Yonglei Zheng

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PROBLEM ADDRESSED Wrist-worn accelerometers are associated with greater compliance. However, validated algorithms for predicting activity type from wrist-worn accelerometer data are lacking. This study compared the activity recognition rates of an activity classifier trained on acceleration signal collected on the wrist and hip. METHODOLOGY 52 children(More)
Introduction • Goal: accurate, objective and detailed measurement of physical activity • Why? Many health related reasons… • Understand relationship between physical activity and health outcomes • Detecting at risk populations • Measure effectiveness of intervention strategies Introduction • Accelerometers are a cheap, reliable and unobtrusive way to(More)
UNLABELLED Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research(More)
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