Abstract

The combination of artificial intelligence (AI) and sensor systems enables many applications. This work shows an innovative solution to test the performance of smart Continuous Wave (CW) Doppler radar sensor system by investigating the mathematical models for receiving signals from different breathing disorder patients. CW radar sensor has many good features such as simple hardware structure, narrow bandwidth frequency, and high sensitivity in detecting the chest movement of humans remotely. Based on the developed berating theoretical models, data sets at different values of signal-to-noise ratio (SNR) are generated. The next step is to apply machine learning technique on this data set to categorize breathing disorder patterns. The results show the high potential application of smart radar sensor in diagnosing disorder sleeping problems.

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