2);border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center}\n#lvm-shell .get-band .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;color:var(--pink);font-weight:600;letter-spacing:.1em;margin-bottom:14px}\n#lvm-shell .get-band h3{font-size:36px;margin:0 0 14px;letter-spacing:-.025em}\n#lvm-shell .get-band p{font-size:16px;color:var(--muted);max-width:480px;margin:0 auto 26px}\n#lvm-shell .get-band .stores{display:flex;justify-content:center;gap:14px;flex-wrap:wrap}\n#lvm-shell .get-band .stores a{line-height:0;transition:transform .15s}\n#lvm-shell .get-band .stores a:hover{transform:translateY(-3px)}\n#lvm-shell .get-band .stores img{height:60px;width:auto;border-radius:11px}\n\n#lvm-shell .sources{font-size:14px;color:var(--muted);line-height:1.7}\n#lvm-shell .sources ol{padding-left:22px}\n#lvm-shell .sources li{margin-bottom:8px}\n\n#lvm-shell footer{padding:50px 0 60px;border-top:1px solid var(--rule);margin-top:40px}\n#lvm-shell footer .row{display:flex;justify-content:space-between;align-items:center;gap:18px;flex-wrap:wrap}\n#lvm-shell footer .kicker{font-family:var(--font-mono);font-size:11px;text-transform:uppercase;letter-spacing:.08em;color:var(--pink);font-weight:600}\n#lvm-shell footer p{font-size:13px;color:var(--muted);margin:8px 0 0}\n#lvm-shell footer .stores{display:flex;gap:8px}\n#lvm-shell footer .stores img{height:34px;width:auto;border-radius:6px}\n\n#lvm-shell .rev{opacity:0;transform:translateY(12px);transition:opacity .8s cubic-bezier(.22,.61,.36,1),transform .8s cubic-bezier(.22,.61,.36,1)}\n#lvm-shell .rev.on{opacity:1;transform:translateY(0)}\n@media (prefers-reduced-motion:reduce){#lvm-shell .rev{transition:none;opacity:1;transform:none}}\n\n@media (max-width:760px){\n  #lvm-shell .nav-row{padding:8px 18px;gap:8px}\n  #lvm-shell .nav-link{display:none}\n  #lvm-shell .nav-stores img{height:24px}\n  #lvm-shell .wrap{padding:0 22px}\n  #lvm-shell .hero{padding:34px 0 0}\n  #lvm-shell h1{font-size:46px;letter-spacing:-.035em}\n  #lvm-shell h1 .alt{font-size:.55em;margin-top:10px}\n  #lvm-shell .dek{font-size:20px}\n  #lvm-shell .hero-stores img{height:42px}\n  #lvm-shell .hero-bottom{grid-template-columns:1fr;gap:28px;margin:30px 0 40px;padding-top:24px;align-items:stretch}\n  #lvm-shell .phone-wrap{order:-1}\n  #lvm-shell .phone{width:240px}\n  #lvm-shell .tap-hint.desktop{display:none}\n  #lvm-shell .tap-hint.mobile{display:block;position:relative;left:auto;top:auto;text-align:center;margin:0 auto 10px;width:100%}\n  #lvm-shell .tap-hint.mobile .th-arrow{position:relative;display:block;margin:6px auto 0;width:34px;height:34px;transform:none;color:var(--pink)}\n  #lvm-shell .snippet{padding:24px 22px}\n  #lvm-shell .snippet p{font-size:18px}\n  #lvm-shell section{padding:48px 0}\n  #lvm-shell h2{font-size:34px;letter-spacing:-.03em}\n  #lvm-shell h3{font-size:24px}\n  #lvm-shell .section-label{margin-bottom:22px}\n  #lvm-shell .statement{padding:24px 0;margin:32px 0}\n  #lvm-shell .statement .num{font-size:44px}\n  #lvm-shell .statement .lbl{font-size:19px}\n  #lvm-shell .fig{padding:20px 14px 14px;border-radius:16px}\n  #lvm-shell .cv-wrap{height:310px}\n  #lvm-shell .method{grid-template-columns:1fr;gap:20px}\n  #lvm-shell .method.flip{grid-template-columns:1fr}\n  #lvm-shell .method.flip .m-phone{order:0}\n  #lvm-shell .mini-row{grid-template-columns:repeat(3,1fr);gap:10px}\n  #lvm-shell .mini-phone{padding:3px;border-radius:18px;border-width:1px;max-width:110px}\n  #lvm-shell .mini-phone .notch{width:42px;height:11px;border-radius:0 0 8px 8px}\n  #lvm-shell .mini-phone .scr{border-radius:15px}\n  #lvm-shell .mini-cap{font-size:10px}\n  #lvm-shell .mini-cap strong{font-size:13px}\n  #lvm-shell .duo-row{grid-template-columns:repeat(2,1fr);gap:12px}\n  #lvm-shell .duo-row .mini-phone{max-width:130px}\n  #lvm-shell .steps{grid-template-columns:1fr;gap:18px}\n  #lvm-shell .steps::before{display:none}\n  #lvm-shell .step{padding-top:0;padding-left:24px}\n  #lvm-shell .step::before{top:6px;left:0}\n  #lvm-shell .table-row{grid-template-columns:1.4fr .9fr .9fr}\n  #lvm-shell .table-row > .crit{padding:13px 12px;font-size:13px}\n  #lvm-shell .table-row > .cell{padding:13px 10px;font-size:12px;gap:8px}\n  #lvm-shell .table-row.head > div{padding:14px 12px;font-size:10px;gap:7px}\n  #lvm-shell .table-row.head .brand-cell img{width:20px;height:20px}\n  #lvm-shell .get-band{padding:36px 22px;border-radius:18px;margin:40px 0 30px}\n  #lvm-shell .get-band h3{font-size:28px}\n  #lvm-shell .get-band .stores img{height:50px}\n  #lvm-shell .cta-band{padding:22px;gap:14px}\n  #lvm-shell .cta-band .l{font-size:16px;min-width:0}\n  #lvm-shell .cta-band .stores img{height:38px}\n  #lvm-shell .faq summary{font-size:18px;gap:14px}\n  #lvm-shell .pyramid{max-width:100%}\n  #lvm-shell .pyramid .level{padding:11px 14px;font-size:14px}\n  #lvm-shell .scorecard{padding:20px 16px;border-radius:16px}\n  #lvm-shell .scorecard-head{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px}\n  #lvm-shell .scorecard-head .h-brand{font-size:12px;gap:5px}\n  #lvm-shell .scorecard-head .h-brand img{width:18px;height:18px}\n  #lvm-shell .scorecard-row{grid-template-columns:1.2fr 1fr 1fr;column-gap:14px;padding:12px 0}\n  #lvm-shell .scorecard-row .crit{font-size:13px;padding-right:8px}\n  #lvm-shell .scorecard-row .bar{gap:6px}\n  #lvm-shell .scorecard-row .bar .v{font-size:11px;min-width:26px}\n  #lvm-shell .persona-it{grid-template-columns:44px 1fr;gap:12px;padding:16px 16px;border-radius:14px}\n  #lvm-shell .persona-it .pic{width:44px;height:44px;font-size:12px}\n  #lvm-shell .persona-it h4{font-size:15px}\n  #lvm-shell .persona-it p{font-size:13px}\n  #lvm-shell .feat-it{grid-template-columns:auto 1fr;gap:14px;padding:20px 0}\n  #lvm-shell .feat-it .fn{font-size:36px;width:54px}\n  #lvm-shell .feat-it .ft{font-size:18px}\n  #lvm-shell .feat-it .fd{font-size:13px}\n  #lvm-shell .feat-it .fc{display:none}\n}\n@media (max-width:480px){\n  #lvm-shell .phone-tabs{gap:5px}\n  #lvm-shell .phone-tabs button{padding:5px 8px;font-size:10px}\n  #lvm-shell .nav-stores{gap:4px}\n  #lvm-shell .nav-stores img{height:22px}\n  #lvm-shell .hero-stores img{height:40px}\n  #lvm-shell .crumb{font-size:12px}\n  #lvm-shell .table-row{grid-template-columns:1.3fr .85fr .85fr}\n  #lvm-shell .table-row > .crit{padding:11px 9px;font-size:12px}\n  #lvm-shell .table-row > .cell{padding:11px 8px;font-size:11px;gap:6px}\n  #lvm-shell .table-row.head > div{padding:11px 9px;font-size:9px;gap:5px}\n}<\/style>\n\n<style id=\"lvm-collision-reset\">\n\/* Hard reset for global theme styles that collide with our content *\/\nbody.postid-1760 #lvm-shell .hero{display:block!important;align-items:initial!important;justify-content:initial!important;text-align:left!important;flex-direction:initial!important;padding:54px 0 0!important}\nbody.postid-1760 #lvm-shell .wrap,\nbody.postid-1760 #lvm-shell main.wrap{display:block!important;max-width:760px!important;margin-left:auto!important;margin-right:auto!important;padding-left:28px!important;padding-right:28px!important}\n@media (max-width:820px){\n  body.postid-1760 #lvm-shell .wrap,\n  body.postid-1760 #lvm-shell main.wrap{padding-left:18px!important;padding-right:18px!important}\n}\nhtml, body{overflow-x:hidden!important}\nbody.postid-1760 #lvm-shell{overflow-x:hidden;max-width:100vw}\nbody.postid-1760 #lvm-shell *{max-width:100%}\nbody.postid-1760 #lvm-shell .nav-row{max-width:100vw;box-sizing:border-box}\nbody.postid-1760 #lvm-shell.force-show .rev{opacity:1!important;transform:none!important}\n\n\/* === A.1 PHONE BACKGROUND CLASSES === *\/\nbody.postid-1760 #lvm-shell .phone-bg{position:absolute;inset:0;width:100%;height:100%;background-size:cover;background-position:center top;background-repeat:no-repeat;transition:opacity .28s ease;background-color:#FAF0E6}\nbody.postid-1760 #lvm-shell .phone-bg.tab-depense{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.tab-bilan{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_bilan.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.tab-kcal{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_kcal.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.tab-strategie{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_strategie.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.sub-BMR{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.sub-NEAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.sub-EAT{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp)}\nbody.postid-1760 #lvm-shell .phone-bg.sub-TEF{background-image:url(https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp)}\n\n\/* === v11.3 CTA BANDS MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .cta-band{flex-direction:column!important;align-items:center!important;text-align:center!important;padding:26px 22px!important;gap:20px!important}\n  body.postid-1760 #lvm-shell .cta-band .l{min-width:0!important;width:100%!important;font-size:16px!important;line-height:1.5!important;text-align:center!important}\n  body.postid-1760 #lvm-shell .cta-band .stores{width:100%!important;justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1760 #lvm-shell .cta-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1760 #lvm-shell .cta-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1760 #lvm-shell .cta-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1760 #lvm-shell .get-band{padding:38px 22px!important}\n  body.postid-1760 #lvm-shell .get-band .stores{justify-content:center!important;flex-wrap:nowrap!important;gap:10px!important}\n  body.postid-1760 #lvm-shell .get-band .stores a{flex:1!important;max-width:170px!important;display:flex!important;justify-content:center!important}\n  body.postid-1760 #lvm-shell .get-band .stores picture{width:100%!important;display:block!important}\n  body.postid-1760 #lvm-shell .get-band .stores img{height:56px!important;width:100%!important;max-width:170px!important;object-fit:contain!important;object-position:center!important;border-radius:10px!important}\n  body.postid-1760 #lvm-shell .get-band h3{font-size:26px!important;line-height:1.2!important}\n  body.postid-1760 #lvm-shell .get-band p{font-size:15px!important}\n}\n\n\/* === v11.2 BRAND BANNER above table responsive === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .brand-banner img{width:54px!important;height:54px!important}\n  body.postid-1760 #lvm-shell .brand-banner > div{padding:16px 12px!important;gap:8px!important}\n  body.postid-1760 #lvm-shell .brand-banner > div > div{font-size:15px!important}\n}\n\n\/* === v11.4 SCORECARD partie 7 : redesign mobile === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .scorecard{padding:18px 16px!important;border-radius:16px!important}\n  body.postid-1760 #lvm-shell .scorecard-head{display:none!important}\n  body.postid-1760 #lvm-shell .scorecard-row{\n    display:block!important;\n    padding:14px 0!important;\n    border-bottom:1px solid #E8E2D6!