Evaluation Of Swallowing Function Based On High-Density Surface EMG

Dysphagia is a common disorder among people of all age groups, especially the elderly, which may result in a serious health risk for them. Considering swallowing is essentially a semiautomatic motor action of muscles, Surface electromyography has been used extensively as one of the best tools to monitor muscles activities, since it corresponds directly to the physiological response of muscle contraction and can be non-invasively acquired from skin surface.Most of the previous investigations on muscle activities during swallowing were primarily based on the single-channel or few-channel (mostly from 1 to 4 electrodes) sEMG recordings from an individual muscle or a muscle pair. However, the reason of dysphagia always is not that all the muscles can not normal contraction, but due to a single or partial muscle do not have effectively control. It is difficult for the traditional sEMG recording to monitor that.High-density sEMG technique is a new method to investigate muscle activities in both temporal and spatial domains. The sEMG recordings with a two-dimension electrode array can be used to decompose sEMG signals and extract localization information. Unlike conventional single-channel or few-channel EMG, high-density sEMG is capable of collecting global information from a wide area of muscles and providing the spatial properties of electrical muscle activities.The main disadvantage of sEMG is the problem of "cross-talk", whereby several different muscles may contribute to the recording of a given electrode, making the source of the signal difficult to interpret. This is of particular concern with swallowing sEMG, where several muscles involved with swallowing are in close proximity and deep of the surface. This is probably why the role of sEMG in swallowing has been largely restricted to its therapeutic potential in biofeedback.In order to overcome the disadvantage of sEMG, three kinds of algorithms——High-Density sEMG maps, independent component analysis and source localization——are put forward to decode sEMG respectively from the perspective of time and space.