Dataset Information

Criterion validity of ActiGraph monitoring devices for step counting and distance measurement in adults and older adults: a systematic review.

ABSTRACT:

Background

Wearable activity monitors such as ActiGraph monitoring devices are widely used, especially in research settings. Various research studies have assessed the criterion validity of ActiGraph devices for step counting and distance estimation in adults and older adults. Although several studies have used the ActiGraph devices as a reference system for activity monitoring, there is no summarized evidence of the psychometric properties. The main objective of this systematic review was to summarize evidence related to the criterion validity of ActiGraph monitoring devices for step counting and distance estimation in adults and/or older adults.

Methods

Literature searches were conducted in six databases (Medline (OVID), Embase, IEEExplore, CINAHL, Engineering Village and Web of Science). Two reviewers independently conducted selection, a quality analysis of articles (using COSMIN and MacDermid's grids) and data extraction.

Results

This review included 21 studies involving 637 participants (age 30.3 ± 7.5 years (for adults) and 82.7 ± 3.3 years (for older adults)). Five ActiGraph devices (7164, GT1M, wGTX +, GT3X +/wGT3X + and wGT3X - BT) were used to collect data at the hip, wrist and ankle to assess various walking and running speeds (ranging from 0.2 m/s to 4.44 m/s) over durations of 2 min to 3 days (13 h 30 mins per day) for step counting and distance estimation. The ActiGraph GT3X +/wGT3X + and wGT3X - BT had better criterion validity than the ActiGraph 7164, wGTX + and GT1M according to walking and running speeds for step counting. Validity of ActiGraph wGT3X + was good for distance estimation.

Conclusion

The ActiGraph wGT3X - BT and GT3X +/wGT3X + have good criterion validity for step counting, under certain conditions related to walking speeds, positioning and data processing.

SUBMITTER: Ngueleu AM

PROVIDER: S-EPMC9575229 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Publications

Criterion validity of ActiGraph monitoring devices for step counting and distance measurement in adults and older adults: a systematic review.

Ngueleu Armelle-Myriane AM Barthod Corentin C Best Krista Lynn KL Routhier François F Otis Martin M Batcho Charles Sèbiyo CS

Journal of neuroengineering and rehabilitation 20221017 1

<h4>Background</h4>Wearable activity monitors such as ActiGraph monitoring devices are widely used, especially in research settings. Various research studies have assessed the criterion validity of ActiGraph devices for step counting and distance estimation in adults and older adults. Although several studies have used the ActiGraph devices as a reference system for activity monitoring, there is no summarized evidence of the psychometric properties. The main objective of this systematic review w ...[more]

PMID: 36253787

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Project description:BackgroundStandardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies.PurposeTo expand a previously published child/youth catalog of validity indices to include adults (21-40, 41-60 and 61-85 years of age) assessed across a range of treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist).MethodsTwo hundred fifty-eight adults (52.5 ± 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015-2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV).ResultsOver the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p ≤ 0.045).ConclusionsStandardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy.Trial registrationClinicaltrials.gov NCT02650258. Registered 24 December 2015.