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .crit{\n    display:block!important;\n    font-size:13px!important;\n    font-weight:600!important;\n    color:#0E0E10!important;\n    margin-bottom:10px!important;\n    padding-right:0!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar{\n    display:grid!important;\n    grid-template-columns:54px 1fr 32px!important;\n    column-gap:8px!important;\n    align-items:center!important;\n    padding:5px 0!important;\n    flex-direction:initial!important;\n    position:relative!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar::before{\n    content:attr(data-brand)!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:11px!important;\n    font-weight:600!important;\n    text-transform:uppercase!important;\n    letter-spacing:.05em!important;\n    color:#0E0E10!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar.lean::before{color:#FF2D6E!important}\n  body.postid-1760 #lvm-shell .scorecard-row .bar.mfp::before{color:#6ABF6C!important}\n  body.postid-1760 #lvm-shell .scorecard-row .bar .b{\n    height:10px!important;\n    width:100%!important;\n    border-radius:99px!important;\n    position:relative!important;\n    background:#EFEAE0!important;\n    overflow:hidden!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar .b > i{\n    display:block!important;\n    height:100%!important;\n    border-radius:99px!important;\n  }\n  body.postid-1760 #lvm-shell .scorecard-row .bar .v{\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:12px!important;\n    font-weight:700!important;\n    color:#0E0E10!important;\n    min-width:0!important;\n    text-align:right!important;\n  }\n}\n\n\/* === A.2 CHARTS MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .cv-wrap{height:380px!important;min-height:360px!important;max-height:420px!important;width:100%!important}\n  body.postid-1760 #lvm-shell .cv-wrap canvas{width:100%!important;height:100%!important;display:block!important}\n  body.postid-1760 #lvm-shell .fig{padding:16px 4px 14px!important;margin:24px -4px 14px!important;overflow:visible!important}\n  body.postid-1760 #lvm-shell .fig-head{padding:0 12px!important;flex-wrap:wrap!important;gap:6px!important;margin-bottom:10px!important}\n  body.postid-1760 #lvm-shell .fig-body{padding:0 2px!important}\n  body.postid-1760 #lvm-shell .fig-cap{padding:0 12px!important;font-size:13px!important;margin-top:10px!important}\n}\n@media (max-width:480px){\n  body.postid-1760 #lvm-shell .cv-wrap{height:360px!important;min-height:340px!important;max-height:380px!important}\n  body.postid-1760 #lvm-shell .fig{padding:14px 2px 12px!important;margin:20px -6px 12px!important;border-radius:14px!important}\n  body.postid-1760 #lvm-shell .fig-body{padding:0!important}\n}\n\n\/* === v11.2 TABLEAU MOBILE STACKED CARDS avec mini-tags Lean\/Foodvisor === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .table{border-radius:14px!important}\n  body.postid-1760 #lvm-shell .table-row.head{display:none!important}\n  body.postid-1760 #lvm-shell .table-row{\n    display:grid!important;\n    grid-template-columns:1fr 1fr!important;\n    grid-template-areas:\"crit crit\" \"lean mfp\"!important;\n    gap:0!important;\n    min-height:0!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .crit{\n    grid-area:crit!important;background:#0E0E10!important;color:#fff!important;\n    padding:11px 14px!important;font-size:13px!important;font-weight:600!important;\n    letter-spacing:-0.1px!important;border-right:0!important;line-height:1.35!important;\n    font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif!important;text-transform:none!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell.lean{\n    grid-area:lean!important;border-right:1px solid #E8E2D6!important;\n    position:relative!important;background:#FFF1F5!important;padding-top:30px!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell:not(.lean):not(.crit){\n    grid-area:mfp!important;background:#EFF7EF!important;padding-top:30px!important;\n    position:relative!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell.lean::before{\n    content:\"LEAN\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    right:auto!important;bottom:auto!important;width:auto!important;height:auto!important;\n    background:transparent!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#FF2D6E!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell:not(.lean):not(.crit)::before{\n    content:\"FOODVISOR\"!important;position:absolute!important;top:8px!important;left:12px!important;\n    font-family:-apple-system,'SF Pro Display',sans-serif!important;\n    font-size:10px!important;font-weight:700!important;letter-spacing:.07em!important;\n    color:#6ABF6C!important;\n  }\n  body.postid-1760 #lvm-shell .table-row > .cell{\n    padding:12px 12px!important;font-size:13px!important;line-height:1.4!important;\n    align-items:flex-start!important;gap:7px!important;\n  }\n  body.postid-1760 #lvm-shell .icn{flex-shrink:0!important;margin-top:1px!important}\n}\n\n\/* === A.5 MINI-LOGOS triplet NEAT\/EAT\/TEF === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .mini-row{gap:6px!important;margin:24px 0!important;grid-template-columns:repeat(3,1fr)!important}\n  body.postid-1760 #lvm-shell .mini-phone{max-width:100px!important;padding:2px!important;border-radius:14px!important;border-width:1px!important}\n  body.postid-1760 #lvm-shell .mini-phone.tiny{max-width:96px!important;padding:2px!important;border-radius:13px!important}\n  body.postid-1760 #lvm-shell .mini-phone .notch{width:30px!important;height:8px!important;border-radius:0 0 5px 5px!important}\n  body.postid-1760 #lvm-shell .mini-phone .scr{border-radius:11px!important}\n  body.postid-1760 #lvm-shell .mini-cap{font-size:10px!important;margin-top:8px!important}\n  body.postid-1760 #lvm-shell .mini-cap strong{font-size:12px!important;margin-top:2px!important}\n}\n\n\/* === MOCKUP TAP HINT MOBILE === *\/\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .tap-hint.mobile{position:relative!important;width:100%!important;left:auto!important;top:auto!important;text-align:center!important;margin:0 auto 14px!important;display:block!important}\n  body.postid-1760 #lvm-shell .tap-hint.desktop{display:none!important}\n  body.postid-1760 #lvm-shell .tap-hint.hidden{display:none!important;height:0!important;margin:0!important;padding:0!important}\n}\n\n\/* === A.6 BODYSCAN ILLUST partie BMR === *\/\nbody.postid-1760 #lvm-shell .bodyscan-illust{margin:40px auto 8px!important;display:flex!important;flex-direction:column!important;align-items:center!important;gap:14px!important;max-width:220px!important}\nbody.postid-1760 #lvm-shell .bodyscan-illust .mini-phone{max-width:200px!important;padding:3px!important;border-radius:22px!important;border-width:1px!important}\nbody.postid-1760 #lvm-shell .bodyscan-illust .mini-phone .notch{width:40px!important;height:11px!important;border-radius:0 0 7px 7px!important}\nbody.postid-1760 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:18px!important}\n@media (max-width:760px){\n  body.postid-1760 #lvm-shell .bodyscan-illust{max-width:180px!important}\n  body.postid-1760 #lvm-shell .bodyscan-illust .mini-phone{max-width:160px!important;padding:3px!important;border-radius:20px!important}\n  body.postid-1760 #lvm-shell .bodyscan-illust .mini-phone .notch{width:34px!important;height:9px!important;border-radius:0 0 6px 6px!important}\n  body.postid-1760 #lvm-shell .bodyscan-illust .mini-phone .scr{border-radius:16px!important}\n}\n<\/style>\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  \/* Hard fallback: force .rev visible after 2s if IntersectionObserver doesn't fire *\/\n  setTimeout(function(){\n    var shell = document.getElementById('lvm-shell');\n    if(!shell) return;\n    var anyOn = shell.querySelector('.rev.on');\n    if(!anyOn){ shell.classList.add('force-show'); }\n  }, 2000);\n\n  \/* ResizeObserver fallback: ensure charts resize correctly *\/\n  if (typeof ResizeObserver !== 'undefined'){\n    var observer = new ResizeObserver(function(entries){\n      entries.forEach(function(entry){\n        var canvas = entry.target.querySelector('canvas');\n        if (!canvas || !window.Chart) return;\n        var inst = window.Chart.getChart(canvas);\n        if (inst) { try { inst.resize(); } catch(e){} }\n      });\n    });\n    document.querySelectorAll('#lvm-shell .cv-wrap').forEach(function(w){ observer.observe(w); });\n  }\n})();\n<\/script>\n<div id=\"lvm-shell\"><div class=\"progress\" aria-hidden=\"true\"><i id=\"progBar\"><\/i><\/div>\n\n<header class=\"nav\">\n  <div class=\"nav-row\">\n    <a class=\"nav-brand\" href=\"https:\/\/lean-app.com\/no\/\" aria-label=\"Lean forside\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n      <span>Lean<\/span>\n    <\/a>\n    <span class=\"nav-spacer\"><\/span>\n    <a class=\"nav-link\" href=\"https:\/\/lean-app.com\/no\/tdee-calculator\/\">TDEE-kalkulator<\/a>\n    <div class=\"nav-stores\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\" aria-label=\"Last ned fra App Store\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n      <\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\" aria-label=\"Tilgjengelig p\u00e5 Google Play\">\n        <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/header>\n\n<main class=\"wrap\">\n\n<section class=\"hero\" aria-labelledby=\"title\">\n  <div class=\"crumb\"><a href=\"https:\/\/lean-app.com\/no\/\">Hjem<\/a> &nbsp;\/&nbsp; Lean vs Foodvisor<\/div>\n  <div class=\"eyebrow\">Sammenligning &middot; Ern\u00e6ring &amp; TDEE<\/div>\n  <h1 id=\"title\">Lean vs Foodvisor.