Karate is a martial art that partly depends on subjective scoring of complex movements. Principal component analysis (PCA)-based methods can identify the fundamental synergies (principal movements) of motor system, providing a quantitative global analysis of technique. In this study, we aimed at describing the fundamental multi-joint synergies of a karate performance, under the hypothesis that the latter are skilldependent; estimate karateka's experience level, expressed as years of practice. A motion capture system recorded traditional karate techniques of 10 professional and amateur karateka. At any time point, the 3D-coordinates of body markers produced posture vectors that were normalised, concatenated from all karateka and submitted to a first PCA. Five principal movements described both gross movement synergies and individual differences. A second PCA followed by linear regression estimated the years of practice using principal movements (eigenpostures and weighting curves) and centre of mass kinematics (error: 3.71 years; R2 = 0.91, P ≪ 0.001). Principal movements and eigenpostures varied among different karateka and as functions of experience. This approach provides a framework to develop visual tools for the analysis of motor synergies in karate, allowing to detect the multi-joint motor patterns that should be restored after an injury, or to be specifically trained to increase performance.
Keywords: Martial arts; biomechanics; coordinative structures; kihon; principal movements.