Evidence map›Paper›PMID 31376273›Full record

ArticleJMIR mHealth and uHealth2019

Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study.

Haruka Murakami, Ryoko Kawakami, Satoshi Nakae, Yosuke Yamada, Yoshio Nakata, Kazunori Ohkawara, Hiroyuki Sasai, Kazuko Ishikawa-Takata, Shigeho Tanaka, Motohiko Miyachi

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

50 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  7. A Smart Headband for Multimodal Physiological Monitoring in Human Exercises.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Haruka Murakami *Department of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.ORCID 0000-0001-9160-0033
Ryoko Kawakami *Department of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.ORCID 0000-0001-8211-1553
Satoshi NakaeDepartment of Nutrition and Metabolism, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.ORCID 0000-0001-7840-9090
Yosuke YamadaSection of Healthy Longevity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.ORCID 0000-0002-4284-6317
Yoshio NakataFaculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, Japan.ORCID 0000-0002-0888-4440
Kazunori OhkawaraGraduate School of Informatics and Engineering, University of Electro-Communication, Tokyo, Japan.ORCID 0000-0002-2098-8840
Hiroyuki SasaiGraduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan.ORCID 0000-0001-8120-6163
Kazuko Ishikawa-TakataDepartment of Nutrition and Metabolism, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.ORCID 0000-0003-2995-2956
Shigeho TanakaDepartment of Nutrition and Metabolism, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.ORCID 0000-0002-8933-3041
Motohiko MiyachiDepartment of Physical Activity Research, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.ORCID 0000-0002-1146-0905

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSelf-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established.

objectiveWe examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method.

methodsA total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices.

resultsOn the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=-.13 to .37) and Spearman (ρ=-.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw.

conclusionsMost wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

Indexed as

AccelerometryActigraphyAdultBasal MetabolismEnergy MetabolismExerciseFemaleHumansMaleMiddle AgedValidation Studies as TopicWearable Electronic DevicesWeights and Measuresaccelerometrydoubly labeled waterenergy expenditureindirect calorimetryphysical activity

Identifiers

PMID31376273
PMCPMC6696858

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.