Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data

JMIR mhealth and uhealth, Год журнала: 2018, Номер 6(8), С. e10527 - e10527

Опубликована: Июль 23, 2018

Background: Although designed as a consumer product to help motivate individuals be physically active, Fitbit activity trackers are becoming increasingly popular measurement tools in physical and health promotion research also commonly used inform care decisions. Objective: The objective of this review was systematically evaluate report accuracy for controlled free-living settings. Methods: We conducted electronic searches using PubMed, EMBASE, CINAHL, SPORTDiscus databases with supplementary Google Scholar search. considered original published English comparing versus reference- or research-standard criterion healthy adults those living any condition disability. assessed risk bias modification the Consensus-Based Standards Selection Health Status Measurement Instruments. explored steps, energy expenditure, sleep, time activity, distance group percentage differences common rubric error comparisons. descriptive analyses frequency comparisons within ±3% ±10% settings potential over- underestimation. secondarily how variations body placement, ambulation speed, type influenced accuracy. Results: included 67 studies. Consistent evidence indicated that devices were likely meet acceptable step count approximately half time, tendency underestimate steps testing overestimate Findings suggested greater provide accurate measures during normal self-paced walking torso jogging wrist slow very ankle placement no mobility limitations. unlikely expenditure condition. Evidence from few studies that, compared research-grade accelerometers, may similar bed sleeping, while markedly overestimating spent higher-intensity activities underestimating faster-paced ambulation. However, further warranted. Our point estimations mean median gave equal weighting all comparisons, possibly misrepresenting true estimate some conditions we examined. Conclusions: Other than limitations mobility, discretion should when considering use an outcome tool decisions, there seemingly limited number situations where device is measurement.

Язык: Английский

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Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables

Journal of Medical Internet Research, Год журнала: 2018, Номер 20(3), С. e110 - e110

Опубликована: Март 22, 2018

Background: New fitness trackers and smartwatches are released to the consumer market every year. These devices equipped with different sensors, algorithms, accompanying mobile apps. With recent advances in sensor technology, privately collected physical activity data can be used as an addition existing methods for health collection research. Furthermore, from these have possible applications patient diagnostics treatment. increasing number of diverse brands, there is a need overview device support, well applicability research projects.

Язык: Английский

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A Critical Review of Consumer Wearables, Mobile Applications, and Equipment for Providing Biofeedback, Monitoring Stress, and Sleep in Physically Active Populations

Frontiers in Physiology, Год журнала: 2018, Номер 9

Опубликована: Июнь 28, 2018

The commercial market for technologies to monitor and improve personal health sports performance is ever expanding. A wide range of smart watches, bands, garments, patches with embedded sensors, small portable devices mobile applications now exist record provide users feedback on many different physical variables. These variables include cardiorespiratory function, movement patterns, sweat analysis, tissue oxygenation, sleep, emotional state, changes in cognitive function following concussion. In this review, we have summarized the features evaluated characteristics a cross-section according what technology claimed do, whether it has been validated reliable, if suitable general consumer use. Consumers who are choosing new should consider (1) produces desirable (or non-desirable) outcomes, (2) developed based real-world need, (3) tested proven effective applied studies settings. Among included more than half not through independent research. Only 5% formally validated. Around 10% used value such use debatable, however, because they may require extra time set up interpret data produce. Looking future, rapidly expanding much offer consumers. To create competitive advantage, companies producing consult consumers identify invest research prove effectiveness their products. get best value, carefully select products, only needs, but also strength supporting evidence

Язык: Английский

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Wearable Sleep Technology in Clinical and Research Settings

Medicine & Science in Sports & Exercise, Год журнала: 2019, Номер 51(7), С. 1538 - 1557

Опубликована: Фев. 19, 2019

: The accurate assessment of sleep is critical to better understand and evaluate its role in health disease. boom wearable technology part the digital revolution producing many novel, highly sophisticated relatively inexpensive consumer devices collecting data from multiple sensors claiming extract information about users' behaviors, including sleep. These are now able capture different biosignals for determining, example, HR variability, skin conductance, temperature, addition activity. They perform 24/7, generating overwhelmingly large sets (big data), with potential offering an unprecedented window on health. Unfortunately, little guidance exists within outside scientific community their use, leading confusion controversy validity application. current state-of-the-art review aims highlight validation utility sleep-trackers clinical practice research. Guidelines a standardized device performance deemed necessary, several factors (proprietary algorithms, malfunction, firmware updates) need be considered before using these research protocols. Ultimately, holds promise advancing understanding health; however, careful path forward needs navigated, benefits pitfalls this as applied medicine.

