The subject of this study was fencing and the object was to classify the fundamental motions of fencers by creating a library of movements. Based on this library, thus, the recognition of motions during a real fencing match can be made. Kinematic data were acquired by a motion capture system (Vicon). The automated algorithm that recognized motions is based on three steps: a Principal Component Analysis for data dimension reduction, an innovative wavelet-based analysis of signals and a feature extraction method. The algorithm was tested on high level fencing athletes and it was found to be robust with a 12% of misclassification rate. It gave a description of how atheletes move and showed that in real match athletes do not execute fundamental motions but they mix different techniques in order to surprise the opponent.
Mantovani, G., Ravaschio, A., Piaggi Pa, P., & Landi, A. (2010). Fine classification of complex motion pattern in fencing. In Procedia Engineering (Vol. 2, pp. 3423–3428). Elsevier Ltd. https://doi.org/10.1016/j.proeng.2010.04.168