Surface EMG signal decomposition using empirically sustainable biosignal separation principles.

We introduce the concept of empirically sustainable principles for biosignal separation as a means of addressing the complexities that are practically encountered in the decomposition of surface electromyographic (sEMG) signals. Recently, we have identified two new principles of this type. The first principle places upper bounds on the inter-firing intervals and residual signal energies of the separated components. The second principle seeks a local minimum in the coefficient of variation of inter-firing intervals of each separated component. Upon incorporation of these principles into our latest Precision Decomposition system for sEMG signals, 20 to 30 motor unit action potential trains (MUAPTs) were decomposed per experimental sEMG signal from isometric contractions with trapezoidal force profiles. Our new system performs well even as the force generated by a muscle approaches maximum voluntary levels.