Project description:BACKGROUND:To assess whether commercial-grade activity monitors are appropriate for measuring step counts in older adults, it is essential to evaluate their measurement properties in this population. OBJECTIVE:This study aimed to evaluate test-retest reliability and criterion validity of step counting in older adults with self-reported intact and limited mobility from 6 commercial-grade activity monitors: Fitbit Charge, Fitbit One, Garmin vívofit 2, Jawbone UP2, Misfit Shine, and New-Lifestyles NL-1000. METHODS:For test-retest reliability, participants completed two 100-step overground walks at a usual pace while wearing all monitors. We tested the effects of the activity monitor and mobility status on the absolute difference in step count error (%) and computed the standard error of measurement (SEM) between repeat trials. To assess criterion validity, participants completed two 400-meter overground walks at a usual pace while wearing all monitors. The first walk was continuous; the second walk incorporated interruptions to mimic the conditions of daily walking. Criterion step counts were from the researcher tally count. We estimated the effects of the activity monitor, mobility status, and walk interruptions on step count error (%). We also generated Bland-Altman plots and conducted equivalence tests. RESULTS:A total of 36 individuals participated (n=20 intact mobility and n=16 limited mobility; 19/36, 53% female) with a mean age of 71.4 (SD 4.7) years and BMI of 29.4 (SD 5.9) kg/m2. Considering test-retest reliability, there was an effect of the activity monitor (P<.001). The Fitbit One (1.0%, 95% CI 0.6% to 1.3%), the New-Lifestyles NL-1000 (2.6%, 95% CI 1.3% to 3.9%), and the Garmin vívofit 2 (6.0%, 95 CI 3.2% to 8.8%) had the smallest mean absolute differences in step count errors. The SEM values ranged from 1.0% (Fitbit One) to 23.5% (Jawbone UP2). Regarding criterion validity, all monitors undercounted the steps. Step count error was affected by the activity monitor (P<.001) and walk interruptions (P=.02). Three monitors had small mean step count errors: Misfit Shine (-1.3%, 95% CI -19.5% to 16.8%), Fitbit One (-2.1%, 95% CI -6.1% to 2.0%), and New-Lifestyles NL-1000 (-4.3%, 95 CI -18.9% to 10.3%). Mean step count error was larger during interrupted walking than continuous walking (-5.5% vs -3.6%; P=.02). Bland-Altman plots illustrated nonsystematic bias and small limits of agreement for Fitbit One and Jawbone UP2. Mean step count error lay within an equivalence bound of ±5% for Fitbit One (P<.001) and Misfit Shine (P=.001). CONCLUSIONS:Test-retest reliability and criterion validity of step counting varied across 6 consumer-grade activity monitors worn by older adults with self-reported intact and limited mobility. Walk interruptions increased the step count error for all monitors, whereas mobility status did not affect the step count error. The hip-worn Fitbit One was the only monitor with high test-retest reliability and criterion validity.

Project description:Multiple wearable devices that purport to measure physical activity are widely available to consumers. While they may support increases in physical activity among people with multiple sclerosis (MS) by providing feedback on their performance, there is little information about the validity and acceptability of these devices. Providing devices that are perceived as inaccurate and difficult to use may have negative consequences for people with MS, rather than supporting participation in physical activity. The aim of this study was, therefore, to assess the validity and acceptability of commercially available devices for monitoring step-count and activity time among people with MS. Nineteen ambulatory adults with MS [mean (SD) age 52.1 (11.9) years] participated in the study. Step-count was assessed using five commercially available devices (Fitbit Alta, Fitbit Zip, Garmin Vivofit 4, Yamax Digi Walker SW200, and Letscom monitor) and an activPAL3μ while completing nine everyday activities. Step-count was also manually counted. Time in light activity, moderate-to-vigorous activity, and total activity were measured during activities using an Actigraph GT3X accelerometer. Of the 19 participants who completed the validity study, fifteen of these people also wore the five commercially available devices for three consecutive days each, and participated in a semi-structured interview regarding their perception of the acceptability of the monitors. Mean percentage error for step-count ranged from 12.1% for the Yamax SW200 to -112.3% for the Letscom. Mean step-count as manually determined differed to mean step-count measured by the Fitbit Alta (p = 0.002), Garmin vivofit 4 (p < 0.001), Letscom (p < 0.001) and the research standard device, the activPAL3μ (p < 0.001). However, 95% limits of agreement were smallest for the activPAL3μ and largest for the Fitbit Alta. Median percentage error for activity minutes was 52.9% for the Letscom and 100% for the Garmin Vivofit 4 and Fitbit Alta compared to minutes in total activity. Three inductive themes were generated from participant accounts: Interaction with device; The way the device looks and feels; Functionality. In conclusion, commercially available devices demonstrated poor criterion validity when measuring step-count and activity time in people with MS. This negatively affected the acceptability of devices, with perceived inaccuracies causing distrust and frustration. Additional considerations when designing devices for people with MS include an appropriately sized and lit display and ease of attaching and charging devices.

