Electromyography for Assistive Robotics

This chapter provides a comprehensive overview of electromyography (EMG), a widely used technique for recording and evaluating electrical impulses generated by skeletal muscles. EMG signals have gained significant attention in the field of assistive robotics as a means of facilitating human–machine interaction (HMI). The chapter delves into the generation of EMG signals by muscles and their conversion into neurological commands that actuate body parts. Various techniques for recording EMG signals, such as Surface EMG (sEMG), Intramuscular EMG (iEMG), High-Density EMG (HD-EMG), Wireless EMG, and Dry EMG, are discussed in detail. The chapter further investigates the factors that can significantly impact the quality of EMG signals, including electrode placement, muscle fiber orientation, muscle contraction intensity, fatigue, skin impedance, crosstalk, filtering, and movement artifact. This chapter also provides insights into the implementation areas of EMG in assistive robotics, including prosthetics, exoskeletons, rehabilitation, wheelchair control, home automation, augmentative and alternative communication (AAC), human–robot interaction (HRI), and biomechanical analysis, where EMG signals have been increasingly utilized to enhance communication and control in human–robot interfaces. The chapter concludes with a discussion of the latest research advancements in the field of EMG and its application in assistive robotics, including the use of machine learning and artificial intelligence to improve EMG signal processing and interpretation, the development of new electrode materials and configurations, and the integration of EMG with other sensing technologies.