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A Detection of Snore based on Breathing Sound Signal for Healthcare

Snore is considered as an early symptom of obstructive sleep apnea-hypopnea syndrome (OSAHS), which threatens the health of human beings by leading to cardiovascular and cerebrovascular diseases, even death. In this study, a detection system of snore during sleep is built via the breathing sound signal. The breathing sound signal can be acquired by a portable and noninvasive acquisition system. Then an index combination was proposed to represent the characteristic of snore in the time and frequency domain. The index combination is applied to detect snores by setting the threshold. The efficiency of the proposed system can be validated by a set of sleep breathing data. The average accuracy can reach 77.8 %, which shows the potential for deeper analysis for OSAHS.