Contactless Heartbeat Detection from CW-Doppler Radar using Windowed-Singular Spectrum Analysis
Yuki Iwata, Koichiro Ishibashi, Guanghao Sun, Ha Manh Luu, Hán Trọng Thanh, Linh Trung NGUYEN, Trong Tuan
Abstract
Yuki Iwata, Koichiro Ishibashi, Guanghao Sun, Ha Manh Luu, Hán Trọng Thanh, Linh Trung NGUYEN, Trong Tuan
Abstract
The continuous-wave Doppler radar measures the movement of a chest surface including of cardiac and breathing signals and the body movement. The challenges associated with extracting cardiac information in the presence of respiration and body movement have not been addressed thus far. This paper presents a novel method based on the windowed-singular spectrum analysis (WSSA) for solving this issue. The algorithm consists of two processes: signal decomposition via WSSA followed by the reconstruction of decomposed heartbeat signals through convolution. An experiment was conducted to collect chest signals in 212 people by Doppler radar. In order to confirm the effect of reducing the large noise by the proposed method, we evaluated 136 signals that were considered to contain respiration body movements from the collected signals. When comparing to the performance of a band-pass filter, the proposed analysis achieves improved beat count accuracy. The results indicate its applicability to contactless heartbeat estimation under involving respiration and body movements.
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The continuous-wave Doppler radar measures the movement of a chest surface including of cardiac and breathing signals and the body movement. The challenges associated with extracting cardiac information in the presence of respiration and body movement have not been addressed thus far. This paper presents a novel method based on the windowed-singular spectrum analysis (WSSA) for solving this issue. The algorithm consists of two processes: signal decomposition via WSSA followed by the reconstruction of decomposed heartbeat signals through convolution. An experiment was conducted to collect chest signals in 212 people by Doppler radar. In order to confirm the effect of reducing the large noise by the proposed method, we evaluated 136 signals that were considered to contain respiration body movements from the collected signals. When comparing to the performance of a band-pass filter, the proposed analysis achieves improved beat count accuracy. The results indicate its applicability to contactless heartbeat estimation under involving respiration and body movements.
Key concepts: Heartbeat, Doppler radar, Computer science, Radar, Doppler effect, Singular spectrum analysis, Pulse-Doppler radar, SIGNAL (programming language)