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Ultra wideband (UWB) Doppler radar has many biomedical applications, including remote diagnosis of cardiovascular disease, triage and real-time personnel tracking in rescue missions. It uses narrow pulses to probe the human body and detect tiny cardiopulmonary movements by spectral analysis of the backscattered electromagnetic (EM) field. With the help of super-resolution spectral algorithms, UWB radar is capable of increased accuracy for estimating vital signs such as heart and respiration rates in adverse signal-to-noise conditions. A major challenge for biomedical radar systems is detecting the heartbeat of a subject with high accuracy, because of minute thorax motion (less than 0.5 mm) caused by the heartbeat. The problem becomes compounded by EM clutter and noise in the environment. In this paper, we introduce a new algorithm based on the state space method (SSM) for the extraction of cardiac and respiration rates from UWB radar measurements. SSM produces range-dependent system poles that can be classified parametrically with spectral peaks at the cardiac and respiratory frequencies. It is shown that SSM produces accurate estimates of the vital signs without producing harmonics and inter-modulation products that plague signal resolution in widely used FFT spectrograms.

In this paper, we compare the performance of radar and optical (camera based) techniques in detecting vital signs such as respiratory rate (RR), heart rate (HR), and blood oxygen saturation (SpO2). Specifically, we investigate the application of ultrawideband stepped-frequency continuous-wave radar and imaging photoplethysmography (iPPG) techniques to measure vital signs. The radar performance can be enhanced by using phase information of backscattered signal instead of its amplitude. On the other hand, the iPPG system can be enhanced by using more than one camera and utilizing very selective narrowband filters coupled with good illumination. In either system, use of advanced signal processing is required to improve accuracy. Generally, HR and RR can be accurately read by either microwave radar or optical techniques with 500 lx illumination level to have < ±2% error up to 2 m distance between the subject and the system, but optical technique errors increase significantly to < ±15% for <200 lx. However, each system has its unique advantages as the radar can be used for seeing-through walls and optical technique is uniquely capable of measuring SpO2). [ABSTRACT FROM AUTHOR]

Ultra-wideband (UWB) pulse Doppler radars can be used for noncontact vital signs monitoring of more than one subject. However, their detected signals typically have low signal-to-noise ratio (SNR) causing significant heart rate (HR) detection errors, as the spurious harmonics of respiration signals and mixed products of respiration and heartbeat signals (that can be relatively higher than heartbeat signals) corrupt conventional fast Fourier transform spectrograms. In this paper, we extend the complex signal demodulation (CSD) and arctangent demodulation (AD) techniques previously used for accurately detecting the phase variations of reflected signals of continuous wave radars to UWB pulse radars as well. These detection techniques reduce the impact of the interfering harmonic signals, thus improving the SNR of the detected vital sign signals. To further enhance the accuracy of the HR estimation, a recently developed state-space method has been successfully combined with CSD and AD techniques and over 10 dB improvements in SNR is demonstrated. The implementation of these various detection techniques has been experimentally investigated and full error and SNR analysis of the HR detection are presented. [ABSTRACT FROM PUBLISHER]