Upper Limb Phasic Muscle Synergies with Negative Weightings: Applications for Rehabilitation

The study of synergistic control has recently been improved with the introduction of a mixed-matrix factorization (MMF) algorithm that allows to remove the constrain of non-negativity on a customizable number of input channels, extending the range of application of the standard non-negative matrix factorization (NMF) algorithm. MMF can be used to extract kinematic-muscular synergies, where muscle data are non-negative and kinematic data are unconstrained, leading to synergies with positive and negative loads. The feature of analyzing negative data makes MMF also suitable for investigating the mixture of positive and negative waveforms that can be observed in the phasic electromyographic (EMG) signals recorded in a variety of movements of the upper-limb, as a result of the subtraction of tonic (gravity-related) EMG components. Muscle synergies that include negative coefficients are necessary to provide a compact representation of these data and account for negative EMG waveforms. In this paper, muscle synergies were extracted using MMF on 16-channel phasic EMG signals in forward and backward reaching movements performed by 5 healthy participants. This paper shows the potential of the method, preliminary interpretation of the results, and possible applications for motor evaluation in the rehabilitation field.