Consumer Wearable Activity Trackers Research Articles

Criterion-Related Validity of Consumer-Wearable Activity Trackers for Estimating Steps in Primary Schoolchildren under Controlled Conditions: Fit-Person Study.

The purposes were to examine the criterion-related validity of the steps estimated by consumer-wearable activity trackers (wrist-worn activity trackers: Fitbit Ace 2, Garmin Vivofit Jr, and Xiomi Mi Band 5; smartphone applications: Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health) and their comparability in primary schoolchildren under controlled conditions. An initial sample of 66 primary schoolchildren (final sample = 56; 46.4% females), aged 9-12 years old (mean = 10.4 ± 1.0 years), wore three wrist-worn activity trackers (Fitbit Ace 2, Garmin Vivofit Jr 2, and Xiaomi Mi Band 5) on their non-dominant wrist and had three applications in two smartphones (Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health for Android/iOS installed in Samsung Galaxy S20+/iPhone 11 Pro Max) in simulated front trouser pockets. Primary schoolchildren's steps estimated by the consumer-wearable activity trackers and the video-based counting independently by two researchers (gold standard) were recorded while they performed a 200-meter course in slow, normal and brisk pace walking, and running conditions. Results showed that the criterion-related validity of the step scores estimated by the three Samsung applications and the Garmin Vivofit Jr 2 were good-excellent in the four walking/running conditions (e.g., MAPE = 0.6-2.3%; lower 95% CI of the ICC = 0.81-0.99), as well as being comparable. However, the Apple applications, Fitbit Ace 2, and Xiaomi Mi Band 5 showed poor criterion-related validity and comparability on some walking/running conditions (e.g., lower 95% CI of the ICC < 0.70). Although, as in real life primary schoolchildren also place their smartphones in other parts (e.g., schoolbags, hands or even somewhere away from the body), the criterion-related validity of the Garmin Vivofit Jr 2 potentially would be considerably higher than that of the Samsung applications. The findings of the present study highlight the potential of the Garmin Vivofit Jr 2 for monitoring primary schoolchildren's steps under controlled conditions.

A 12-week consumer wearable activity tracker-based intervention reduces sedentary behaviour and improves cardiometabolic health in free-living sedentary adults: a randomised controlled trial

BackgroundReducing sedentary behaviour significantly improves cardiometabolic health and plays an important role in the prevention and management of cardiometabolic diseases. However, limited effective strategies have been proposed to combat the negative effects of sedentary lifestyles. Although consumer wearable activity trackers (CWATs) can effectively improve physical activity, they were only included as part of a multiple behaviour change technique. In addition, it is not known whether these devices are also effective to reduce sedentary behaviour. Therefore, we aim to investigate the efficacy of a single component CWAT-only intervention and the added value of a multicomponent (CWATs + motivational interviewing) behaviour change intervention to reduce sedentary behaviour and increase physical activity within sedentary adults.MethodsIn a three-armed randomised controlled trial, 59 (male/female: 21/38) sedentary adults were randomly allocated to a control group (n = 20), a CWAT-only group (n = 20) or the CWAT + group (CWAT + motivational interviewing; n = 19) for 12 weeks. Physical activity and sedentary behaviour were assessed using the activPAL3™ accelerometer. In addition, anthropometrics, blood pressure, plasma lipids and insulin sensitivity using an oral glucose tolerance test were assessed at baseline and after the 12-week intervention period.ResultsAs compared with the control group, the CWAT + group significantly reduced time spent in sedentary behaviour (− 81 min/day, confidence interval [95%]: [− 151, − 12] min/day) and significantly increased step count (+ 3117 [827, 5406] steps/day), standing time (+ 62 [14, 110] min/day), light intensity PA (+ 28 [5, 50] min/day) and moderate-to-vigorous PA (+ 22 [4, 40] min/day). Body fat mass (− 1.67 [− 3.21, − 0.14] kg), percentage body fat (− 1.5 [− 2.9, − 0.1] %), triglyceride concentration (− 0.31 [− 0.62, − 0.01] mmol/l), the 2 h insulin concentration (− 181 [− 409, − 46] pmol/l), the quantitative insulin sensitivity check index (− 0.022 [− 0.043, − 0.008]) and total area under the curve of insulin (− 6464 [− 26837, − 2735] mmol/l min) were significantly reduced in the CWAT + group, compared to the control group. No significant differences within the CWAT-only group were found.ConclusionA 12-week multicomponent CWAT-based intervention (CWAT + motivational interviewing) reduces sedentary time, increases physical activity levels and improves various cardiometabolic health variables in sedentary adults, whereas self-monitoring on itself (CWAT-only group) has no beneficial effects on sedentary time.Trial registration The present study was registered (2018) at clinicaltrials.gov as NCT03853018.

A Multi-Level Classification Approach for Sleep Stage Prediction With Processed Data Derived From Consumer Wearable Activity Trackers.

