Linear regression using intramuscular EMG for simultaneous myoelectric control of a wrist and hand system

Clinically available myoelectric prostheses are limited by the inability to control multiple degrees of freedom simultaneously. Linear regression-based control and parallel dual-site control (an extension of conventional amplitude-based methods using intramuscular EMG) are two frequently proposed approaches for simultaneous control. Both approaches assume linearity in the EMG features, but differ in whether users are required to independently modulate the EMG amplitudes from residual limb muscles. The objective of this preliminary study was to compare these two methods for the real-time control of a 3 degree-of-freedom (DOF) wrist/hand system. Both systems used intramuscular EMG amplitudes from six forearm muscles, and differed only in how the signals were used to predict intended prosthesis activity. Five able-bodied subjects were recruited to evaluate each control system (ten subjects total). Performance in a virtual Fitts' law task demonstrated that parallel dual-site control provided improved controllability when acquiring targets that required use of only one DOF, but linear regression control provided improved performance when acquiring targets requiring use of all three DOFs. Subjects using linear regression control were more easily able to activate multiple DOFs simultaneously, but at the expense of unintended movement when trying to isolate individual DOFs.