Abstract
Muscle synergies encode motor activity as a linear superposition of multiple motor units composed of a temporal command exciting a specific network of muscles. This study examines muscle synergies derived from simple standing studies of a complete spinal cord injury (SCI) patient under epidural spinal stimulation. A popular technique for extracting these synergies from EMG data is non-negative matrix factorization (NNMF). However, standard NNMF algorithms do not allow for physiological delays for a neural signal to reach different muscles. These delays are prevalent in SCI patients under spinal stimulation, and so we propose a new algorithm (regularized ShiftNMF) to extract muscle synergies which account for signal delays. We find muscle synergies extracted by the regularized ShiftNMF algorithm are significantly better at reconstructing EMG activity, and the resulting features are physiologically consistent and more useful in describing patient behavior.
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