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.
Castagneri, C., Agostini, V., Rosati, S., Balestra, G., Knaflitz, M.
IEEE Transactions on Neural Systems and Rehabilitation Engineering
S. Rosati, V. Agostini, M. Knaflitz and G. Balestra
Biomedical Signal Processing and Control