The Validation of a Pocket Worn Activity Tracker for Step Count and Physical Behavior in Older Adults during Simulated Activities of Daily Living

Author:

Ummels Darcy123ORCID,Bijnens Wouter4,Aarts Jos4,Meijer Kenneth5,Beurskens Anna J.12,Beekman Emmylou123

Affiliation:

1. Research Centre for Autonomy and Participation of Persons with a Chronic Illness, Zuyd University of Applied Sciences, Heerlen, Netherlands

2. Department of Family Medicine, CAPHRI School for Public Health and Primary Care, Maastricht University Medical Centre, Maastricht, Netherlands

3. ParaMedisch Centrum Zuid, Sittard, Netherlands

4. Instrument Development, Engineering and Evaluation, Maastricht University, Maastricht, Netherlands

5. Department of Nutrition and Movement Sciences, NUTRIM school for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, Netherlands

Abstract

Purpose: The purpose of this study was to validate optimized algorithm parameter settings for step count and physical behavior for a pocket worn activity tracker in older adults during ADL. Secondly, for a more relevant interpretation of the results, the performance of the optimized algorithm was compared to three reference applications Methods: In a cross-sectional validation study, 20 older adults performed an activity protocol based on ADL with MOXMissActivity versus MOXAnnegarn, activPAL, and Fitbit. The protocol was video recorded and analyzed for step count and dynamic, standing, and sedentary time. Validity was assessed by percentage error (PE), absolute percentage error (APE), Bland-Altman plots and correlation coefficients. Results: For step count, the optimized algorithm had a mean APE of 9.3% and a correlation coefficient of 0.88. The mean APE values of dynamic, standing, and sedentary time were 15.9%, 19.9%, and 9.6%, respectively. The correlation coefficients were 0.55, 0.91, and 0.92, respectively. Three reference applications showed higher errors and lower correlations for all outcome variables. Conclusion: This study showed that the optimized algorithm parameter settings can more validly estimate step count and physical behavior in older adults wearing an activity tracker in the trouser pocket during ADL compared to reference applications.

Funder

Brightlands Innovation Program LIME

Publisher

SAGE Publications

Subject

Geriatrics and Gerontology

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