Jaw Motion From EMG Signals – A New Bruxism Monitor

B. Fu, M.P. Beddoes (Canada), C.C. Peck (Australia), R.K. Ward, and A.G. Hannam (Canada)

Keywords

Motion recognition, bruxism, signal processing, and ANN.

Abstract

Sleep bruxism is the involuntary and excessive clenching and grinding of teeth at night. It is one of the reasons that cause serious teeth damage and jaw muscle disorder and currently there is no definitive cure. Knowing actual jaw actions during bruxism will help in designing a more targeted treatment. This paper presents an EMG pattern recognition method to identify jaw movements. Pattern recognition is carried out using backpropagation artificial neural networks (BPN) trained by supervised learning. Different feature extraction methods have been implemented. Results are presented to support the feasibility of the suggested approach.

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