Non-contact Breathing and Heartbeat signals monitoring using FMCW radar
Non-contact breathing and heartbeat signals monitoring are the tasks of extracting them without contact sensors. It became even more critical in COVID 19, and hence it is crucial to estimate them correctly. FMCW (Frequency Modulated Continuous Wave) radar is employed to estimate these two signals without contact. Radar captures chest displacement and body movement. Because of this, breathing and heartbeat signals are distorted. The reduction of false peaks and peak estimation is crucial for breathing rate calculation. So in this thesis, firstly, we propose a novel way for tracing body movement and eliminating the traced segment for breathing and heart rate calculation. In the second part, we efficiently reduced false peaks using maximal overlap discrete wavelet transform (MODWT) to decompose and reconstruct the filtered breathing signal for estimating breathing rate. The heartbeat signal is estimated using bandpass filtering of unwrapped phase. We also compared our algorithm with the task force monitoring (TFM) device as a reference and discussed its performance. Also, our proposed method for breathing rate estimation has an accuracy of 92.43% and heartrate estimation it is 85.16%.