Wavelet Based Compression Analysis For Tele-Sleep Bruxism Diagnosis

Bruxism is a medical condition in which a person’s teeth grind or clench. If you have bruxism, you may have unconsciously clenched or ground your teeth while awake (awake bruxism) or while sleeping (sleep bruxism). Polysomnography, Overnight sleep studies at a sleep clinic are the most definitive approach to identify sleep bruxism. Polysomnography will include monitoring of the heart and muscles, as well as pulse and blood pressure data. To transmit polysomnography data via telemedicine, the best compression technique should be chosen. As a result, in this study, the dominant signal in sleep bruxism diagnosis, such as ECG and EMG, is tested under various wavelets to find the best wavelet for compression and data transmission with low error. ECG and EMG signals are tested using the MATLAB tool with various wavelet transforms such as Haar, db8, symmetrical, coiflets, Biorthogonal, and reverse bior wavelet transforms. To determine the best wavelet, for each wavelet, the experimental findings for Percent Root Mean Square Difference (PRD), Compression Ratio (CR), and Recovery Ratio are obtained.