Tongue movement classification in chewing and swallowing using electromyography

Nurses who engaged in elderly care would like to assess their ability of chewing and swallowing because deterioration of the ability of chewing and swallowing will cause pulmonary aspiration. Currently, nurses can not assess the chewing and swallowing ability quantitatively. In this paper, to quantitatively assess the ability of chewing and swallowing, electromyography (EMG) signals around the lower jaw and the neck are obtained by some electrodes when the subject persons vocalize some Japanese pronunciations. Then, the obtained EMG signals are classified by some machine learning methods. fc-nearest neighbor methods show better classification results for the obtained EMG signals.