An Automatic Sequential Smoothing Method for Processing Biomechanical Kinematic Signals
نویسندگان
چکیده
The combined application of Singular Spectrum Analysis (SSA) and Cluster Analysis to the automatic smoothing of raw kinematic signals is an alternative to the use of traditional digital filtering and spline based methods. SSA is a non parametric technique that decomposes original time series into a number of additive time series each of which can be easily identified as being part of the noise present in the acquired signal. Nevertheless, the smoothing automation is not a trivial task. This work presents a heuristic automatic smoothing procedure for processing kinematic biomechanical signals based in sequential SSA. Cluster analysis is used to group the SSA decomposition in order to obtain several independent components in the frequency domain. The procedure eliminates iteratively the noise present in the signal in a simple and intuitive way. The new method is applied to several signals to demonstrate its performance. Key-Words: Signal processing, Smoothing, Noise removal, Singular Spectrum Analysis, Signal differentiation, Automatic smoothing, Cluster analysis.
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