Cristina Castagneri1, Valentina Agostini1, Gabriella Balestra2, Marco Knaflitz, Marina Carlone3, Giuseppe Massazza4
10:00 - 17:00 | Tue 30 Oct | Foyer | B1P-E
The study of EMG cycle patterns is an important tool in clinical research, for managing locomotion pathologies and rehabilitation. Statistical Gait Analysis (SGA) was introduced to process muscle cyclic activation patterns extracted from a functional walk. The CIMAP algorithm was recently introduced to improve the SGA. As result of CIMAP, principal activations, defined as those activations necessary to perform a specific cyclic movement, are extracted. They are coded using a binary string of activation values that characterizes a specific muscle. The aim of this work is to define an index to evaluate muscle-activation asymmetry in cyclic movements, using principal activations.
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