Consumer wearable activity trackers, such as Fitbit are widely used in ubiquitous and longitudinal sleep monitoring in free-living environments. However, these devices are known to be inaccurate for measuring sleep stages. In this study, we develop and validate a novel approach that leverages the processed data readily available from consumer activity trackers (i.e., steps, heart rate, and sleep metrics) to predict sleep stages. The proposed approach adopts a selective correction strategy and consists of two levels of classifiers. The level-I classifier judges whether a Fitbit labeled sleep epoch is misclassified, and the level-II classifier re-classifies misclassified epochs into one of the four sleep stages (i.e., light sleep, deep sleep, REM sleep, and wakefulness). Best epoch-wise performance was achieved when support vector machine and gradient boosting decision tree (XGBoost) with up sampling were used, respectively at the level-I and level-II classification. The model achieved an overall per-epoch accuracy of 0.731 ± 0.119, Cohen's Kappa of 0.433 ± 0.212, and multi-class Matthew's correlation coefficient (MMCC) of 0.451 ± 0.214. Regarding the total duration of individual sleep stage, the mean normalized absolute bias (MAB) of this model was 0.469, which is a 23.9% reduction against the proprietary Fitbit algorithm. The model that combines support vector machine and XGBoost with down sampling achieved sub-optimal per-epoch accuracy of 0.704 ± 0.097, Cohen's Kappa of 0.427 ± 0.178, and MMCC of 0.439 ± 0.180. The sub-optimal model obtained a MAB of 0.179, a significantly reduction of 71.0% compared to the proprietary Fitbit algorithm. We highlight the challenges in machine learning based sleep stage prediction with consumer wearables, and suggest directions for future research.

Can We Use Consumer-Wearable Activity Tracker Fitbit in Parkinson Disease?

Consumer-wearable activity trackers have been used for monitoring health-related metrics to estimate steps, distance, physical activity, energy expenditure, and sleep. The purpose of this mini review was to summarize the evidence for validity of the most popular wrist-worn activity tracker (Fitbit) to estimate those health-related metrics in Parkinson disease. We researched full-length English studies in PubMed, Science Direct, Google Scholar, and Scopus, through September, 2021. In total, 27 studies and a textbook description were included in the review. To adapt consumer-wearable activity trackers for evaluating health-related metrics in Parkinson’s disease (PD) patients, there may be some points to be elucidated and conquered. First, measurement accuracy and precision are required. Second, inter-device reliability for measuring steps, distance, and energy expenditure must be considered. Third, wearability: there are some types of device such as wrist-worn, ankle-worn, belt-fixed, and so on. Overall, Fitbit has advantage for these points. This mini review indicates that Fitbit has enough measurement accuracy and precision to estimate health-related metrics of PD patients including amount of step, physical activity energy expenditure, and quality of sleep.

Use of consumer wearable devices to promote physical activity among breast, prostate, and colorectal cancer survivors: a review of health intervention studies.

A growing amount of research has successfully incorporated Fitbit devices and other wearable activity trackers into technology-oriented lifestyle interventions to increase physical activity among cancer survivors. The present review of this literature is based upon bibliographic searches in PubMed and CINAHL and relevant search terms. Articles published in English from January 1, 2009, through October 16, 2019, were considered. A total of 1726 article citations were identified in PubMed and non-duplicates in CINAHL. After screening the abstracts or full texts of these articles and reviewing the references of previous review articles, we found 13 studies that met the eligibility criteria. Of these, 8 were randomized controlled trials, one was a pre-post-test trial, and 4 were qualitative studies (focus groups, in-depth interviews). The studies focused on breast cancer (n = 8), prostate cancer (n = 2), and colorectal cancer (n = 1), and the remainder focused on more than one cancer site. Additional research is needed to examine the efficacy of consumer wearable devices in promoting physical activity and weight management among cancer survivors. Cancer survivors show an increase in physical activity when using consumer wearable activity trackers. Increased physical activity plays an important role in alleviating many adverse effects of breast cancer therapy as well as improving morbidity and mortality. Additional research such as clinical trials focused on the development of successful interventions utilizing these devices is warranted.

Validation of consumer wearable activity tracker as step measurement in free-living conditions

Different generations of consumer wearable activity trackers are prevalent with the increasing demands in health and physical activity monitor. This pilot study aims to validate one of the consumer wearable activity trackers, the Mi band 2 as a step measurement in free-living conditions.&#x0D; Thirty-one healthy volunteers, aged 23 to 45 with 16 female (52%), wore both Mi band 2 and ActiGraph GT9X Link on their dominant hand’s wrist for seven consecutive days. The validity of the electronic activity devices was assessed objectively by average steps/day using i) Paired sample t-tests; ii) Pearson correlation. In addition, Bland-Altman plots were constructed to visually inspect the data and to assess agreement with the ActiGraph accelerometer.&#x0D; There was a high correlation in steps/day between the reference device, Actigraph accelerometer and Mi Band 2 (r = 0.97, p &lt; 0.001). No significant mean different in steps/ day and no apparent systematic biases in the Bland-Altman plots between step count measurements obtained using the Mi Band 2. Xiaomi Mi Band 2 provided valid step count measurement in the free-living conditions.