\n    <span class=\"alt\">Fotoskanningens pioner mot den eneste som setter TDEE-en din sammen p\u00e5 nytt kontinuerlig.<\/span>\n  <\/h1>\n  <p class=\"dek\">Foodvisor ser tallerkenen din. Lean ser det reelle forbruket ditt. To AI-er, to halvdeler av problemet.<\/p>\n  <div class=\"byline\">\n    <img class=\"by-logo\" src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/>\n    <span><strong>Lean-teamet<\/strong> &middot; Lesetid 12&nbsp;min &middot; Oppdatert 15. august 2026<\/span>\n  <\/div>\n  <div class=\"hero-stores\">\n    <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"T\u00e9l\u00e9charger sur l'App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Disponible sur Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" \/>\n    <\/a>\n    <span class=\"or\">Gratis nedlasting<\/span>\n  <\/div>\n\n  <div class=\"hero-bottom\">\n    <div class=\"hero-lead\">\n      Foodvisor er den franske pioneren innen fotoskanning av m\u00e5ltider: du fotograferer tallerkenen din, AI-en gjenkjenner matvarene og ansl\u00e5r porsjonene. P\u00e5 denne halvdelen av problemet er \u00e6ren fortjent. Men den andre halvdelen, forbruket ditt, forblir der en populasjonsformel (Mifflin-St Jeor 1990), pluss en statisk aktivitetsmultiplikator valgt \u00e9n eneste gang ved registreringen. Uten reell m\u00e5lt fettprosent, uten metabolsk tilpasning. Kampen Lean vs Foodvisor avgj\u00f8res alts\u00e5 ikke p\u00e5 fotoet: den avgj\u00f8res p\u00e5 hva appen gj\u00f8r med tallet, over 3 m\u00e5neder med seri\u00f8s deff.\n    <\/div>\n    <div class=\"phone-wrap rev\">\n      <div class=\"phone-stage\">\n        <div class=\"tap-hint mobile\" id=\"tapHintMobile\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Interaktiv demo<\/small>Trykk p\u00e5 skjermen for \u00e5 utforske appen<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 24 24\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M12 4 L12 20 M5 13 L12 20 L19 13\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"tap-hint desktop\" id=\"tapHintDesktop\" aria-hidden=\"true\">\n          <span class=\"th-pill\"><small>Interaktiv demo<\/small>Trykk p\u00e5 skjermen<br>for \u00e5 utforske appen<\/span>\n          <svg class=\"th-arrow\" viewbox=\"0 0 104 34\" fill=\"none\" aria-hidden=\"true\">\n            <path d=\"M4 9 C 34 1, 64 20, 94 27\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\"\/>\n            <path d=\"M86 20 L 94 27 L 84 30\" stroke=\"currentColor\" stroke-width=\"2.6\" fill=\"none\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/>\n          <\/svg>\n        <\/div>\n        <div class=\"phone\" id=\"phone\" role=\"img\" aria-label=\"Oversikt over Lean-appen med drilldown av TDEE\">\n          <div class=\"notch\"><\/div>\n          <div class=\"phone-screen\">\n            <button class=\"phone-back\" id=\"phoneBack\" aria-label=\"Tilbake\">&#8249;<\/button>\n            <div id=\"phoneImg\" class=\"phone-bg tab-depense\" role=\"img\" aria-label=\"Lean-oversikt, Forbruk-fanen\"><\/div>\n            <div class=\"phone-zones\" id=\"phoneZones\">\n              <div class=\"z\" data-sub=\"BMR\"  style=\"top:11%;height:21%\" role=\"button\" tabindex=\"0\" aria-label=\"BMR-detaljer\"><\/div>\n              <div class=\"z\" data-sub=\"NEAT\" style=\"top:33%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"NEAT-detaljer\"><\/div>\n              <div class=\"z\" data-sub=\"EAT\"  style=\"top:50%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"EAT-detaljer\"><\/div>\n              <div class=\"z\" data-sub=\"TEF\"  style=\"top:67%;height:16%\" role=\"button\" tabindex=\"0\" aria-label=\"TEF-detaljer\"><\/div>\n            <\/div>\n            <div class=\"phone-navbar\" id=\"phoneNav\" aria-hidden=\"false\">\n              <button data-tab=\"bilan\"     type=\"button\" aria-label=\"Oversikt-fanen\"><\/button>\n              <button data-tab=\"kcal\"      type=\"button\" aria-label=\"Kalorier-fanen\"><\/button>\n              <button data-tab=\"depense\"   type=\"button\" aria-label=\"Forbruk-fanen\"><\/button>\n              <button data-tab=\"strategie\" type=\"button\" aria-label=\"Strategi-fanen\"><\/button>\n            <\/div>\n          <\/div>\n        <\/div>\n        <div class=\"phone-tabs\" role=\"tablist\" aria-label=\"Naviger i Lean-appen\">\n          <button data-tab=\"bilan\"     type=\"button\">Oversikt<\/button>\n          <button data-tab=\"kcal\"      type=\"button\">Kalorier<\/button>\n          <button data-tab=\"depense\"   type=\"button\" class=\"on\">Forbruk<\/button>\n          <button data-tab=\"strategie\" type=\"button\">Strategi<\/button>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"snippet rev\">\n    <div class=\"lbl\">Raskt svar<\/div>\n    <p>Foodvisor oppfant fotoskanning av m\u00e5ltider i Frankrike og er fortsatt en referanse for \u00e5 identifisere hva du spiser: foto, gjenkjenning av matvarer, anslag av porsjoner. P\u00e5 forbrukssiden derimot st\u00f8tter Foodvisor seg p\u00e5 en populasjonsformel (Mifflin-St Jeor 1990, uten m\u00e5lt fettprosent) og en statisk aktivitetsmultiplikator valgt ved registreringen. Lean tar problemet fra den andre siden: beregne hver TDEE-komponent p\u00e5 nytt (<span data-term=\"BMR\">BMR<span class=\"tt\">Basal Metabolic Rate. Energi brukt i hvile. Hos Lean beregnet p\u00e5 den reelle fettfrie massen via AI BodyScan.<\/span><\/span> p\u00e5 reell fettprosent via en patentert propriet\u00e6r modell, <span data-term=\"NEAT\">NEAT<span class=\"tt\">Non-Exercise Activity Thermogenesis. Forbruk knyttet til skritt og daglige aktiviteter utenom trening.<\/span><\/span> per skritt, <span data-term=\"EAT\">EAT<span class=\"tt\">Exercise Activity Thermogenesis. Forbruk knyttet til trenings\u00f8ktene dine, beregnet via MET.<\/span><\/span> per MET, <span data-term=\"TEF\">TEF<span class=\"tt\">Thermic Effect of Food. Energi brukt p\u00e5 ford\u00f8yelsen. Avhenger av inntatte makroer.<\/span><\/span> per makroer) og modulere BMR med den metabolske tilpasningen kontinuerlig, uten koeffisient \u00e5 velge.<\/p>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"constat\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">00 &middot; Situasjonen<\/span><\/div>\n  <h2 id=\"constat\">Foodvisor ser tallerkenen din, ikke det reelle forbruket ditt<\/h2>\n  <p>Leser du dette, har du trolig allerede installert Foodvisor. Du valgte den nettopp for det ingen gjorde f\u00f8r den: fotografere tallerkenen din og la AI-en gjenkjenne kyllingen, risen, sausen, og ansl\u00e5 porsjonene uten \u00e5 ta frem vekten. Du har oppgitt vekt, h\u00f8yde, alder, kj\u00f8nn, og valgt aktivitetsniv\u00e5et ditt fra en statisk liste. Appen viste deg et kalorim\u00e5l, la oss si 2&nbsp;250&nbsp;kcal for \u00e5 g\u00e5 ned i vekt.<\/p>\n  <p>Du spilte med. Du skannet m\u00e5ltidene dine, korrigerte porsjonene n\u00e5r AI-en n\u00f8lte, holdt en ren logg dag etter dag. De 6 f\u00f8rste ukene fungerer det. Du g\u00e5r ned. Du er forn\u00f8yd. S\u00e5 rundt uke 8 stivner vekten. Du strammer inn. Du g\u00e5r ned til 2&nbsp;000&nbsp;kcal. Igjen, ingenting r\u00f8rer seg.<\/p>\n\n  <div class=\"statement\">\n    <div class=\"num\">&minus;10 til &minus;15&nbsp;%<\/div>\n    <div class=\"lbl\">m\u00e5lt nedgang i TDEE etter 4 til 6 uker med underskudd p\u00e5 &minus;500&nbsp;kcal\/dag. Foodvisor oppdager det ikke. Kalorim\u00e5let ditt forblir fastl\u00e5st p\u00e5 aktivitetsniv\u00e5et ditt fra 100&nbsp;dager siden.<\/div>\n  <\/div>\n\n  <p>Tenk deg at Foodvisor viser deg en TDEE p\u00e5 2&nbsp;500&nbsp;kcal. Du spiser 2&nbsp;250 (teoretisk underskudd p\u00e5 250&nbsp;kcal). Men i virkeligheten har din <a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/depense-energetique-totale-v2\/\">TDEE har sunket til 2&nbsp;200&nbsp;kcal<\/a> p\u00e5 grunn av den metabolske tilpasningen. Du er i overskudd p\u00e5 50&nbsp;kcal uten \u00e5 vite det. Ingen sjanse til \u00e5 fortsette \u00e5 g\u00e5 ned, selv med markedets reneste logg.<\/p>\n  <p>Foodvisors l\u00f8fte er tydelig og holdes: du vet hva som er p\u00e5 tallerkenen din uten \u00e5 veie noe. Det er verdifullt. Det Foodvisor ikke gj\u00f8r, er \u00e5 <a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/comment-compter-ses-calories\/\">beregne forbruket ditt p\u00e5 nytt<\/a> gjennom ukene i underskudd. Og det er n\u00f8yaktig der l\u00f8ftet stopper, mens det er spaken som gj\u00f8r at du g\u00e5r ned i vekt.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p1\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">01 &middot; Problem 1<\/span><\/div>\n  <h2 id=\"p1\">BMR-formelen fra 1990, uten m\u00e5lt fettprosent<\/h2>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figur 1 &middot; Mann 1,80&nbsp;m, 120&nbsp;kg, 30&nbsp;% BF<\/span><span class=\"r\">kcal<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartBMR\" aria-label=\"BMR-sammenligning Mifflin-St Jeor 2500 kcal vs Leans patenterte egenutviklede modell 2000 kcal, forskjell p\u00e5 500 kcal\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Ansl\u00e5tt BMR.<\/strong> Leans patenterte propriet\u00e6re modell tar hensyn til den fettfrie massen. Mifflin-St Jeor (populasjonsformel, uten fettprosent) gj\u00f8r det ikke. Avvik p\u00e5 500&nbsp;kcal, tilsvarende en hel lunsj.<\/p>\n  <\/div>\n\n  <p>For \u00e5 beregne basalmetabolismen din (BMR, energien du forbrenner i hvile) tar Foodvisor utgangspunkt i profilen din: vekt, h\u00f8yde, alder, kj\u00f8nn. Det er logikken i nesten alle forbrukerrettede kaloritrackere, arvet fra populasjonsformler som Mifflin-St Jeor. Og vi m\u00e5 v\u00e6re \u00e6rlige: det er bedre enn Harris-Benedict 1919 som andre apper fortsatt bruker.<\/p>\n  <p>Mifflin-St Jeor er fra 1990 (PubMed 2305711). Utvalget er stort (498 fors\u00f8kspersoner), metoden med indirekte kalorimetri er seri\u00f8s, formelen er kalibrert p\u00e5 en moderne populasjon: 10 \u00d7 vekt (kg) + 6,25 \u00d7 h\u00f8yde (cm) \u2212 5 \u00d7 alder \u2212 161 (kvinner) eller +5 (menn).<\/p>\n  <p>Problemet er ikke den valgte formelen. Problemet er det ingen formel av denne typen kan se: <strong>den tar bare hensyn til vekten. Ikke fettprosenten. Ikke den fettfrie massen.