scholarly journals The Use of Consumer Wearable Physical Activity Monitors in Clinical Populations with Functional L imitations

2021 ◽  
Vol 3 (2) ◽  
Rheumatology ◽  
2021 ◽  
Author(s):  
Bonny Rockette-Wagner ◽  
Didem Saygin ◽  
Siamak Moghadam-Kia ◽  
Chester Oddis ◽  
Océane Landon-Cardinal ◽  
...  

Abstract Objective Idiopathic inflammatory myopathies (IIM) cause proximal muscle weakness, which affect activities of daily living. Wearable physical activity monitors (PAMs) objectively assess continuous activity with potential clinical usefulness in IIM assessment. We examined the psychometric characteristics for PAM outcomes in IIM. Methods Adult IIM patients were prospectively evaluated (baseline, 3 and 6-months) in an observational study. A waist-worn PAM (ActiGraph GT3X-BT) assessed average step counts/min, peak 1-min cadence, and vector magnitude/min. Validated myositis core set measures (CSM) including manual muscle testing (MMT), physician global disease activity (MD global), patient global disease activity (Pt global), extra-muscular disease activity (Ex-muscular global), HAQ-DI, muscle enzymes, and patient-reported physical function were evaluated. Test-retest reliability, construct validity, and responsiveness were determined for PAM measures and CSM using Pearson correlations and other appropriate analyses. Results 50 adult IIM patients enrolled [mean (SD) age, 53.6 (±14.6); 60% female, 94% Caucasian]. PAM measures showed strong test-retest reliability, moderate-to-strong correlations at baseline with MD global (r=-0.37- -0.48), Pt-global (r=-0.43- -0.61), HAQ-DI (r=-0.47- -0.59) and MMT (r = 0.37–0.52), and strong discriminant validity for categorical MMT and HAQ-DI. Longitudinal association with MD global (r=-0.38- -0.44), MMT (r = 0.50–0.57), HAQ-DI (r=-0.45- -0.55), and functional tests (r = 0.30–0.65) were moderate-to-strong. PAM measures were responsive to MMT improvement (≥10%) and moderate-to-major improvement on ACR/EULAR myositis response criteria. Peak 1-min cadence had the largest effect size and Standardized Response Means (SRMs). Conclusion PAM measures showed promising construct validity, reliability, and longitudinal responsiveness; especially peak 1-min cadence. PAMs provide valid outcome measures for future use in IIM clinical trials.


2017 ◽  
Vol 1 (S1) ◽  
pp. 40-41
Author(s):  
Stephen P. Wright ◽  
Kathryn Sandberg

OBJECTIVES/SPECIFIC AIMS: To analyze how consumer physical activity monitors are currently used in biomedical research. METHODS/STUDY POPULATION: Searches were conducted in Ovid Medline, PubMed Medline, clinicaltrials.gov, and NIH RePORTER using search terms including Fitbit, Jawbone, Apple watch, Garmin, Polar, Microsoft band, Misfit, Nike, Withings, and Xiaomi. Results were quantitated by category: condition/topic, intervention, enrollment status, study type and design, age, grant mechanism, and primary outcome. RESULTS/ANTICIPATED RESULTS: Fitbit is used >80%. There are 127 clinical studies using Fitbit devices listed in clinicaltrials.gov. In total, 48 have been completed while 79 are ongoing. Some studies have already published their findings; 40 papers cited in Ovid MEDLINE report use of a Fitbit device. NIH is now funding research that uses consumer physical activity monitors, and the NIH RePORTER shows the number of grants using Fitbit is rapidly increasing. DISCUSSION/SIGNIFICANCE OF IMPACT: The current state and potential growth of this technology is transforming biomedical research and is enabling us to ask new and more granular questions about activity and sleep in health and disease.


2018 ◽  
Vol 7 (1) ◽  
Author(s):  
Rasmus Tolstrup Larsen ◽  
Jan Christensen ◽  
Carsten Bogh Juhl ◽  
Henning Boje Andersen ◽  
Henning Langberg

2017 ◽  
Vol 312 (3) ◽  
pp. R358-R367 ◽  
Author(s):  
Stephen P. Wright ◽  
Tyish S. Hall Brown ◽  
Scott R. Collier ◽  
Kathryn Sandberg

