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Table 2 Accuracy problems in studies using physiological measurements by wearables

From: Smartphones in mental health: a critical review of background issues, current status and future concerns

MeasureNumber testedWearablesPatientsFindingStudy
Total energy expenditure12 devicesWithings Pulse
Jawbone
Garmin Vivofit
Suzuken Lifecorder EX
Panasonic Actimaker
Epson Pulsense
Tanita-AM-160
Fitbit Flex
Misfit Shine
Omron Active Style Pro
Omron CaloriScan
19 healthy adults, not obese.“absolute values differed widely among products and varied significantly from the gold standard measures”Murakami et al. (2016)
Step count3 pedometersYamax
Digiwalker
Fitbit
14 young health participants walking at 3 speeds“all the evaluated devices had high error rates at 1 km/h” (slow walking speeds).Beevi et al. (2016)
Step count10 activity trackersPolar Loop
Garmin Vivosmart
Fitbit Charge HR
Apple Watch Sport
Pebble Smartwatch
Samsung Gear S
Misfit Flash
Jawbone Up Move
Flyfit
Moves
31 healthy participants on a treadmill“Test–retest validity depends on walking speed”; “consumer activity trackers perform better at average and vigorous walking speed…”Fokkema et al. (2017)
Sleep2 monitorsWithings Pulse
Jawbone Up
36, including 22 with obstructive sleep apnea (OSA)“confirmed… in patients suffering from OSA, the limited performance of wearable sleep monitors”Gruwez et al. (2019)
Sleep2 monitorsFitbit Change 2
Neuroon
25 studentsUnderestimate light sleep and overestimate deep sleep. “Reasonably satisfactory for general purpose and non-clinical use”Liang and Martell (2018)