<\/strong> Ingen felt i Foodvisors onboarding sp\u00f8r om fettprosenten din, og ingen m\u00e5ling finnes i appen.<\/p>\n  <p>Men siden 1980-tallet har vi visst at <strong>fettmassen bruker sv\u00e6rt lite energi<\/strong> sammenlignet med resten av kroppen. Leveren, hjernen, hjertet, nyrene og fremfor alt musklene er de reelle forbrukspostene. Fettmassen er inert. En person med 30&nbsp;% fettprosent forbrenner slett ikke like mye som en person med 10&nbsp;% fettprosent, selv ved lik vekt.<\/p>\n  <p>Frankenfield 2013 (PubMed 23631843) sammenlignet Mifflin-St Jeor med referansemetoden indirekte kalorimetri p\u00e5 kohorter med og uten fedme. Resultat: 87&nbsp;% presisjon hos dem uten fedme, og bare <strong>75&nbsp;% hos dem med fedme<\/strong>. En nyere studie (PMC11820646) viser at ved BMI over 35 bommer Mifflin med <strong>250 til 315&nbsp;kcal per dag<\/strong>. Det tilsvarer et helt mellomm\u00e5ltid i beregningen av et underskudd.<\/p>\n  <p>500&nbsp;kcal er ikke ingenting. Hvis appen sier \u00ab&nbsp;BMR-en din er 2&nbsp;500&nbsp;\u00bb og den i virkeligheten er 2&nbsp;000, er alt som f\u00f8lger feil: underskuddsm\u00e5let ditt, den ukentlige vekttapsprognosen din, makrofordelingen din beregnet i prosent av TDEE. Og ingen tallerkenfoto, uansett hvor godt gjenkjent, retter et feil m\u00e5l.<\/p>\n\n  <div class=\"bodyscan-illust\" style=\"margin:40px auto 8px;display:flex;flex-direction:column;align-items:center;gap:14px;max-width:200px\">\n    <div class=\"mini-phone\" style=\"max-width:200px\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"BodyScan IA Lean : bodyfat mesur\u00e9 par photo en 5 secondes\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n    <div class=\"mini-cap\">Reell fettprosent<strong>Foto, 5 sekunder<\/strong><\/div>\n  <\/div>\n\n  <div class=\"statement\">\n    <div class=\"num\">400&nbsp;kcal<\/div>\n    <div class=\"lbl\">i avvik mellom to menn p\u00e5 80&nbsp;kg, den ene med 10&nbsp;% fettprosent (BMR 1&nbsp;900), den andre med 30&nbsp;% (BMR 1&nbsp;500). En vektbasert formel viser dem samme tall.<\/div>\n  <\/div>\n\n  <p>Delkonklusjon: hvis en app beregner BMR-en din utelukkende fra vekt, h\u00f8yde, alder og kj\u00f8nn, kan ikke resultatet individualiseres. Det er matematisk umulig. Selv med den beste tallerkengjenkjenningen som inndata.<\/p>\n<\/section>\n\n<section aria-labelledby=\"p2\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">02 &middot; Problem 2<\/span><\/div>\n  <h2 id=\"p2\">Aktivitetsmultiplikatoren, valgt \u00e9n gang for alle<\/h2>\n  <p>Her blir det alvorlig. Og det er trolig punktet ingen har forklart deg.<\/p>\n  <p>N\u00e5r BMR-en din er ansl\u00e5tt, m\u00e5 Foodvisor g\u00e5 videre til total TDEE. <a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/depense-energetique-totale-v2\/\">TDEE er BMR + alt det andre<\/a> : forbruket knyttet til skritt, daglige aktiviteter, trening og ford\u00f8yelse. Alt som ikke er basalmetabolisme.<\/p>\n  <p>Hvordan gj\u00f8r Foodvisor det&nbsp;? Som nesten alle trackere: den ber deg, ved registreringen, velge aktivitetsniv\u00e5et ditt fra en statisk liste. Disse faktorene kalles i idrettsvitenskapen <strong>PAL-niv\u00e5er<\/strong> (Physical Activity Level), det er bare en multiplikator brukt p\u00e5 BMR-en din:<\/p>\n  <ul>\n    <li>Stillesittende (PAL 1,2): kontor, lite gange<\/li>\n    <li>Lett aktiv (PAL 1,375): sporadisk gange<\/li>\n    <li>Aktiv (PAL 1,55): trening 3 til 5 ganger i uken<\/li>\n    <li>Sv\u00e6rt aktiv (PAL 1,725): intens trening nesten daglig<\/li>\n    <li>Ekstremt aktiv (PAL 1,9): sv\u00e6rt intens trening eller fysisk arbeid<\/li>\n  <\/ul>\n  <p>Og etter valget ditt multipliserer appen BMR-en din med den tilh\u00f8rende koeffisienten. Det er alt. Det er alt som ligger bak det daglige kalorim\u00e5let ditt. En boks DU krysset av \u00e9n eneste gang ved registreringen. Ofte for seks m\u00e5neder siden. Uendret siden.<\/p>\n  <p>Og her er den stille fellen: denne tiln\u00e6rmingen er <strong>ekstremt uperfekt<\/strong>. Forskjellen mellom en dag der du er klistret til sofaen foran Netflix og en dag der du drar til Disneyland med barna og g\u00e5r 15&nbsp;km, <strong>det er over 1&nbsp;000&nbsp;kcal<\/strong>. Ingen av de 5 boksene fanger det.<\/p>\n  <p>Foodvisor kan likevel f\u00f8lge aktiviteten din: appen kan telle skrittene dine og registrere \u00f8ktene dine. Men disse dataene brukes f\u00f8rst og fremst til \u00e5 vise aktiviteten din, ikke til \u00e5 sette sammen en komplett TDEE: kalorim\u00e5let ditt hviler fortsatt p\u00e5 multiplikatoren valgt ved onboarding, og treningsforbruket legges til uten at NEAT og EAT skilles ordentlig.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figur 2 &middot; 7 reelle dager<\/span><span class=\"r\">kcal\/dag<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartNEAT\" aria-label=\"Daglig variasjon i kaloriforbruket over 7 dager, mot 2400 kcal fast if\u00f8lge Foodvisor\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Reelt forbruk<\/strong> m\u00e5lt over 7&nbsp;dager for en Lean-bruker. Den gr\u00f8nne linjen er det Foodvisor viste (2&nbsp;400&nbsp;kcal fast, statisk multiplikator \u00d7 BMR). De rosa merknadene viser hvorfor hver dag beveger seg.<\/p>\n  <\/div>\n\n  <p>Du kan ikke redusere aktivitetsniv\u00e5et ditt til en statisk boks. Du er kanskje aktiv de ukene du har lite hjemmekontor, og stillesittende de ukene du ikke forlater kontoret. Du er kanskje aktiv om sommeren og stillesittende om vinteren. Du er kanskje aktiv fra tirsdag til fredag og stillesittende i helgen.<\/p>\n  <p>Hvilken boks skal du krysse av denne uken? Sannheten er at ingen av de 5 vil v\u00e6re riktig. Og dermed gir Foodvisor deg en TDEE som systematisk er frakoblet virkeligheten.<\/p>\n  <p>N\u00f8kkelpoenget i denne artikkelen: selv med en perfekt BMR-formel ville den statiske multiplikatoren v\u00e6re nok til \u00e5 \u00f8delegge alt. Du kan ikke ansl\u00e5 en <a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/neat-depense-non-sportive\/\">NEAT<\/a>, en EAT og en <a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/effet-thermique-des-aliments\/\">TEF<\/a> med \u00e9n enkelt multiplikator brukt p\u00e5 BMR. Det er konseptuelt absurd.<\/p>\n  <p>Du har skj\u00f8nt det: <strong>en BMR-formel uten fettprosent, pluss en statisk tiln\u00e6rming av alt det andre, gir sv\u00e6rt liten sjanse til \u00e5 n\u00e5 m\u00e5lene dine over 3 til 6 m\u00e5neder.<\/strong> Uansett hvor ren loggen er p\u00e5 tallerkensiden.<\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Se din reelle TDEE, delt opp i BMR + NEAT + EAT + TEF. Gratis nedlasting.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"p3\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">03 &middot; Problem 3<\/span><\/div>\n  <h2 id=\"p3\">Den metabolske tilpasningen, aldri modellert<\/h2>\n  <p>Dette er sluttbossen. Det fineste begrepet. Og trolig det viktigste.<\/p>\n  <p>N\u00e5r du er i kaloriunderskudd, forst\u00e5r kroppen din at den f\u00e5r mindre energi enn f\u00f8r. For \u00e5 beskytte seg g\u00e5r den i sparemodus. N\u00f8yaktig som str\u00f8msparingsmodusen p\u00e5 iPhonen din: alt fortsetter \u00e5 fungere, men med mindre energi. BMR-en din synker. NEAT-en din synker. EAT-en din synker.<\/p>\n  <p>Det er det som kalles metabolsk tilpasning. Den vitenskapelige litteraturen er klar og reproduserbar: M\u00fcller 2015 (PubMed 26399868, ny gjennomgang av Minnesota), Doucet 2001 (PubMed 11430776), Nunes 2020 (PMC7484122) over 6 uker i underskudd. Her er tallene:<\/p>\n  <ul>\n    <li>Underskudd p\u00e5 &minus;250&nbsp;kcal per dag, over 2 til 8 uker: tilpasning p\u00e5 <strong>5 til 10&nbsp;%<\/strong> (TDEE synker til 90-95&nbsp;% av utgangsniv\u00e5et)<\/li>\n    <li>Underskudd p\u00e5 &minus;500&nbsp;kcal per dag: <strong>10 til 15&nbsp;%<\/strong> tilpasning (TDEE synker til 85-90&nbsp;%)<\/li>\n    <li>Underskudd p\u00e5 &minus;750&nbsp;kcal per dag: <strong>15 til 25&nbsp;%<\/strong> tilpasning (TDEE synker til 75-85&nbsp;%)<\/li>\n  <\/ul>\n  <p>Lean-konvensjon: 100&nbsp;% = optimalt, 90&nbsp;% = 10&nbsp;% tilpasning. Og siden NEAT, EAT og TEF alle avhenger direkte av BMR, p\u00e5virkes nesten hele TDEE-en.<\/p>\n\n  <div class=\"fig\">\n    <div class=\"fig-head\"><span class=\"l\">Figur 3 &middot; 8 uker i underskudd<\/span><span class=\"r\">kcal\/dag<\/span><\/div>\n    <div class=\"fig-body\"><div class=\"cv-wrap\" style=\"position:relative;width:100%;height:380px;min-height:340px\"><canvas id=\"chartAdapt\" aria-label=\"TDEE som faller fra 2500 til 2150 kcal over 8 uker, mot 2500 fast if\u00f8lge Foodvisor\"><\/canvas><\/div><\/div>\n    <p class=\"fig-cap\"><strong>Reell TDEE<\/strong> over 8 uker med underskudd p\u00e5 &minus;500&nbsp;kcal\/dag. Den rosa kurven synker. Foodvisor-linjen forblir flat. I uke 6 er du allerede p\u00e5 vedlikehold. Uten \u00e5 ha endret noe.<\/p>\n  <\/div>\n\n  <p>Konkret: hvis du hadde planlagt et underskudd p\u00e5 10&nbsp;% p\u00e5 en TDEE p\u00e5 2&nbsp;500 (alts\u00e5 spise 2&nbsp;250 per dag), og kroppen din tilpasser seg med 10&nbsp;%, er den reelle TDEE-en din n\u00e5 2&nbsp;250. Du er p\u00e5 vedlikehold. Du g\u00e5r ikke ned lenger.<\/p>\n  <p>Fellen er at det er snikende. I starten g\u00e5r du ned. Du er forn\u00f8yd. Du fortsetter. Men uke etter uke akkumuleres tilpasningen. Og p\u00e5 et tidspunkt, uten \u00e5 ha endret noe i loggingen din, <strong>slutter du \u00e5 g\u00e5 ned<\/strong>.<\/p>\n  <p>95&nbsp;% av folk g\u00e5r gjennom dette uten \u00e5 forst\u00e5 det. De skylder p\u00e5 viljestyrken sin. De skylder p\u00e5 sitt \u00ab&nbsp;\u00f8delagte stoffskifte&nbsp;\u00bb. De g\u00e5r i gang med hardere dietter, noe som forverrer tilpasningen. Spiral.<\/p>\n  <p>Foodvisor beregner aldri den metabolske tilpasningen. Den gir deg et fast kalorim\u00e5l s\u00e5 lenge du ikke oppdaterer vekten og aktivitetsniv\u00e5et ditt manuelt. Du kan skanne tallerkenene dine med eksemplarisk regelmessighet, men n\u00e5r du stagnerer etter 6 uker med deff, aner ikke appen hvorfor.