Classification Accuracy Of Wrist-worn Physical Activity Monitors Relative To Free-living Heart Rate

Abstract

Wrist-worn accelerometers have replaced hip-worn devices as the wear-site of choice when measuring physical activity (PA) in many large-scale studies. Data suggesting superior compliance with study protocols has largely driven this transition due to the potential for a more accurate view of habitual PA. Similarly, activity classification utilizing raw acceleration data has gained popularity relative to epoch-based activity count methods, owing to open source analytical packages, higher classification accuracy, and the potential for greater comparability among devices. As activity classification methods for wrist-worn accelerometer data are derived from PA performed in controlled settings, their accuracy in quantifying free-living PA is unknown. PURPOSE: The purpose of this study was to examine the classification accuracy of common PA quantification methods against a free-living, participant-specific intensity classification, heart rate reserve (HRR). METHODS: Healthy young adults (n=33; 18.6 ± 0.7 years, 69.6% female) wore a triaxial accelerometer on their non-dominant wrist and a heart rate monitor around their chest for 24 hours. Free-living intensity was quantified using traditional HRR ranges (e.g. MVPA ≥40%), calculated using resting heart rate during sleep and age-predicted maximum heart rate. Two commonly used data classification methods were applied, 1) Euclidean norm minus one (ENMO) values calculated from raw triaxial data using milligravitational (mg) cut points of light <100.6, moderate 100.6 - <428.8, vigorous ≥428.8, and MVPA ≥100.6, and 2) activity counts across 1-, 15-, and 60-second epochs with count per minute (cpm) cut points of light 1514 - <2199, moderate 2199 - <4712, vigorous ≥4721, and MVPA ≥2199. RESULTS: ENMO-based classification underestimated average MVPA by 31.9 ± 106.6% (19.4 ± 105.3 mins). In contrast, activity count-based classification overestimated average MVPA by 368.4 ± 396.2% (178.3 ± 105.1 mins), 708.9 ± 914.7% (271.0 ± 113.9 mins), and 798.9 ± 1170.7% (280.3 ± 131.7 mins), for 1-, 15-, and 60-second epochs, respectively. CONCLUSIONS: Data processing utilizing raw triaxial data and ENMO appears to offer the most accurate PA intensity classification. However, all methods substantially misclassify activity relative to free-living HRR.