Human elbow joint torque is linearly encoded in electromyographic signals from multiple muscles.

When the central nervous system (CNS) develops a muscular activation pattern to accomplish a particular isometric task, it clearly uses information concerning the external task requirements. These task requirements serve as inputs to neural transformations that output muscular activations. However, the nature of the inputs is not exactly known. Electromyographic (EMG) signals from eight muscles spanning the human elbow, as well as the total joint torque, were collected during a submaximal isometric flexion/extension task at a single joint angle. The EMG data, without any torque information, were subjected to principal components analysis. We found that 98% of EMG data variation could be described by two principal components the first resembled the joint torque and the second resembled the sum of the EMG signals from all eight muscles. The findings suggest that the CNS encodes these two quantities during isometric tasks.