Cyclical movements are characterized by different muscle activation patterns (onset-offset timings). To interpret correctly the electromyographic (EMG) data, it is important to group cycles sharing similar EMG activation patterns. We developed a method based on hierarchical clustering, able to group cycles showing homogeneous onset-offset activation intervals.
The method was applied to EMG acquired during gait. A by-product of the clustering procedure is the possibility to extract the principal activations of a muscle, that are those activations necessary for the specific muscle contribution to the biomechanical function of walking. Principal activations were also used to define a robust index to quantitative assess the asymmetry of muscle activations during locomotion.