<\/p>\n<\/section>\n\n<section aria-labelledby=\"solution\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">04 &middot; Lean-l\u00f8sningen<\/span><\/div>\n  <h2 id=\"solution\">Hvordan Lean l\u00f8ser hvert av de 3 problemene<\/h2>\n  <p>Foodvisor har satt en standard for fotoskanning av en rett, og gjenkjenningen av fransk mat er fortsatt utmerket. Problemet er ikke det den ser p\u00e5 tallerkenen din, det er det den ikke ser av kroppen din&nbsp;: forbruket forblir ansl\u00e5tt med en populasjonsformel multiplisert med et aktivitetsniv\u00e5. Lean gj\u00f8r begge deler&nbsp;: AI-fotoskanning <em>og<\/em> m\u00e5ling av hver TDEE-komponent (BMR&nbsp;+&nbsp;NEAT&nbsp;+&nbsp;EAT&nbsp;+&nbsp;TEF) pluss den metabolske tilpasningen. Her er detaljene.<\/p>\n\n  <div class=\"method\">\n    <div class=\"m-phone\">\n      <div class=\"duo-row\">\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-bodyscan-result.webp\" alt=\"R\u00e9sultat BodyScan IA : pourcentage de masse grasse mesur\u00e9 par photo\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Trinn 1<strong>AI BodyScan<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_BMR.webp\" alt=\"\u00c9cran BMR Lean : m\u00e9tabolisme de base calcul\u00e9 sur la masse maigre\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\">Trinn 2<strong>Omberegnet BMR<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div>\n      <div class=\"m-tag\">BMR p\u00e5 reell fettprosent<\/div>\n      <h3>Patentert propriet\u00e6r modell, basert p\u00e5 fettfri masse<\/h3>\n      <p>\u00c5 telle inntatte kalorier perfekt er nyttel\u00f8st hvis forbrukte kalorier er 300&nbsp;kcal feil. Lean beregner stoffskiftet p\u00e5 din <strong>fettfri masse<\/strong>, den eneste som faktisk forbruker i hvile, og ikke p\u00e5 r\u00e5vekten din.<\/p>\n      <p>Den <strong>AI BodyScan<\/strong> bruker p\u00e5 kroppen din det Foodvisor bruker p\u00e5 tallerkenen din&nbsp;: ett foto, en modell trent p\u00e5 en bank av DEXA-skanninger, fettprosenten din p\u00e5 noen sekunder, gjentatt hver uke.<\/p>\n      <p>Ingen hudfoldsm\u00e5ler, ingen impedansvekt, ingen DEXA. Samme enkelhet som en m\u00e5ltidsskanning, anvendt p\u00e5 kroppssammensetningen din.<\/p>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Ingen aktivitetskoeffisient<\/div>\n      <h3>NEAT, EAT, TEF beregnet hver for seg<\/h3>\n      <p><strong>NEAT.<\/strong> De reelle skrittene dine kommer via HealthKit (iOS) eller Google Fit (Android) og blir til kalorier etter stoffskiftet ditt. Det er den mest variable posten i dagen, og den et oppgitt aktivitetsniv\u00e5 flater helt ut.<\/p>\n      <p><strong>EAT.<\/strong> Hver \u00f8kt tallfestes per MET p\u00e5 den reelle innsatstiden din, hviletid ekskludert. \u00c5 telle en time styrketrening som en time l\u00f8ping forvrenger balansen med flere hundre kcal per uke.<\/p>\n      <p><strong>TEF.<\/strong> Foodvisor identifiserer matvarene dine, Lean utleder ford\u00f8yelseskostnaden av dem&nbsp;: 20 til 30&nbsp;% av kaloriene for proteiner, 5 til 10&nbsp;% for karbohydrater, 1 til 3&nbsp;% for fett, i stedet for den faste satsen p\u00e5 10&nbsp;% brukt overalt.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-row\" style=\"margin:0;gap:10px\">\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_NEAT.webp\" alt=\"\u00c9cran NEAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">NEAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_EAT.webp\" alt=\"\u00c9cran EAT Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">EAT<\/strong><\/div>\n        <\/div>\n        <div>\n          <div class=\"mini-phone tiny\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_TEF.webp\" alt=\"\u00c9cran TEF Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n          <div class=\"mini-cap\" style=\"font-size:10px\"><strong style=\"font-size:12px\">TEF<\/strong><\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"method flip\">\n    <div>\n      <div class=\"m-tag\">Automatisk metabolsk tilpasning<\/div>\n      <h3>En verdensnyhet i en forbrukerapp<\/h3>\n      <p><strong>Den metabolske tilpasningen.<\/strong> Ingen m\u00e5ltidsskanning oppdager at stoffskiftet ditt har bremset med 12&nbsp;% etter \u00e5tte uker. Lean ansl\u00e5r det etter de publiserte intervallene (M\u00fcller 2015, Doucet 2001) og korrigerer m\u00e5let ditt deretter.<\/p>\n      <p>Over 10 til 15&nbsp;% tilpasning kan appen anbefale en retur til vedlikehold for \u00e5 sette fart p\u00e5 stoffskiftet igjen f\u00f8r du starter p\u00e5 nytt.<\/p>\n      <p>Ingen aktivitetsmultiplikator \u00e5 velge. Hver komponent m\u00e5les, uke for uke.<\/p>\n    <\/div>\n    <div class=\"m-phone\">\n      <div class=\"mini-phone solo\" style=\"max-width:240px!important;width:240px;padding:6px!important;border-radius:24px!important;border-width:2px!important\"><div class=\"notch\" style=\"width:60px!important;height:14px!important;border-radius:0 0 9px 9px!important\"><\/div><div class=\"scr\" style=\"border-radius:18px!important\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-screen_depense.webp\" alt=\"\u00c9cran d\u00e9pense totale Lean avec adaptation m\u00e9tabolique\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Metode<strong>Metabolsk tilpasning<\/strong><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tab\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">05 &middot; Sammenligningstabell<\/span><\/div>\n  <h2 id=\"tab\">Lean mot Foodvisor, kriterium for kriterium<\/h2>\n  <p>\u00c6rlig lesning av styrkene og svakhetene til hver app. Ingen kriterier gjelder pris.<\/p>\n\n  <div class=\"brand-banner\" style=\"display:grid;grid-template-columns:1fr 1fr;gap:16px;margin:24px 0 18px;padding:0\">\n  <div style=\"background:#FFF1F5;border:1.5px solid #FF2D6E;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"Lean\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#FF2D6E;letter-spacing:-0.2px\">Lean<\/div>\n  <\/div>\n  <div style=\"background:#EFF7EF;border:1.5px solid #6ABF6C;border-radius:14px;padding:20px 18px;display:flex;flex-direction:column;align-items:center;text-align:center;gap:10px\">\n    <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/08\/fv-logo-foodvisor.jpg\" alt=\"Foodvisor\" width=\"64\" height=\"64\" loading=\"lazy\" decoding=\"async\" style=\"width:64px;height:64px;border-radius:14px;display:block;object-fit:cover\" \/>\n    <div style=\"font-family:-apple-system,BlinkMacSystemFont,'SF Pro Display',sans-serif;font-size:18px;font-weight:700;color:#6ABF6C;letter-spacing:-0.2px\">Foodvisor<\/div>\n  <\/div>\n<\/div>\n<div class=\"table\" role=\"table\" aria-label=\"Sammenligning Lean mot Foodvisor\">\n    <div class=\"table-row head\" role=\"row\">\n      <div role=\"columnheader\">Kriterium<\/div>\n      <div class=\"brand-cell lean\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Lean<\/span><\/div>\n      <div class=\"brand-cell\" role=\"columnheader\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/08\/fv-logo-foodvisor.jpg\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> <span>Foodvisor<\/span><\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">BMR-formel<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Patentert propriet\u00e6r modell (fettfri masse)<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Populasjonsformel (Mifflin-St Jeor 1990)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Tar hensyn til fettprosent<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, m\u00e5lt i appen<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Nei, bare vekt-h\u00f8yde-alder-kj\u00f8nn<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">M\u00e5ling av fettprosent i appen<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> AI BodyScan via foto<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Nei<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">NEAT (skritt, aktivitet utenom trening)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Beregnet p\u00e5 reelle skritt hver dag<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> Skritt fulgt, men m\u00e5l basert p\u00e5 den statiske multiplikatoren<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">EAT (treningsforbruk)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Per idrett via MET, effektiv tid<\/div>\n      <div class=\"cell\"><span class=\"icn mid\">&minus;<\/span> \u00d8kter registrert, lagt til et fastl\u00e5st m\u00e5l<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">TEF (ford\u00f8yelse)<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Beregnet etter makroer, integrert i TDEE<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Ikke integrert i forbruksberegningen<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Metabolsk tilpasning<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Automatisk, uke for uke<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Nei<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Aktivitetskoeffisient \u00e5 velge<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Nei, beregnet p\u00e5 reelle data<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Ja, statisk multiplikator valgt ved registreringen<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">AI-fotoskanning av en rett<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, ubegrenset<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, den historiske pioneren (2018)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Visuell gjenkjenning av matvarer<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, moderne AI-fotoskanning<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Referanse i det franske markedet, \u00e5r med trening<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Strekkodeskanning<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Matvaredatabase<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> USDA + OpenFoodFacts, kuratert<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Bred base, franske produkter godt dekket<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Coaching av ern\u00e6ringsfysiologer<\/div>\n      <div class=\"cell lean\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Utenfor omfang, appen veileder via Progresjonspyramiden<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, autoriserte ern\u00e6ringsfysiologer (eget tilbud)<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Anbefaling kaloriunderskudd<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Tilpasset den reelle TDEE-en<\/div>\n      <div class=\"cell\"><span