| Summary: | 碩士 === 國立清華大學 === 通訊工程研究所 === 101 === This paper presents a ultra-wideband (UWB) impulse-radio radar signal processing platform. This platform is integrated with a front-end radar chip for human respiratory feature extraction and signal compression. The conventional radar detection algorithms only extract the respiration rate for medical diagnosis. However, there is more information in the radar-detected respiratory signals which can be useful for medical diagnosis. Thus, this study proposed a modified raised cosine model and an iterative correlation algorithm to extract more respiratory features, such as inspiration and expiration speed, respiration intensity, and respiration holding ratio. Moreover, the extracted features are useful in remote medical monitoring system since they can be seen as compressed respiratory signals. Transmission bandwidth can be saved by transmitting the extracted features instead of lots of sampled data. The proposed algorithm and architecture is designed and implemented on a radar signal processing platform with the ARM processor and FPGA logic array. Human respiratory signals of 0.1 to 1 Hz rate are detected and analyzed along with other information at each period.
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