Sleep Posture Recognition With a Dual-Frequency Cardiopulmonary Doppler Radar

While Doppler radar can be used to measure cardiopulmonary vital signs during sleep, meaningful diagnostic assessments are often subject to knowledge of a subject's changing sleep posture. The torso Effective Radar Cross Section (ERCS) and displacement magnitude were studied for 20 human subjects in three imitated sleep posture categories using a dual-frequency Doppler radar system in an exploratory examination of the feasibility of using radar to recognize body orientation. Box plot statistical analyses were performed for comparative assessment of ratio variations in ERCS and respiration depth for three different imitated sleep postures. The observed statistical trends and correlations were applied to a physical model to develop posture decision algorithms with initial supine posture data used as a reference. A single-frequency algorithm tracked postures without error for 90% of the subjects using 2.4 GHz data, and 80% using 5.8 GHz data. As accuracy limitations were complementary, a dual-frequency algorithm was developed which recognized postures without error for 100% of the subjects.

Automated summary

The study explored the feasibility of using radar to recognize body orientation based on torso Effective Radar Cross Section and displacement magnitude. Statistical analyses were conducted for ratio variations in different sleep postures, leading to the development of posture decision algorithms. The algorithms achieved high accuracy rates, with a dual-frequency algorithm recognizing postures without error for 100% of the subjects.