Heart and Respiratory Rate Extraction from a Single Audio-based Monitoring System using Wavelet and Hilbert Transforms

Audio-based health monitoring systems have gained traction for its capability in capturing different physiological target signals and holding features relevant in diagnosis and treatment, making it a feasible form of data acquisition in biomedical signal processing and feature extraction. Acquiring audio for both heart and respiratory sounds for rate estimation was accomplished using the bottom microphone of the Google Pixel 6A from the trachea and anterior left. A direct comparison of the filter-Hilbert and wavelet-Shannon algorithms based on literature with modifications catering to the application of this study was done to measure their performance and reliability against the KardiaMobile 6L EKG. Tests done were able to show good accuracy for both algorithms on heart rate calculations on both the trachea and anterior left, satisfying having less than ± 10 BPM difference from control. Tests for respiratory rate only provided promising results of less than ± 5 CPM difference from control for tracheal recordings,