Wearable Sensors for Athletic Performance: A Comparison of Discrete and Continuous Feature-Extraction Methods for Prediction Models
Mark White,
Beatrice De Lazzari,
Neil Bezodis
et al.
Abstract:Wearable sensors have become increasingly popular for assessing athletic performance, but the optimal methods for processing and analyzing the data remain unclear. This study investigates the efficacy of discrete and continuous feature-extraction methods, separately and in combination, for modeling countermovement jump performance using wearable sensor data. We demonstrate that continuous features, particularly those derived from Functional Principal Component Analysis, outperform discrete features in terms of… Show more
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