Язык: Английский

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A validation study of Fitbit Charge 2™ compared with polysomnography in adults

Chronobiology International, Год журнала: 2017, Номер 35(4), С. 465 - 476

Опубликована: Дек. 13, 2017

We evaluated the performance of a consumer multi-sensory wristband (Fitbit Charge 2™), against polysomnography (PSG) in measuring sleep/wake state and sleep stage composition healthy adults.In-lab PSG Fitbit 2™ data were obtained from single overnight recording at SRI Human Sleep Research Laboratory 44 adults (19—61 years; 26 women; 25 Caucasian). Participants screened to be free mental medical conditions. Presence disorders was with clinical PSG. findings indicated periodic limb movement (PLMS, > 15/h) nine participants, who analyzed separately main group (n = 35). compared using paired t-tests, Bland–Altman plots, epoch-by-epoch (EBE) analysis.In group, showed 0.96 sensitivity (accuracy detect sleep), 0.61 specificity wake), 0.81 accuracy detecting N1+N2 (“light sleep”), 0.49 N3 (“deep 0.74 rapid-eye-movement (REM) sleep. significantly (p < 0.05) overestimated TST by 9 min, 34 underestimated SOL 4 min 24 min. outcomes did not differ for WASO time spent REM No more than two participants fell outside agreement limits all measures. correctly identified 82% PSG-defined non-REM–REM cycles across night. Similar found PLMS group.Fitbit shows promise sleep-wake states relative gold standard PSG, particularly estimation sleep, but limitations detection. reliability need further investigated different settings (at-home, multiple nights) populations which is known vary (adolescents, elderly, patients disorders).

Язык: Английский

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Accuracy of Wristband Fitbit Models in Assessing Sleep: Systematic Review and Meta-Analysis

Journal of Medical Internet Research, Год журнала: 2019, Номер 21(11), С. e16273 - e16273

Опубликована: Окт. 17, 2019

Wearable sleep monitors are of high interest to consumers and researchers because their ability provide estimation patterns in free-living conditions a cost-efficient way.We conducted systematic review publications reporting on the performance wristband Fitbit models assessing parameters stages.In adherence with Preferred Reporting Items for Systematic Reviews Meta-Analyses (PRISMA) statement, we comprehensively searched Cumulative Index Nursing Allied Health Literature (CINAHL), Cochrane, Embase, MEDLINE, PubMed, PsycINFO, Web Science databases using keyword identify relevant meeting predefined inclusion exclusion criteria.The search yielded 3085 candidate articles. After eliminating duplicates compliance criteria, 22 articles qualified review, 8 providing quantitative data meta-analysis. In reference polysomnography (PSG), nonsleep-staging tended overestimate total time (TST; range from approximately 7 67 mins; effect size=-0.51, P<.001; heterogenicity: I2=8.8%, P=.36) efficiency (SE; 2% 15%; size=-0.74, I2=24.0%, P=.25), underestimate wake after onset (WASO; 6 44 size=0.60, I2=0%, P=.92) there was no significant difference latency (SOL; P=.37; P=.92). PSG, correctly identified epochs accuracy values between 0.81 0.91, sensitivity 0.87 0.99, specificity 0.10 0.52. Recent-generation that collectively utilize heart rate variability body movement assess stages performed better than early-generation ones only movement. Sleep-staging models, comparison showed measured WASO (P=.25; P=.92), TST (P=.29; P=.98), SE (P=.19) but they underestimated SOL (P=.03; P=.66). higher (0.95-0.96) (0.58-0.69) detecting those reported literature regular wrist actigraphy.Sleep-staging promising performance, especially differentiating sleep. However, although these convenient economical means obtain gross estimates spent stages, limited not substitute PSG.

