Joint Angle and Torque Estimation Using Multifrequency Electrical Impedance Myography and Surface Electromyography

This article explores the feasibility of combining surface electromyography (sEMG) and multifrequency electrical impedance myography (mfEIM) for predicting joint angles and torques. We utilize a current-limited multifrequency electrical impedance spectrometer to simultaneously perform mfEIM on the biceps brachii and triceps brachii at 14 frequencies. The same system also measures the sEMG signals using the same electrodes. Measurements are conducted while subjects perform tasks in a 1-degree-of-freedom (DOF) exoskeleton, which enables the measurement of elbow joint torque and angle. We train time-delay neural networks (TDNNs) to model the relationships between mfEIM, sEMG, joint torque, and joint angle. The results demonstrate that the sEMG signal can predict joint torque and that mfEIM can predict joint angle. Additionally, we find indications that a combination of sEMG and mfEIM enhances joint torque predictions compared to using sEMG alone. We also determine the delays between the sEMG, mfEIM signals, and the joint angle and torque, finding that the joint torque signal has a delay relative to the sEMG signal of 155 ms during an isometric exercise and 125 ms during dynamic tasks. These results suggest that combining sEMG and mfEIM measurements could provide additional insights during biomedical experiments.