SEMG analysis for recognition of rehabilitation actions

Abstract

Surface electromyography (sEMG), a measurement of biomedical electronic signals from the muscle surface using electrodes, shows the motor status of the nerve-muscle system and motor instruction information. Active motion intention and the motor status of impaired stroke patients can be acquired by sEMG. Currently, sEMG is widely used in prosthetic arm control, rehabilitation robot control, exoskeletal power assist robot control, tele-operated robots, virtual reality, and so on. The application of sEMG to a rehabilitation robot is studied in this chapter. sEMG is used to build an information channel between the patient and the robot to obtain biological feedback control during rehabilitation training. It is of great significance for the improvement of patients’ consciousness of active participation. It will also help to improve the evaluation and efficiency of rehabilitation. It establishes a general scheme for other applications related to the human-machine interface. First, the generation mechanism and characteristic of the sEMG signal are presented in this chapter. Next, current feature analysis methods of sEMG are summarized. The advantages and disadvantages of each method are discussed. Then, an example of sEMG signal analysis for the recognition of rehabilitation actions is given. Finally, future work and discussions are given in the conclusion.