Wang Jianqi

A new method for identifying the life parameters via radar

It has been proved that the vital signs can be detected via radar. To better identify the life parameters such as respiration and heartbeat, a novel method combined with several signal processing techniques is presented. Firstly, to improve the signal-to-noise ratio (SNR) of the life signals, the signal accumulation technique by FFT is used. Then, to restrain the interferences produced by moving objects, a dual filtering algorithm (DFA) which is able to remove the interferences by tracing the interfering spectral peaks is proposed. Finally, the wavelet transform is applied to separate the heartbeat from the respiration signal. The method cannot only help to automatically detect the existence of human beings effectively, but also identifying the parameters like respiration, heartbeat, and body-moving signals significantly. Experimental results demonstrated that the method is very promising in identifying the life parameters via radar.It has been proved that the vital signs can be detected via radar. To better identify the life parameters such as respiration and heartbeat, a novel method combined with several signal processing techniques is presented. Firstly, to improve the signal-to-noise ratio (SNR) of the life signals, the signal accumulation technique by FFT is used. Then, to restrain the interferences produced by moving objects, a dual filtering algorithm (DFA) which is able to remove the interferences by tracing the interfering spectral peaks is proposed. Finally, the wavelet transform is applied to separate the heartbeat from the respiration signal. The method cannot only help to automatically detect the existence of human beings effectively, but also identifying the parameters like respiration, heartbeat, and body-moving signals significantly. Experimental results demonstrated that the method is very promising in identifying the life parameters via radar.

Detecting and Identifying Two Stationary-Human-Targets: A Technique Based on Bioradar

Bioradar is a novel kind of radar combining the technology of radar and biomedical engineering. It can detect vital signals (such as breath, heartbeat, movement, etc.) in a certain distance through the nonmetal substances (such as brick walls, rubble, etc.) without using electrodes or sensors. However, multi-stationary-human-target identifying and locating has not been resolved yet. Based on the Ultra Wide-band (UWB) bioradar, we developed a method combining biomedical signal processing and space-frequency analysis to distinguish two stationary human subjects in different distances and to identify the location of each human subject. Experiments were done to evaluate the effectiveness of the proposed method. In 86 data sets the accuracy of distinguishing two stationary subjects reached 73%. This method may serve as a basis for further studies in developing appropriate 2-Dimension locating image reconstruction models via multi-antenna (static) UWB radar.

Study of the Ballistocardiogram signal in life detection system based on radar

In this article, our study of non-contact method via radar for monitoring the heart and respiratory rates of human subject is reported. The system is constructed which synchronously detects the electrocardiogram signals by the electrocardiograph and the ballistocardiogram signals by the non-contact life parameter detecting technology. Also, the detected signals are analyzed respectively in the time and frequency domain. The results show that the cycle of the ballistocardiogram is obvious in time domain and that the rhythm of the two kinds of signals keeps consistent. And their characteristic points in frequency domain are also the same. The clinical medicine usefulness of ballistocardiogram detected by the non-contact technology is approved and the credible evidence for the succeeding signal analysis and the clinical application is provided. Furthermore, the characters of the heartbeat signal detected by our system and the reasons for that are also discussed in detail in our paper.