class=\"icn no\"><svg viewbox=\"0 0 12 12\"><path d=\"M3 3 L9 9 M9 3 L3 9\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\"\/><\/svg><\/span> Fast m\u00e5l, manuell omberegning kreves<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Fransk app<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Ja, f\u00f8dt i Paris<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Omd\u00f8mme og publikumsst\u00f8rrelse<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> 4,7\/5, 10&nbsp;000+ brukere, ung fransk app<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Anerkjent pioner innen fotoskanning, sterk kjennskap i Frankrike<\/div>\n    <\/div>\n    <div class=\"table-row\" role=\"row\">\n      <div class=\"crit\">Forretningsmodell<\/div>\n      <div class=\"cell lean\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Premium, 7 dagers gratis pr\u00f8veperiode p\u00e5 \u00e5rsabonnementet<\/div>\n      <div class=\"cell\"><span class=\"icn ok\"><svg viewbox=\"0 0 12 12\"><path d=\"M2 6.5 L5 9 L10 3.5\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\"\/><\/svg><\/span> Gratisversjon, coaching som valg<\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"tracking\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">06 &middot; Sporing<\/span><\/div>\n  <h2 id=\"tracking\">3 metoder for \u00e5 logge et m\u00e5ltid<\/h2>\n  <p>Foodvisor beviste at ett foto kunne erstatte manuell inntasting. Lean tar denne ideen videre og utvider den&nbsp;: tre registreringsmetoder etter situasjonen, for \u00e5 holde ut over tid.<\/p>\n\n  <div class=\"mini-row\">\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-database.webp\" alt=\"Recherche dans la base de donn\u00e9es USDA + OpenFoodFacts\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Metode 1<strong>Database<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-codebarre.webp\" alt=\"Scan de code-barres dans Lean\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Metode 2<strong>Strekkode<\/strong><\/div>\n    <\/div>\n    <div>\n      <div class=\"mini-phone\"><div class=\"notch\"><\/div><div class=\"scr\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-scania.webp\" alt=\"Scan photo IA d'un plat\" width=\"1179\" height=\"2556\" loading=\"lazy\" decoding=\"async\" \/><\/div><\/div>\n      <div class=\"mini-cap\">Metode 3<strong>AI-fotoskanning<\/strong><\/div>\n    <\/div>\n  <\/div>\n\n  <ol>\n    <li><strong>S\u00f8k i databasen.<\/strong> Kuratert base, USDA + OpenFoodFacts. Ingen st\u00f8y fra brukere, ingen \u00ab&nbsp;Grillet kylling&nbsp;\u00bb lagt inn 47 ganger av 47 ulike brukere med 47 ulike verdier.<\/li>\n    <li><strong>Strekkodeskanning.<\/strong> Standard. Du skanner pastapakken din, du f\u00e5r makroene.<\/li>\n    <li><strong>AI-fotoskanning av en rett.<\/strong> Du tar bilde av tallerkenen din, AI-en gjenkjenner matvarene, du f\u00e5r kalorier og makroer per matvare. Refleksen du allerede har hvis du kommer fra Foodvisor: du beholder den som den er.<\/li>\n  <\/ol>\n  <p>Leans AI-fotoskanning spiller samme rolle som Foodvisors for m\u00e5ltider spist ute. Forskjellen ligger et annet sted&nbsp;: det Lean deretter gj\u00f8r med disse kaloriene, ved \u00e5 stille dem opp mot et m\u00e5lt og ikke ansl\u00e5tt forbruk.<\/p>\n  <p>Utover m\u00e5ltidet viser Lean en TDEE som oppdateres i l\u00f8pet av dagen etter skrittene dine. \u00c5 skanne en tallerken perfekt mot et fastl\u00e5st kalorim\u00e5l er ikke nok.<\/p>\n  <p>Og over det, Progresjonspyramiden&nbsp;:<\/p>\n\n  <div class=\"pyramid\" aria-label=\"Leans Progresjonspyramide\">\n    <div class=\"level l1\"><span>Etterlevelse<\/span><span class=\"k\">Grunnmur<\/span><\/div>\n    <div class=\"level l2\"><span>Kalorim\u00e5l<\/span><span class=\"k\">Etasje 2<\/span><\/div>\n    <div class=\"level l3\"><span>Skritt \/ NEAT<\/span><span class=\"k\">Etasje 3<\/span><\/div>\n    <div class=\"level l4\"><span>Makron\u00e6ringsstoffer<\/span><span class=\"k\">Topp<\/span><\/div>\n  <\/div>\n  <div class=\"pyramid-cap\">Ikke hopp over trinn. Hvis du ikke er regelmessig i loggingen, er det nyttel\u00f8st \u00e5 optimalisere makroene p\u00e5 prosenten.<\/div>\n<\/section>\n\n<section aria-labelledby=\"foodvisor-better\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">07 &middot; \u00c6rlighet<\/span><\/div>\n  <h2 id=\"foodvisor-better\">Det Foodvisor gj\u00f8r bedre<\/h2>\n  <p>Lean er ikke perfekt, og Foodvisor har flere reelle styrker man m\u00e5 anerkjenne. \u00c6rlig lesning, kriterium for kriterium, p\u00e5 aksene der pioneren fortsatt leder. Ingen av disse aksene er sekund\u00e6re: de er reelle pilarer i Foodvisors l\u00f8fte.<\/p>\n\n  <div class=\"scorecard rev\" aria-label=\"Scorecard Foodvisor overfor Lean p\u00e5 4 akser\">\n    <div class=\"scorecard-head\">\n      <div class=\"h-crit\">Akse<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/08\/fv-logo-foodvisor.jpg\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Foodvisor<\/div>\n      <div class=\"h-brand\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-logo-lean-square-scaled.webp\" alt=\"\" width=\"512\" height=\"512\" loading=\"lazy\" decoding=\"async\" \/> Lean<\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Visuell gjenkjenning av en tallerken<\/div>\n      <div class=\"bar mfp\" data-brand=\"FOODVISOR\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:80%\"><\/i><\/div><div class=\"v\">8,0<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Automatisk anslag av porsjoner<\/div>\n      <div class=\"bar mfp\" data-brand=\"FOODVISOR\"><div class=\"b\"><i style=\"width:90%\"><\/i><\/div><div class=\"v\">9,0<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:75%\"><\/i><\/div><div class=\"v\">7,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Menneskelig coaching (autoriserte ern\u00e6ringsfysiologer)<\/div>\n      <div class=\"bar mfp\" data-brand=\"FOODVISOR\"><div class=\"b\"><i style=\"width:92%\"><\/i><\/div><div class=\"v\">9,2<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:25%\"><\/i><\/div><div class=\"v\">2,5<\/div><\/div>\n    <\/div>\n    <div class=\"scorecard-row\">\n      <div class=\"crit\">Forsprang p\u00e5 fotoskanning (fransk marked)<\/div>\n      <div class=\"bar mfp\" data-brand=\"FOODVISOR\"><div class=\"b\"><i style=\"width:95%\"><\/i><\/div><div class=\"v\">9,5<\/div><\/div>\n      <div class=\"bar lean\" data-brand=\"LEAN\"><div class=\"b\"><i style=\"width:40%\"><\/i><\/div><div class=\"v\">4,0<\/div><\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>\u00c6rlig lesning.<\/strong> P\u00e5 tallerkengjenkjenning skapte Foodvisor kategorien i Frankrike i 2018, og AI-en har \u00e5r med treningsforsprang: identifisering av matvarer, anslag av porsjoner uten vekt, h\u00e5ndtering av sammensatte retter. Det er dens historiske lekeplass, og der forblir den referansen. P\u00e5 menneskelig oppf\u00f8lging tilbyr Foodvisor oppf\u00f8lging av autoriserte ern\u00e6ringsfysiologer direkte i appen: Lean tilbyr ikke det, og p\u00e5st\u00e5r ikke \u00e5 erstatte det. Leans AI-fotoskanning er moderne, ubegrenset og mer enn tilstrekkelig for daglig bruk, men Lean gj\u00f8r ikke krav p\u00e5 forspranget p\u00e5 dette feltet.<\/p>\n  <p>Hvis hovedvinkelen din er den mest innarbeidede tallerkenidentifiseringen som finnes, eller menneskelig coaching integrert i appen, er Foodvisor mer relevant enn Lean. Hvis vinkelen din er presisjonen i <a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/tdee-calculator\/\">TDEE-beregning<\/a>, fettprosenten m\u00e5lt hver uke via AI BodyScan, og den automatiske metabolske tilpasningen, er det n\u00f8yaktig det som nettopp er vist i de 3 foreg\u00e5ende avsnittene. Noen kj\u00f8rer begge appene parallelt mens de velger, og det er helt forsvarlig.<\/p>\n<\/section>\n\n<section aria-labelledby=\"forwho\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">08 &middot; For hvem<\/span><\/div>\n  <h2 id=\"forwho\">Hvem Lean er laget for<\/h2>\n  <p>4 profiler. Kjenner du deg igjen i minst \u00e9n, er Lean trolig laget for deg.<\/p>\n\n  <div class=\"persona\">\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Du har brukt Foodvisor seri\u00f8st og ikke g\u00e5tt ned<\/h4>\n        <p>Du har skannet tallerkenene dine, korrigert porsjonene, fulgt et \u00e6rlig underskudd i ukevis, og du stagnerer. Det er ikke fotoet som er skyldig, det er det fastl\u00e5ste m\u00e5let beregnet uten fettprosent. Lean retter det ved roten via BMR p\u00e5 reell fettprosent.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Du stagnerer etter flere uker med deff<\/h4>\n        <p>Plat\u00e5 som varer etter 4 til 8 uker. Det er den metabolske tilpasningen. Lean beregner den automatisk og justerer m\u00e5let ditt hver uke.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Du vil forst\u00e5 stoffskiftet ditt<\/h4>\n        <p>Lean viser hver komponent (BMR, NEAT, EAT, TEF) og forklarer deretter tilpasningen separat, i stedet for \u00e5 skjule alt bak ett enkelt tall. Du ser hvor hver forbrukt kcal kommer fra.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"persona-it match\">\n      <div class=\"pic\"><svg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.4\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 12 L9 18 L21 5\"\/><\/svg><\/div>\n      <div>\n        <h4>Du vil ha en logging som varer i 12 m\u00e5neder<\/h4>\n        <p>AI-fotoskanning + kuratert base + strekkode dekker alle bruksomr\u00e5der, fra r\u00e5varen til pizzaen p\u00e5 restaurant. Det er det som utgj\u00f8r forskjellen mellom \u00e5 holde ut og \u00e5 gi opp.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <p style=\"margin-top:30px\"><strong>Foodvisor er fortsatt mer relevant for<\/strong>&nbsp;: menneskelig coaching av autoriserte ern\u00e6ringsfysiologer direkte i appen, og den mest innarbeidede tallerkengjenkjenningen i det franske markedet. Presisjonen i forbruksberegningen og den metabolske tilpasningen er rett og slett ikke en del av hovedl\u00f8ftet.<\/p>\n<\/section>\n\n<section aria-labelledby=\"migrate\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">09 &middot; Migrasjon<\/span><\/div>\n  <h2 id=\"migrate\">Bytt fra Foodvisor til Lean (eller bruk begge) p\u00e5 3 minutter<\/h2>\n\n  <div class=\"steps\">\n    <div class=\"step\"><div class=\"sn\">01<\/div><h4>Last ned Lean<\/h4><p>App Store eller Play Store. Registrering p\u00e5 30 sekunder.