The development and validation of an open-source accelerometery algorithm for measuring jump height and frequency in ballet

Abstract

ABSTRACT The aim was to determine the validity of an open-source algorithm for measuring jump height and frequency in ballet using a wearable accelerometer. Nine professional ballet dancers completed a routine ballet class whilst wearing an accelerometer positioned at the waist. Two investigators independently conducted time-motion analysis to identify time-points at which jumps occurred. Accelerometer data were cross-referenced with time-motion data to determine classification accuracy. To determine the validity of the measurement of jump height, five participants completed nine jetés, nine sautés and three double tour en l’air from a force plate. The jump height predicted by the accelerometer algorithm was compared to the force plate jump height to determine agreement. Across 1440 jumps observed in time-motion analysis, 1371 true positives, 34 false positives and 69 false negatives were identified by the algorithm, resulting in a sensitivity of 0.98, a precision of 0.95 and a miss rate of 0.05. For all jump types, mean absolute error was 2.6 cm and the repeated measures correlation coefficient was 0.97. Bias was 1.2 cm and 95% limits of agreement were −4.9 to 7.2 cm. The algorithm may be used to manage jump load, implement periodization strategies, or plan return-to-jump pathways for rehabilitating athletes.