Aidan Acquah

ActiNet: an open-source tool for activity intensity classification of wrist-worn accelerometry using self-supervised deep learning

Abstract The use of accurate and reliable open-source human activity recognition (HAR) models on passively collected wrist-accelerometer data is essential in large-scale epidemiological studies that investigate the association between physical activity and health outcomes. While...

Towards harmonised accelerometer-derived physical activity: a comparability study across wrist, thigh, and hip wear locations

Abstract Background Wearable devices are widely used in epidemiological studies, but differences in wear locations make data harmonisation and pooled meta-analyses challenging. We aimed to (i) assess the comparability of measures of physical activity and sedentary behaviour deriv...