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">02<\/div><h4>AI BodyScan<\/h4><p>Ett foto, 5 sekunder. Du f\u00e5r fettprosenten din.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">03<\/div><h4>Vekt &amp; h\u00f8yde<\/h4><p>Du oppgir vekten og h\u00f8yden din. Det er alt.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">04<\/div><h4>Lean beregner<\/h4><p>BMR p\u00e5 reell fettprosent, NEAT via HealthKit \/ Google Fit (reelle skritt), EAT per MET, TEF per makroer, pluss den metabolske tilpasningen som modulerer BMR. Automatisk.<\/p><\/div>\n    <div class=\"step\"><div class=\"sn\">05<\/div><h4>Logg et m\u00e5ltid<\/h4><p>Foto, strekkode eller database. Du kjenner allerede handlingen.<\/p><\/div>\n  <\/div>\n\n  <p style=\"margin-top:24px\"><strong>Viktig merknad.<\/strong> Lean importerer ikke Foodvisor-historikken din automatisk, heller ikke favorittmatvarene dine. Hvis oppf\u00f8lgingen din med en Foodvisor-ern\u00e6ringsfysiolog betyr noe for deg, hindrer ingenting deg i \u00e5 beholde begge i overgangsperioden: Foodvisor for den menneskelige oppf\u00f8lgingen, Lean for TDEE og den daglige loggingen. Synkroniseringen HealthKit \/ Google Health Connect tar derimot over umiddelbart for skrittene dine og aktivitetshistorikken din.<\/p>\n\n  <div class=\"cta-band rev\" style=\"display:flex;align-items:center;justify-content:space-between;gap:20px;flex-wrap:wrap;padding:26px 28px;margin:40px 0;background:#FAF5EE;border:1px solid #E8E2D6;border-radius:16px\">\n    <div class=\"l\" style=\"flex:1;min-width:240px;font-size:18px;line-height:1.4;font-weight:500;color:#0E0E10\">Last ned Lean og start AI BodyScan n\u00e5. Gratis registrering.<\/div>\n    <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"deblock-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">10 &middot; Det Lean l\u00e5ser opp<\/span><\/div>\n  <h2 id=\"deblock-h\">Det Lean gj\u00f8r, og som Foodvisor ikke gj\u00f8r (p\u00e5 forbruket)<\/h2>\n  <p>Seks funksjoner sentrert p\u00e5 forbruket, som ikke finnes hos Foodvisor. Alle f\u00f8lger av samme prinsipp&nbsp;: beregne hver TDEE-komponent presist, ikke tiln\u00e6rme den.<\/p>\n\n  <div class=\"feat-stack\">\n    <div class=\"feat-it\"><div class=\"fn\">01<\/div><div><div class=\"ft\">Ubegrenset AI BodyScan<\/div><p class=\"fd\">Din reelle fettprosent, m\u00e5lt fra ett enkelt foto, gjentatt hver uke. Det er dataen som endrer hele BMR-beregningen. Ingen annen forbrukerapp tilbyr det.<\/p><\/div><div class=\"fc\">Fettprosent<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">02<\/div><div><div class=\"ft\">Automatisk metabolsk tilpasning<\/div><p class=\"fd\">TDEE-en din justeres uke for uke etter vitenskapelig etablerte tall. Du unng\u00e5r plat\u00e5ene ingen klarer \u00e5 forklare.<\/p><\/div><div class=\"fc\">Tilpasning<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">03<\/div><div><div class=\"ft\">Oppdelt TDEE live<\/div><p class=\"fd\">BMR + NEAT + EAT + TEF vist hver for seg, oppdatert i l\u00f8pet av dagen. Ikke lenger et tall frosset klokka 8 om morgenen. Du ser kaloribalansen din direkte.<\/p><\/div><div class=\"fc\">Live<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">04<\/div><div><div class=\"ft\">NEAT p\u00e5 reelle skritt, uten koeffisient<\/div><p class=\"fd\">Skrittene dine, m\u00e5lt av telefonen din, mater direkte TDEE-beregningen hver dag. Ingen boks stillesittende eller aktiv \u00e5 krysse av, aldri.<\/p><\/div><div class=\"fc\">NEAT<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">05<\/div><div><div class=\"ft\">TEF beregnet p\u00e5 makroene dine<\/div><p class=\"fd\">Ford\u00f8yelsen er ikke en fast sats p\u00e5 10&nbsp;%. Proteiner 20 til 30&nbsp;%, karbohydrater 5 til 10&nbsp;%, fett 1 til 3&nbsp;%. Lean gj\u00f8r beregningen ved hvert m\u00e5ltid og integrerer den i TDEE.<\/p><\/div><div class=\"fc\">TEF<\/div><\/div>\n    <div class=\"feat-it\"><div class=\"fn\">06<\/div><div><div class=\"ft\">Komplett historikk og trender<\/div><p class=\"fd\">F\u00f8lg trendene dine for vekt, fettprosent og fettfri masse over m\u00e5neder. Forst\u00e5 syklusene dine. Se fasene der du gj\u00f8r fremgang og de der du stagnerer.<\/p><\/div><div class=\"fc\">Historikk<\/div><\/div>\n  <\/div>\n\n  <p style=\"margin-top:26px\">Du installerer appen gratis, tester uten forpliktelse, og bestemmer deretter om verkt\u00f8yet passer m\u00e5let ditt.<\/p>\n<\/section>\n\n<section aria-labelledby=\"faq-h\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">11 &middot; FAQ<\/span><\/div>\n  <h2 id=\"faq-h\">Ofte stilte sp\u00f8rsm\u00e5l<\/h2>\n  <div class=\"faq\">\n    <details><summary>Foodvisor oppfant fotoskanning av m\u00e5ltider, hvorfor sammenligne den med Lean&nbsp;?<\/summary><div class=\"ans\">Fordi l\u00f8ftet til en tracker ikke stopper ved tallerkenen. Foodvisor er den historiske referansen for fotogjenkjenning i Frankrike, men kalorim\u00e5let bygger p\u00e5 en populasjonsformel (Mifflin-St Jeor 1990, uten m\u00e5lt fettprosent) og en statisk aktivitetsmultiplikator valgt ved registreringen. Det er to halvdeler av samme problem&nbsp;: Foodvisor utmerker seg p\u00e5 det som kommer inn, Lean p\u00e5 det som forbrukes.<\/div><\/details>\n    <details><summary>Hvorfor beregner ikke Foodvisor BMR p\u00e5 reell fettprosent&nbsp;?<\/summary><div class=\"ans\">Fordi ingen m\u00e5ling av fettprosent finnes i appen, og populasjonsformlene bare bruker vekt, h\u00f8yde, alder og kj\u00f8nn. Lean integrerer AI BodyScan for \u00e5 m\u00e5le fettprosenten din fra ett enkelt foto, gjentatt hver uke, som gir en BMR basert p\u00e5 den reelle fettfrie massen via en patentert propriet\u00e6r modell.<\/div><\/details>\n    <details><summary>Er Leans fotoskanning like god som Foodvisors&nbsp;?<\/summary><div class=\"ans\">Foodvisor beholder forspranget og \u00e5r med trening p\u00e5 tallerkengjenkjenning, spesielt anslag av porsjoner. Leans AI-fotoskanning identifiserer matvarer, kalorier og makroer med sammenlignbar presisjon for daglig bruk, og den er ubegrenset. P\u00e5 dette kriteriet gj\u00f8r begge jobben. Den reelle forskjellen mellom de to appene avgj\u00f8res p\u00e5 beregningen av forbruket.<\/div><\/details>\n    <details><summary>Foodvisor teller skrittene mine, holder det for NEAT&nbsp;?<\/summary><div class=\"ans\">\u00c5 telle skrittene og integrere dem i beregningen er to forskjellige ting. Hos Foodvisor hviler kalorim\u00e5let fortsatt p\u00e5 den statiske aktivitetsmultiplikatoren valgt ved registreringen. Lean beregner NEAT direkte fra de reelle skrittene m\u00e5lt hver dag, uten koeffisient \u00e5 velge, og skiller den ordentlig fra treningsforbruket (EAT).<\/div><\/details>\n    <details><summary>Er Lean gratis eller betalt&nbsp;?<\/summary><div class=\"ans\">Lean er Premium, med 7 dagers gratis pr\u00f8veperiode p\u00e5 \u00e5rsabonnementet. Du laster ned, tester AI BodyScan, AI-fotoskanning av en rett, TDEE-rekomposisjon, uten forpliktelse. Passer verkt\u00f8yet m\u00e5let ditt, fortsetter du. Hvis ikke, deaktiverer du fornyelsen f\u00f8r pr\u00f8veperioden er over.<\/div><\/details>\n    <details><summary>Kan man bruke Lean og Foodvisor parallelt&nbsp;?<\/summary><div class=\"ans\">Ja, spesielt i overgangen. Noen beholder Foodvisor for coachingen med en ern\u00e6ringsfysiolog og bruker Lean daglig for TDEE, rekomposisjon og logging. Innsatsen med dobbel inntasting er reell&nbsp;: p\u00e5 sikt velger de fleste appen som styrer kalorim\u00e5let deres, og det er nettopp feltet der Lean er bygget for \u00e5 v\u00e6re mest presis.<\/div><\/details>\n  <\/div>\n<\/section>\n\n<section aria-labelledby=\"conclu\" class=\"rev\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">12 &middot; Konklusjon<\/span><\/div>\n  <h2 id=\"conclu\">Tallerkenen er l\u00f8st. Forbruket er det ikke.<\/h2>\n  <p>Det er ikke Foodvisor mot Lean i markedsf\u00f8ring. Det er inntaket mot forbruket, to halvdeler av samme ligning.<\/p>\n  <p>Foodvisor har l\u00f8st venstre halvdel&nbsp;: vite hva du spiser, uten vekt, takket v\u00e6re den mest innarbeidede fotoskanningen i det franske markedet. Men for h\u00f8yre halvdel, forbruket ditt, st\u00f8tter Foodvisor seg p\u00e5 en populasjonsformel fra 1990 uten m\u00e5lt fettprosent, en fastl\u00e5st aktivitetsmultiplikator du krysser av \u00e9n eneste gang ved registreringen, og ingen metabolsk tilpasning. Kombinasjonen av de tre gj\u00f8r enhver presis kalorioppf\u00f8lging umulig utover noen uker med deff. Det er matematikk.<\/p>\n  <p>Lean ble bygget for den halvdelen&nbsp;: BMR basert p\u00e5 <a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/depense-energetique-totale-v2\/\">reelle fettprosent<\/a> (m\u00e5lt med AI BodyScan) via en patentert propriet\u00e6r modell, <a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/neat-depense-non-sportive\/\">NEAT per reelle skritt<\/a>, EAT per idrett og MET, <a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/effet-thermique-des-aliments\/\">TEF per makroer<\/a>, pluss den metabolske tilpasningen som modulerer BMR uke for uke. Hver komponent beregnet presist, uten magisk koeffisient. Og fotorefleksen du fikk hos Foodvisor, beholder du&nbsp;: AI-fotoskanningen er integrert, ubegrenset.<\/p>\n  <p>Hvis du har pr\u00f8vd Foodvisor seri\u00f8st og ikke fikk resultatene du h\u00e5pet p\u00e5 i deffen din, er problemet ikke deg, og heller ikke fotoet. Problemet er den fastl\u00e5ste TDEE-en under panseret. Bytt motor, behold refleksen.<\/p>\n<\/section>\n\n<div class=\"get-band rev\" style=\"background:#F1E9DC;border-radius:24px;padding:48px 36px;margin:60px 0 40px;text-align:center\">\n  <div class=\"kicker\">Nedlasting<\/div>\n  <h3>Lean kan lastes ned gratis<\/h3>\n  <p>iOS og Android. AI BodyScan fungerer med ett enkelt foto. Ingen hudfoldsm\u00e5ler, ingen impedansvekt, ingen DEXA.