Systematic review of the validity and reliability of consumer-wearable activity trackers

Systematic review of the validity and reliability of consumer-wearable activity trackers

Systematic review of the validity and reliability of consumer-wearable activity trackers.

BackgroundConsumer-wearable activity trackers are electronic devices used for monitoring fitness- and other health-related metrics. The purpose of this systematic review was to summarize the evidence for validity and reliability of popular consumer-wearable activity trackers (Fitbit and Jawbone) and their ability to estimate steps, distance, physical activity, energy expenditure, and sleep.MethodsSearches included only full-length English language studies published in PubMed, Embase, SPORTDiscus, and Google Scholar through July 31, 2015. Two people reviewed and abstracted each included study.ResultsIn total, 22 studies were included in the review (20 on adults, 2 on youth). For laboratory-based studies using step counting or accelerometer steps, the correlation with tracker-assessed steps was high for both Fitbit and Jawbone (Pearson or intraclass correlation coefficients (CC) > =0.80). Only one study assessed distance for the Fitbit, finding an over-estimate at slower speeds and under-estimate at faster speeds. Two field-based studies compared accelerometry-assessed physical activity to the trackers, with one study finding higher correlation (Spearman CC 0.86, Fitbit) while another study found a wide range in correlation (intraclass CC 0.36–0.70, Fitbit and Jawbone). Using several different comparison measures (indirect and direct calorimetry, accelerometry, self-report), energy expenditure was more often under-estimated by either tracker. Total sleep time and sleep efficiency were over-estimated and wake after sleep onset was under-estimated comparing metrics from polysomnography to either tracker using a normal mode setting. No studies of intradevice reliability were found. Interdevice reliability was reported on seven studies using the Fitbit, but none for the Jawbone. Walking- and running-based Fitbit trials indicated consistently high interdevice reliability for steps (Pearson and intraclass CC 0.76–1.00), distance (intraclass CC 0.90–0.99), and energy expenditure (Pearson and intraclass CC 0.71–0.97). When wearing two Fitbits while sleeping, consistency between the devices was high.ConclusionThis systematic review indicated higher validity of steps, few studies on distance and physical activity, and lower validity for energy expenditure and sleep. The evidence reviewed indicated high interdevice reliability for steps, distance, energy expenditure, and sleep for certain Fitbit models. As new activity trackers and features are introduced to the market, documentation of the measurement properties can guide their use in research settings.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-015-0314-1) contains supplementary material, which is available to authorized users.

Feasibility and preliminary efficacy of a physical activity counseling intervention using Fitbit in people with knee osteoarthritis: the TRACK-OA study protocol.

BackgroundPhysical activity (PA) reduces pain and improves functioning in people with knee osteoarthritis (OA), but few people with the condition meet recommended PA guidelines. Successful intervention strategies to increase PA include goal setting, action planning, self-monitoring, and follow-up feedback from a healthcare professional. Recently developed consumer wearable activity trackers allow users to set activity goals, self-monitor daily goal-progress, and provide feedback on goal attainment. It is hypothesized that a multi-component physiotherapist-led intervention that includes a short (40-min) education module, guided goal-setting and action planning, the use of a wristband activity tracker, and weekly follow-up phone calls will lead to increased PA outcomes.Methods/designThirty-six participants will be recruited from the community for a two-group pilot randomized controlled trial with a stepped-wedge design using an intention-to-treat analysis. Computer-generated block randomization will be performed using varying block sizes and a 1:1 allocation ratio. The 4-week intervention will be delivered immediately (immediate-intervention group) or after a 5-week delay (delayed-intervention group). Outcome measures of pain and disability (Knee Injury and OA Outcome Score), disease self-management ability (Partners in Health Scale), and objective bouted moderate-to-vigorous PA and sedentary time (BodyMedia SenseWear Mini Armband) will be collected at baseline (week 0) and two follow-ups (weeks 5 and 10), for a total study duration of 11 weeks. Feasibility data relating to process, resource, management, and scientific elements of the trial will be collected. Outcome measure and feasibility data will be summarized, and an estimate of intervention efficacy will be obtained by regression model with planned comparisons. The trial began recruiting in February 2015. To date, 34 subjects have been recruited.DiscussionThis study will evaluate the feasibility and preliminary efficacy of a novel intervention to promote PA in people living with knee OA. The results will provide valuable information to inform a larger randomized trial to assess intervention effectiveness.Trial registrationClinicalTrials.gov Identifier: NCT02313506 (registration date 8 December 2014). First participant randomized 20 February 2015.