Proportional myoelectric and compensating control of a cable-conduit mechanism-driven upper limb exoskeleton

Recent studies have indicated that human motion recognition based on surface electromyography (sEMG) is a reliable and natural method for achieving motion intention. However, achieving accurate estimates of intended motion using a low computational cost is the main challenge in this scenario. In this study, a proportional myoelectric and compensating control method for estimating and assisting human motion intention with a cable-conduit mechanism-driven upper limb exoskeleton was proposed. The integral signal of sEMG and its time-delayed signals were applied as a new feature vector to represent the role of sEMG, which ensured the accuracy and real-time performance of motion estimation. An integrated circuit was used to reduce time of feature extraction. A feed-forward compensator was designed to compensate for the effect of the hysteresis problem in the exoskeleton, which is inevitable when the cable-conduit mechanism was applied to reduce the exoskeleton weight. The model-free control method based on PID method and least squares support vector machine were applied to avoid calculating the complex biomechanical model of human upper limb and the dynamic model of exoskeleton. Experimental results validated the proposed method. The average values of the root-mean-square difference (RMSD) for motion estimation were 0.0579 ± 0.0085 [motion with constant pace (CP)] and 0.0845 ± 0.0137 [motion with variable pace (VP)]. The Bland-Altman analysis results showed that the estimated angle of the proposed method was consistent with the actual angle. The performance of the control method was good, and the accuracies were 98.5608% ± 0.4485% (motion with CP) and 96.6119% ± 0.6628% (motion with VP).