[A Feasibility Study on Bioradar Eye Movement Detection for Sleep Stage Classification].

Abstract

To address the problem of low classification accuracy in existing bioradar sleep staging technology caused by the use of indirect physiological features, research on bioradar sleep eye movement detection is conducted. A synchronous acquisition platform for millimeter-wave bioradar and electrooculogram (EOG)/polysomnography (PSG) is established. Simulated eye movement experiments and real sleep experiments are carried out respectively. In the simulated eye movement experiments, the time-domain cross-correlation coefficient between the eye movement signals detected by the bioradar and the EOG signals exceeds 0.90. The error in the dominant frequency within the frequency domain is less than 0.05 Hz. In the real sleep experiments, eye movement signals consistent with EOG are also detected by the bioradar. These signals exhibit explosive characteristics in the rapid eye movement period, intermittent smooth fluctuation characteristics in the light sleep period, and stable low-amplitude fluctuation characteristics in the deep sleep period. The experimental results indicate that the bioradar can effectively detect and distinguish three typical sleep eye movement events: rapid eye movement, slow eye movement, and no significant eye movement. This provides a new technical approach for bioradar sleep staging, which holds promise for further improving staging accuracy.