An automatic filtering procedure for processing biomechanical kinematic signals

Abstract

In biomechanics studies it is necessary to obtain acceleration of certain parts of the body in order to perform dynamical analysis. The motion capture systems introduce systematic measurement errors that appear in the form of high-frequency noise in recorded displacement signals. The noise is dramatically amplified when differentiating displacements to obtain velocities and accelerations. To avoid this phenomenon it is necessary to smooth the displacement signal prior to differentiation. The use of Singular Spectrum Analysis (SSA) is presented in this paper as an alternative to traditional digital filtering methods. SSA decomposes original time series into a number of additive time series each of which can be easily identified as being part of the modulated signal, or as being part of the random noise. An automatic filtering procedure based in SSA is presented in this work. The procedure is applied to two signals to demonstrate its performance. © Springer-Verlag Berlin Heidelberg 2004.