A low-complexity sleep apnea detection method using millimeter-wave radar

Abstract

Non-contact sleep apnea detection based on radar is a technology of great significance and becomes a research hotspot because of the outstanding advantages of the radar sensors. In this paper, we propose a low-complexity sleep apnea detection method using millimeter-wave radar. The core idea of the proposed method is utilizing the reference thresholds to obtain strong generalization ability for different human targets and sleep postures. Firstly, we perform pre-processing and target detection to obtain the range bins occupied by the target. Secondly, we detect the big movement based on the body movement index and extract the features based on resting energy and respiratory waveform of multiple scatterers. Finally, the reference thresholds are utilized for sleep apnea detection to avoid the impact of different human targets and sleep postures. Experiments with ten participants and three sleep postures are conducted and results show that the proposed method can detect sleep apnea in different sleep postures including supine, lateral, and prone, with an average accuracy of 99.8%.