<\/p>\n  <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\" aria-label=\"Last ned Lean fra App Store\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n    <\/a>\n    <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\" aria-label=\"Last ned Lean fra Google Play\">\n      <img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/>\n    <\/a>\n  <\/div>\n<\/div>\n\n<section aria-labelledby=\"links\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">G\u00e5 videre<\/span><\/div>\n  <h3 id=\"links\" style=\"margin-top:0\">Interne lenker<\/h3>\n  <ul>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/tdee-calculator\/\">Gratis TDEE-kalkulator p\u00e5 nett<\/a> &middot; nettversjon, uten registrering, samme logikk som appen (BMR + NEAT + EAT + TEF).<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/depense-energetique-totale-v2\/\">Forst\u00e5 TDEE i detalj (BMR, NEAT, EAT, TEF, tilpasning)<\/a> &middot; dyptg\u00e5ende vitenskapelig artikkel.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/comment-compter-ses-calories\/\">Slik teller du kaloriene dine riktig<\/a> &middot; praktisk guide for nybegynnere.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/neat-depense-non-sportive\/\">NEAT&nbsp;: forbruk per skritt og aktivitet utenom trening<\/a>.<\/li>\n    <li><a class=\"inline\" href=\"https:\/\/lean-app.com\/no\/effet-thermique-des-aliments\/\">TEF&nbsp;: ford\u00f8yelsen forbrenner kalorier<\/a>.<\/li>\n  <\/ul>\n<\/section>\n\n<section aria-labelledby=\"src\" class=\"sources\">\n  <div class=\"section-label\"><span class=\"bar\"><\/span><span class=\"num\">Kilder<\/span><\/div>\n  <h3 id=\"src\" style=\"margin-top:0;color:var(--ink)\">Bibliografi<\/h3>\n  <ol>\n    <li>Harris J.A., Benedict F.G. (1919). A Biometric Study of Basal Metabolism in Man. Carnegie Institution of Washington.<\/li>\n    <li>Mifflin M.D., St Jeor S.T. et al. (1990). A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/2305711\/\" target=\"_blank\" rel=\"noopener\">PubMed 2305711<\/a>.<\/li>\n    <li>Frankenfield D.C. (2013). Bias and accuracy of resting metabolic rate equations in non-obese and obese adults. Clinical Nutrition. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/23631843\/\" target=\"_blank\" rel=\"noopener\">PubMed 23631843<\/a>.<\/li>\n    <li>Westerterp K.R. (2004). Diet induced thermogenesis. Nutrition &amp; Metabolism. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/15507147\/\" target=\"_blank\" rel=\"noopener\">PubMed 15507147<\/a>.<\/li>\n    <li>M\u00fcller M.J. et al. (2015). Metabolic adaptation to caloric restriction and subsequent refeeding: the Minnesota Starvation Experiment revisited. American Journal of Clinical Nutrition. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/26399868\/\" target=\"_blank\" rel=\"noopener\">PubMed 26399868<\/a>.<\/li>\n    <li>Doucet E. et al. (2001). Evidence for the existence of adaptive thermogenesis during weight loss. British Journal of Nutrition. <a class=\"inline\" href=\"https:\/\/pubmed.ncbi.nlm.nih.gov\/11430776\/\" target=\"_blank\" rel=\"noopener\">PubMed 11430776<\/a>.<\/li>\n  <\/ol>\n<\/section>\n\n<\/main>\n\n<footer>\n  <div class=\"wrap\">\n    <div class=\"row\">\n      <div>\n        <div class=\"kicker\">Lean &middot; lean-app.com<\/div>\n        <p>Artikkel publisert 15. august 2026. Oppdateres jevnlig med tilbakemeldinger fra brukere og nye relevante studier. Lean er tilgjengelig p\u00e5 iOS og Android.<\/p>\n      <\/div>\n      <div class=\"stores\" style=\"display:flex;gap:10px;align-items:center;flex-wrap:wrap\">\n      <a href=\"https:\/\/apps.apple.com\/fr\/app\/lean-calorie-ai-podometre\/id6738668646?utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-appstore-official.webp\" alt=\"App Store\" width=\"413\" height=\"122\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n        <a href=\"https:\/\/play.google.com\/store\/apps\/details?id=com.lean.testsqflite&#038;utm_source=seo&#038;utm_medium=blog&#038;utm_campaign=vs-foodvisor\" target=\"_blank\" rel=\"noopener\"><img src=\"https:\/\/lean-app.com\/wp-content\/uploads\/2026\/05\/lvm-googleplay-official.webp\" alt=\"Google Play\" width=\"315\" height=\"95\" loading=\"lazy\" decoding=\"async\" style=\"height:48px;width:auto;border-radius:9px;display:block\" \/><\/a>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/footer>\n\n<script data-wpmeteor-nooptimize=\"true\">\n(function(){\n  var bar = document.getElementById('progBar');\n  function up(){\n    var h = document.documentElement;\n    var sc = (h.scrollTop)\/Math.max(1,(h.scrollHeight - h.clientHeight));\n    bar.style.transform = 'scaleX(' + Math.max(0,Math.min(1,sc)) + ')';\n  }\n  document.addEventListener('scroll', up, {passive:true});\n  up();\n})();\n\n(function(){\n  if (!('IntersectionObserver' in window)) {\n    document.querySelectorAll('.rev').forEach(function(n){n.classList.add('on')});\n    return;\n  }\n  var obs = new IntersectionObserver(function(entries){\n    entries.forEach(function(e){\n      if (e.isIntersecting) { e.target.classList.add('on'); obs.unobserve(e.target); }\n    });\n  }, {threshold:0.12});\n  document.querySelectorAll('.rev').forEach(function(n){ obs.observe(n); });\n})();\n\n(function(){\n  var phoneImg = document.getElementById('phoneImg');\n  var phoneBack = document.getElementById('phoneBack');\n  var zones = document.getElementById('phoneZones');\n  var topTabs = document.querySelectorAll('.phone-tabs button');\n  var navTaps = document.querySelectorAll('.phone-navbar button');\n\n  var tabMap = {\n    bilan:    {drill:false},\n    kcal:     {drill:false},\n    depense:  {drill:true},\n    strategie:{drill:false}\n  };\n  var subMap = {BMR:1, NEAT:1, EAT:1, TEF:1};\n  var currentTab = 'depense';\n\n  function setActive(tab){\n    topTabs.forEach(function(b){ b.classList.toggle('on', b.dataset.tab===tab); });\n  }\n  function showTab(tab){\n    var t = tabMap[tab]; if(!t) return;\n    currentTab = tab;\n    phoneImg.style.opacity = 0;\n    setTimeout(function(){\n      phoneImg.className = 'phone-bg tab-' + tab;\n      phoneImg.style.opacity = 1;\n      zones.style.display = t.drill ? 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setTimeout(tryApply, 300);\n  }\n  tryApply();\n})();\n<\/script>\n\n\n\n<!-- lean-mesh-v16 -->\n<aside class=\"lean-mesh\" style=\"margin:48px auto;max-width:760px;padding:24px 28px;background:#ffffff;border-left:4px solid #FF2D6E;border-radius:0 12px 12px 0;box-shadow:0 6px 24px rgba(20,20,40,0.06);font-family:-apple-system,'SF Pro Text','Segoe UI',Roboto,Arial,sans-serif;color:#1a1a2e;\"><p style=\"margin:0 0 14px;font-size:13px;font-weight:700;letter-spacing:0.06em;text-transform:uppercase;color:#FF2D6E;\">Les ogs\u00e5<\/p><ul style=\"list-style:none;padding:0;margin:0;display:grid;grid-template-columns:1fr;gap:10px;\"><li><a href=\"https:\/\/lean-app.com\/no\/metabolisme-de-base\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Basalmetabolisme (BMR): alt du trenger \u00e5 vite for \u00e5 beregne det <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Definisjon, TDEE-ligning, 4 historiske formler, hvorfor fettprosenten endrer alt.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/depense-energetique-totale-v2\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Totalt energiforbruk (TDEE): den kanoniske formelen BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Forst\u00e5 de 4 byggesteinene + den metabolske tilpasningen, vitenskapelige kilder 2025.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/eat\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">EAT: det reelle treningsforbruket ditt, \u00f8kt for \u00f8kt <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">De riktige MET-verdiene, dobbelttellingsfellen, det Garmin og MyFitnessPal bommer p\u00e5.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/meilleures-applications-calories-2026\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Beste apper for \u00e5 telle kalorier i 2026: 8 apper testet <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Lean, MFP, Cronometer, Yazio, Lifesum, FatSecret, Noom, Foodvisor.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/alternative-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Hvilket alternativ til MyFitnessPal i 2026? 5 apper testet <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">\u00c6rlig sammenligning, TDEE-presisjon, ergonomi.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/comparatifs\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Alle Lean-sammenligninger mot de store kaloriappene <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hub: MyFitnessPal, Yazio, Cronometer, Lifesum, FatSecret, Noom.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/lean-vs-myfitnesspal\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">Lean mot MyFitnessPal: TDEE-formelen som endrer alt <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Hvorfor MFP tar feil om det reelle kaloriforbruket ditt.<\/span><\/a><\/li><li><a href=\"https:\/\/lean-app.com\/no\/calculateur-tdee\/\" style=\"display:block;padding:14px 16px;background:#FAF7F2;border-radius:8px;color:#1a1a2e;text-decoration:none;font-weight:600;line-height:1.4;\">TDEE-kalkulator: den kanoniske formelen BMR + NEAT + EAT + TEF <span style=\"color:#4D4D52;font-weight:400;display:block;font-size:14px;margin-top:4px;\">Fettprosentbevisst kalkulator med oppdeling av de 4 metabolske byggesteinene.<\/span><\/a><\/li><\/ul><\/aside>","protected":false},"excerpt":{"rendered":"<p>Lean Calculateur TDEE Accueil &nbsp;\/&nbsp; Lean vs Foodvisor Comparatif &middot; Nutrition &amp; TDEE Lean vs Foodvisor. Le pionnier du scan photo face au seul qui recompose ton TDEE en continu. Foodvisor voit ton assiette. Lean voit ta d\u00e9pense r\u00e9elle. Deux IA, deux moiti\u00e9s du probl\u00e8me. L&rsquo;\u00e9quipe Lean &middot; Lecture 12&nbsp;min &middot; Mis \u00e0 jour 15 [&hellip;]<\/p>","protected":false},"author":1,"featured_media":1763,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-lvm-blank","format":"standard","meta":{"footnotes":""},"categories":[13],"tags":[],"class_list":["post-1760","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-comparateurs"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Lean vs Foodvisor: AI-fotoskanning mot det reelle forbruket ditt<\/title>\n<meta name=\"description\" content=\"Foodvisor oppfant fotoskanning av m\u00e5ltider. Men forbruket ditt forblir der en formel fra 1990 uten fettprosent. 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