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Abstract
Sleep apnea and snoring are two sleep disorders that are likely to be genuine. Sleep apnea is defined as pauses during breathing or rare breathing during sleep and snoring is a sound delivered during sleep mode due to blocked development of air in the midst of breathing. The new standard diagnostic technique for these sleep disorders is costly polysomnography that requires human experts and is done in unique laboratories. Subsequently, to detect such types of disorders, a more comfortable and less expensive technique is needed. To expose them, late researchers concentrated on signal processing and pattern recognition as alternate modes. Through applying Tunable Q-Factor wavelet transform (TQWT), the flowing research focuses on the identification of sleep apnea and snoring using ECG signals. The results obtained showed a high degree of accuracy, about 85%.