Contactless sensing of human respiratory movement using UWB radio - Cheng, You. (2011)
This report describes an automatic technique that can locate the desired detection region automatically and accurately without being realized the distance between the test subject and the antennas and a multi-peak detection technique of respiratory rate and amplitude using wireless low-power ultra wideband impulse radio (UWB-IR). The accurate detection of respiratory rate and amplitude are crucial for the assessment of obstructive sleep apnea syndrome (OSAS) and respiration training/therapy of spinal cord injury (SCI) patients. Since the displacement of human chest movement is linearly related to the disposition of backscattered radio signal reflected by human chest, both the chest respiration rate and amplitude can be measured using UWB radio. However, the imperfections in software design can limit the detection capacity of this system and therefore affect the overall performance of UWB system. Consequently, the accurate detection of back-scattering region is urgent. By examining the differences between each data waveform and the rest data waveforms, back-scattering region can be revealed approximately. When utilizing all these differences in a proper way, the location can be very precise. In the other hand, similar to any other wireless system, the accuracy of UWB-IR measurement is limited by the received signal-to-noise ratio at the receiver. The proposed multi-peak detection technique is able to improve the received signal-to-noise ratio (SNR) in a way that is similar to the matched filtering effect. The primary idea of multi-peak detection is to shift–and-add the sub-peaks of the received UWB-IR signal to the main peak. This is possible because the time locations of the sub peaks of the received UWB impulse, relative to the main peak time location, are known a-priori, assuming that these peak locations remains unchanged after propagation through the channel. Based on the experiment results, the SNR obtained using multi peak detection is found to be higher than the SNR obtained using single-peak detection by approximately 2.44 dB.