Non-contact detection of Doppler bio-signals based on gradient decent and extended DACM algorithms

Abstract

In this paper, we present a Doppler radar sensor based approach capable of detecting both small-and large-scale biological motions. To fully recover the time domain motion information from backscattered microwave signals, the gradient descent and the extended DACM algorithms are utilized to solve the problems caused by DC offset and phase wrapping issues. Experimental results show that both Doppler bio-signals of the small-scale human cardiac motion and the large-scale human walk can be accurately detected. The proposed approach provides a generalized method for detecting different Doppler bio-signals in biomedical and healthcare applications.

High Dynamic-Range Motion Imaging Based on Linearized Doppler Radar Sensor

“…Therefore, previous noncontact VSD detections mainly focus on retrieving frequency information of human respiration and heartbeat rates, and monitoring changes in speed for movements detection such as fall detection [17], [18], rather than recovering the exact and continuous movement in time domain. In [15], we pointed out that apart from the frequency information of vital signs, substantial time-domain motion information is carried by the backscattered signals. If a comprehensive linearization to the architecture and the phase demodulation algorithm of DRSs can be carried out, restrictions of the null point, phase wrapping, and other nonlinear issues can be theoretically avoided, and accurate reconstruction of the motion can be achieved.…”

“…Compared with the millimeter-or centimeter-level human cardiac motion measured in [14] and [15], the amplitude of a tuning fork's vibration could be micrometer level, which is hard for human eyes to discriminate. Fig.…”

“…"High-dynamic-range" emphasizes that the DRS can detect different scales of human body or organ motion. Examples of such motions include small-scale motions such as human vital signs [11]- [13], rhythmical beat of human heart [14], [15], and blood flow in the cardiovascular system [16]; as well as large-scale motions such as human walking and fall events [17], [18]. "Linearized" means the DRS can produce a highly linear representation of the original motion.…”