Aug 2026· Frontiers in Digital Health· Vol 8· 0 citations· 42 references
Medicine
TL;DR
Accuracy improved substantially over time, although variability across brands, activities, and populations persisted; Acceptability was generally high across brands, with long wearing time and good participant satisfaction.
Abstract
Background Wrist-worn physical activity trackers have advanced rapidly over the past two decades, evolving from simple accelerometer-based devices to multi-sensor systems integrating photoplethysmography, advanced movement classification, and machine-learning algorithms. Despite widespread use in both research and clinical settings, concerns remain regarding the accuracy and reliability of key metrics such as heart rate, energy expenditure, step count, and activity intensity. Methods This systematic review followed PRISMA guidelines (PROSPERO: CRD42024551740). MEDLINE, Scopus, PubMed, and SPORTDiscus were searched for studies evaluating the accuracy or acceptability of wrist-worn activity trackers in laboratory or free-living-simulated conditions. Eligible studies included healthy or general-population samples using any wrist-worn consumer or research-grade device. Reference standards included ECG, indirect calorimetry, doubly labelled water, manual step counting, and research-grade accelerometry. Of 1,659 records identified, 47 studies met inclusion criteria. Results and discussion Accuracy improved substantially over time, although variability across brands, activities, and populations persisted. Early heart-rate monitors (pre-2010) frequently reported Pearson correlation coefficient as low as 0.50 during exercise, while still being under the validity standard (0.90) at rest. Modern devices such as Apple Watch and Garmin vivosmart demonstrate markedly increased validity scores (typically above 0.80 during exercise), reflecting improvements in optical sensor quality and motion-artifact filtering. Energy-expenditure accuracy showed the least improvement; even recent devices exhibit 10%–40% error relative to indirect calorimetry, reflecting the inherent challenge of estimating metabolic rate without direct O₂ and CO₂ measurement. Step-count accuracy, prior to 2017 showed errors of up to 25%, now commonly falls below 5% for steady-state walking due to improved accelerometer precision and gait-pattern recognition. Classification of physical-activity intensity has also improved, with misclassification decreasing from >20% in early models to 10%–15% in current multi-sensor devices. Acceptability was generally high across brands, with long wearing time and good participant satisfaction.
Overall, accelerometer-based wearable sensors provide a feasible basis for monitoring prolonged sitting, and key gaps include inconsistent definitions, limited specific detection, heterogeneous data preparation and validation reporting, and a lack of translation from monitoring to actionable feedback.
Mei-Xing Liao, Kai Huang, Eva Libeert et al.· PLOS Digital Health· 0 citations
PURPOSE
To determine the criterion validity of research- and consumer-grade wearables (18 step-based methods) for quantifying step counts and step-derived walking metrics in free-living conditions.
METHODS
Sixty healthy adults (20-80 years, balanced by sex and decade) wore six monitors for seven days: StepWatch (ankl...
Adrien Chanteau, G. Faity, G. Mahé et al.· Medicine & Science in Sports...· 0 citations
Accelerometer-derived measures from wrist, thigh, and hip locations are strongly correlated and provide evidence to support pooled meta-analyses across wear locations and the development of location-agnostic processing software.
C. Zisou, B. Maylor, A. Acquah et al.· International Journal of Beh...· 0 citations
Objective assessment of physical activity in children and adolescents supports school health surveillance and the evaluation of behavioral interventions, but wearable recognition models are typically developed on adults, public benchmarks, or sample-level data splits that do not test performance on new users. Baseline...
Zhi-Yuan Yang, Liang-Wu Li, Yu-Jun Cai et al.· Medical Engineering and Phys...· 0 citations
Effective management of multiple sclerosis requires precise monitoring to detect disease progression, yet conventional episodic assessments often fail to capture subtle functional decline. This systematic review aimed to synthesize current evidence on passive digital phenotyping via smartphones and wearable sensors as...
P. De Blasiis, Annunziata Attena, A. Fullin et al.· Revue neurologique (Paris)· 0 citations
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