ABSTRACT
Human activity monitoring technology is one of the most relevant technologies for ambient assisted living, surveillance-based security, sports and fitness activities, and healthcare of elderly people. Activity monitoring takes place in two phases: acquisition of the body signals and identification of the activities that are performed. Among the body signals, the surface electromyography (sEMG) signal has recently received great interest for its ability to give useful information about the body movements that are performed and its ease of being acquired throughout the skin of the body using small wireless sensors. This chapter aims to investigate the state of the art of wearable sEMG circuits and systems and recent advances on systems and techniques based on multimodal signal processing for recognizing human activities from sEMG-based sensors.