Project description:PurposeAn accurate assessment of time spent in 24-hour movement behaviors (24 h-MBs) is crucial in exploring health related associations. This study aims to evaluate the concurrent validity of the Daily Activity Behavior Questionnaire (DABQ) compared to the ActiGraph using absolute and relative indicators of validity.MethodsThis cross-sectional observational study included 105 adults (45 ± 13 y/o, 54% female). Participants wore an ActiGraph during seven consecutive days followed by filling in the DABQ recalling the past seven days. Intraclass correlations (95% confidence intervals), Bland-Altman plots, Spearman's correlations and the magnitude of error were calculated to estimate the absolute agreement and validity. Interaction effects between sociodemographic variables and the measurement methods were explored in mixed models. All analyses were compared by four commonly used data processing methods for ActiGraph data (cut-points and data reduction method-specific).ResultsModerate absolute agreement (ICC = 0.56) and validity (rhosleep=0.58) was found for sleep comparing the DABQ with the ActiGraph. Time spent in sedentary behavior (SB), light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) showed poor absolute agreement (ICCSB: 0.01-0.38, ICCLPA: 0.00-0.31; ICCMVPA: 0.23-0.30) and validity (rhoSB: 0.01-0.43, rhoLPA: 0.10-0.46; rhoMVPA: 0.38-0.44) comparing the DABQ with the ActiGraph. The Ranges in ICC and Spearmans' rho include the comparison between the four data processing methods. A significant interaction was found between the measurement method and educational level (p < 0.001), in specific for sleep, SB and LPA.ConclusionCompared to the ActiGraph, the DABQ showed accurate time-use estimates for sleep but presented poor to moderate evidence of validity regarding SB, LPA and MVPA. This was shown in underestimations regarding SB and MVPA, and overestimations regarding LPA. However, educational level and data processing methods contributed to these variations.

Project description:PurposeThe objective of this systematic review and meta-analysis was to assess the validity of the Actigraph triaxial accelerometer device in measuring physical activity energy expenditure (PAEE) in healthy adults, with indirect calorimetry (IC) serving as the validity criterion.MethodsA comprehensive search was conducted using the PubMed, Web of Science, and sportdiscuss databases, in addition to manual searches for supplementary sources. Search strategies were employed that involved conducting single keyword searches using the terms "gt3x" and "Actigraph gt3x". The literature search encompassed the timeframe spanning from 1 January 2010 to 1 March 2023. The methodological quality of the studies included in the analysis was evaluated using both the Downs and Black checklist and the Consensus-Based Criteria for Selection of Measurement Instruments (COSMIN) checklist. The meta-analysis was conducted using the Review Manager 5.4 software. The standardized mean difference (SMD) was calculated and expressed as a 95% confidence interval (CI). The significance level was set at α = 0.05. A systematic assessment of the Actigraph's performance was conducted through the descriptive analysis of computed effect sizes.ResultsA total of 4738 articles were retrieved from the initial search. After eliminating duplicate articles and excluding those deemed irrelevant, a comprehensive analysis was conducted on a total of 20 studies, encompassing a combined sample size of 1247 participants. The scores on the Downs and Black checklist ranged from 10 to 14, with a mean score of 11.35. The scores on the COSMIN checklist varied from 50% to 100%, with an average score of 65.83%. The meta-analysis findings revealed a small effect size (SMD = 0.01, 95% CI = 0.50-0.52, p = 0.97), indicating no statistically significant difference (p > 0.05).ConclusionsThe meta-analysis revealed a small effect size when comparing the Actigraph and IC, suggesting that the Actigraph can be utilized for assessing total PAEE. Descriptive analyses have indicated that the Actigraph device has limited validity in accurately measuring energy expenditure during specific physical activities, such as high-intensity and low-intensity activities. Therefore, caution should be exercised when utilizing this device for such purposes. Furthermore, there was a significant correlation between the activity counts measured by the Actigraph and the PAEE, indicating that activity counts can be utilized as a predictive variable for PAEE.

Dataset Information

Criterion validity of ActiGraph monitoring devices for step counting and distance measurement in adults and older adults: a systematic review.

Background

Methods

Results

Conclusion

Publications

Criterion validity of ActiGraph monitoring devices for step counting and distance measurement in adults and older adults: a systematic review.

Similar Datasets

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