A NOTE ON DATA SMOOTHING FOR MOVEMENT ANALYSIS - THE RELEVANCE OF A NONLINEAR METHOD

The goal of this experiment was to test a potentially useful nonlinear method for smoothing noisy position data, which often is encountered in the analysis of movement. This algorithm (7RY) uses a nonlinear smo othing function and behaves like a low-pass filter, automatically remo ving aberrant points; it is used prior to differentiation of time seri es so that usable acceleration information can be obtained. The experi mental procedure comprises position data collection along with direct accelerometric data recording. From the position-time data, (a) 7RY an d (b) Butterworth algorithms have been used to compute twice-different iated acceleration curves. The directly recorded acceleration measurem ents were then compared with the acceleration computed from the origin al position data. Although the results indicated an overall good fit b etween the recorded and the calculated acceleration curves, only the n onlinear method led to reliable acceleration curves when aberrant poin ts were present in the position data.