A sedentary lifestyle and lack of physical activity are well-established risk factors for chronic disease and adverse health outcomes. Thus, there is enormous interest in measuring physical activity in biomedical research. Many consumer physical activity monitors, including Basis Health Tracker, BodyMedia Fit, DirectLife, Fitbit Flex, Fitbit One, Fitbit Zip, Garmin Vivofit, Jawbone UP, MisFit Shine, Nike FuelBand, Polar Loop, Withings Pulse O2, and others have accuracies similar to that of research-grade physical activity monitors for measuring steps. This review focuses on the unprecedented opportunities that consumer physical activity monitors offer for human physiology and pathophysiology research because of their ability to measure activity continuously under real-life conditions and because they are already widely used by consumers. We examine current and potential uses of consumer physical activity monitors as a measuring or monitoring device, or as an intervention in strategies to change behavior and predict health outcomes. The accuracy, reliability, reproducibility, and validity of consumer physical activity monitors are reviewed, as are limitations and challenges associated with using these devices in research. Other topics covered include how smartphone apps and platforms, such as the Apple ResearchKit, can be used in conjunction with consumer physical activity monitors for research. Lastly, the future of consumer physical activity monitors and related technology is considered: pattern recognition, integration of sleep monitors, and other biosensors in combination with new forms of information processing.


2020 ◽  
Vol 3 (2) ◽  
pp. 100-109
Author(s):  
Christopher P. Connolly ◽  
Jordana Dahmen ◽  
Robert D. Catena ◽  
Nigel Campbell ◽  
Alexander H.K. Montoye

Purpose: We aimed to determine the step-count validity of commonly used physical activity monitors for pregnancy overground walking and during free-living conditions. Methods: Participants (n = 39, 12–38 weeks gestational age) completed six 100-step overground walking trials (three self-selected “normal pace”, three “brisk pace”) while wearing five physical activity monitors: Omron HJ-720 (OM), New Lifestyles 2000 (NL), Fitbit Flex (FF), ActiGraph Link (AG), and Modus StepWatch (SW). For each walking trial, monitor-recorded steps and criterion-measured steps were assessed. Participants also wore all activity monitors for an extended free-living period (72 hours), with the SW used as the criterion device. Mean absolute percent error (MAPE) was calculated for overground walking and free-living protocols and compared across monitors. Results: For overground walking, the OM, NL, and SW performed well (<5% MAPE) for normal and brisk pace walking trials, and also when trials were analyzed by actual speeds. The AG and FF had significantly greater MAPE for overground walking trials (11.9–14.7%). Trimester did affect device accuracy to some degree for the AG, FF, and SW, with error being lower in the third trimester compared to the second. For the free-living period, the OM, NL, AG, and FF significantly underestimated (>32% MAPE) actual steps taken per day as measured by the criterion SW (M [SD] = 9,350 [3,910]). MAPE for the OM was particularly high (45.3%). Conclusion: The OM, NL, and SW monitors are valid measures for overground step-counting during pregnancy walking. However, the OM and NL significantly underestimate steps by second and third trimester pregnant women in free-living conditions.


2017 ◽  
Vol 13 (2) ◽  
pp. 82-89 ◽  
Author(s):  
Muhammad S. Beg ◽  
Arjun Gupta ◽  
Tyler Stewart ◽  
Chad D. Rethorst

Commercially available physical activity monitors provide clinicians an opportunity to obtain oncology patient health measures to an unprecedented degree. These devices can provide objective and quantifiable measures of physical activity, which are not subject to errors or bias of self-reporting or shorter duration of formal testing. Prior work on so-called quantified-self data was based on older-generation, research-grade accelerometers, which laid the foundation for consumer-based physical activity monitoring devices to be validated as a feasible and reliable tool in patients with cancer. Physical activity monitors are being used in chronic conditions including chronic obstructive pulmonary disease, congestive heart failure, diabetes mellitus, and obesity. Differing demographics, compounded with higher symptom and treatment burdens in patients with cancer, imply that additional work is needed to understand the unique strengths and weaknesses of physical activity monitors in this population. Oncology programs can systematically implement these tools into their workflows in an adaptable and iterative manner. Translating large amounts of data collected from an individual physical activity monitoring device into clinically relevant information requires sophisticated data compilation and reduction. In this article, we summarize the characteristics of older- and newer-generation physical activity monitors, review the validation of physical activity monitors with respect to health-related quality-of-life assessments, and describe the current role of these devices for the practicing oncologist. We also highlight the challenges and next steps needed for physical activity monitors to provide relevant information that can change the current state of oncology practice.


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