Язык: Английский

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Performance of seven consumer sleep-tracking devices compared with polysomnography

SLEEP, Год журнала: 2020, Номер 44(5)

Опубликована: Дек. 30, 2020

Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers clinicians for their possible use as alternatives to standard actigraphy. We, therefore, tested the performance of many latest consumer devices, alongside actigraphy, versus gold-standard sleep assessment technique, polysomnography (PSG).In total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean SD) were on three consecutive nights (including a disrupted condition) in laboratory with PSG, along actigraphy (Philips Respironics Actiwatch 2) subset devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Vivosmart 3) nonwearable (EarlySense Live, ResMed S+, SleepScore Max) tested. Sleep/wake summary epoch-by-epoch agreement measures compared PSG.Most EarlySense performed well or better than sleep/wake measures, while worse. Overall, sensitivity was high (all ≥0.93), specificity low-to-medium (0.18-0.54), stage comparisons mixed, tended perform worse poorer/disrupted sleep.Consumer exhibited detecting sleep, most equivalent (or than) wake. Device assessments inconsistent. Findings indicate that newer demonstrate promising tracking Devices should be different populations settings further examine wider validity utility.

Язык: Английский

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Sensors and Functionalities of Non-Invasive Wrist-Wearable Devices: A Review

Sensors, Год журнала: 2018, Номер 18(6), С. 1714 - 1714

Опубликована: Май 25, 2018

Wearable devices have recently received considerable interest due to their great promise for a plethora of applications. Increased research efforts are oriented towards non-invasive monitoring human health as well activity parameters. A wide range wearable sensors being developed real-time monitoring. This paper provides comprehensive review used in wrist-wearable devices, methods the visualization parameters measured intelligent analysis data obtained from devices. In line with this, main features commercial presented. As result this review, taxonomy sensors, functionalities, and was assembled.

Язык: Английский

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Wearable sensors for monitoring the internal and external workload of the athlete

npj Digital Medicine, Год журнала: 2019, Номер 2(1)

Опубликована: Июль 29, 2019

Abstract The convergence of semiconductor technology, physiology, and predictive health analytics from wearable devices has advanced its clinical translational utility for sports. detection subsequent application metrics pertinent to indicative the physical performance, physiological status, biochemical composition, mental alertness athlete been shown reduce risk injuries improve performance enabled development athlete-centered protocols treatment plans by team physicians trainers. Our discussions in this review include commercially available devices, as well those described scientific literature provide an understanding sensors sports medicine. primary objective paper is a comprehensive applications technology assessing biomechanical parameters athlete. A secondary identify collaborative research opportunities among academic groups, medicine clinics, programs further assist return-to-play athletes across various sporting domains. companion discusses use wearables monitor profile acuity

Язык: Английский

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How consumer physical activity monitors could transform human physiology research

AJP Regulatory Integrative and Comparative Physiology, Год журнала: 2017, Номер 312(3), С. R358 - R367

Опубликована: Янв. 5, 2017

A sedentary lifestyle and lack of physical activity are well-established risk factors for chronic disease adverse health outcomes. Thus, there is enormous interest in measuring biomedical research. Many consumer monitors, including Basis Health Tracker, BodyMedia Fit, DirectLife, Fitbit Flex, One, Zip, Garmin Vivofit, Jawbone UP, MisFit Shine, Nike FuelBand, Polar Loop, Withings Pulse O 2 , others have accuracies similar to that research-grade monitors steps. This review focuses on the unprecedented opportunities offer human physiology pathophysiology research because their ability measure continuously under real-life conditions they already widely used by consumers. We examine current potential uses as a or monitoring device, an intervention strategies change behavior predict The accuracy, reliability, reproducibility, validity reviewed, limitations challenges associated with using these devices Other topics covered include how smartphone apps platforms, such Apple ResearchKit, can be conjunction Lastly, future related technology considered: pattern recognition, integration sleep other biosensors combination new forms information processing.

Язык: Английский

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