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Sleep is an important physiological activity of human body, in recent years, the sleep quality has been highlighted; therefore, the paper explores the effective and feasible method to monitor the sleep quality from the perspective of EEG, and designs a portable sleep quality monitoring system from the perspective of software and hardware. Besides, it studies and analyzes the data collected based on the portable EEG acquisition equipment as well as the CAP Sleep EEG database, and explores the effective algorithm for sleep segmentation by aid of the power spectrum analysis and BP neural network. In addition, the experiment conducts evaluation on the sleep segmentation and quality preliminarily, and proves the correctness of the portable sleep quality monitoring system as well as the effectiveness of implementing the sleep segmentation based on the EEG data. The research puts forward to rely on the single-guide EEG for implementing the sleep segmentation, which provides important experience reference for researching the portable and market-oriented sleep monitoring equipment as well as other applications.

Non-Contact Sleep Staging Algorithm Based on Physiological Signal Monitoring