非接触レーダーを用いた心拍数変動指標・体動・呼吸間隔ゆらぎ指標による睡眠段階推定

抄録

We proposed a technique of variable window-width of Moving-Average Method to extract only the pulse wave signals from the output signals of radars installed underneath the mattress, which enabled to calculate the heartbeat intervals. We applied a canonical discriminant analysis to classify the four sleep stages using the heart rate variability (HRV) derived from 10 students. LF/HF had a high degree of contribution to discriminate between LIGHT and DEEP sleep, and it was showed that the sleep cycle could be estimated (Figure). For the further improvement, we attempted to introduce a new decision tree analysis using not only HRV but also body movement index and respiratory interval indices.