The Elman neural network was used to decode the relationship between extracted motor commands and muscle synergies. To extract the maximum correlation of neural commands with muscle synergies, application of a combined partial least squares and canonical correlation analysis (PLS-CCA) method was proposed. To find the relationship between brain activities and muscle synergies, electroencephalogram (EEG) and electromyogram (EMG) signals were acquired simultaneously during activities of daily living. The main purpose of this paper is to develop synergy-based neural decoding of motor primitives, so for the first time, brain activity and muscle synergy map of the upper extremity was investigated in the activity of daily living movements.
Muscle synergies have been hypothesized as specific predefined motor primitives that the central nervous system can reduce the complexity of motor control by using them, but how these are expressed in brain activity is ambiguous yet.
