PSCS: A Physiological Sound Compression System Based on Compressive Sensing with Self-Adaptive Compression Ratio and Optimized DCT

Continuous physiological sound monitoring is crucial for the prevention, diagnosis, and treatment of various diseases like cardiopulmonary and gastrointestinal conditions. Wearable healthcare sensors have emerged as a potent solution, streamlining the capture, storage, transmission, and analysis of individualized physiological sounds. However, challenges exist including large data volumes, limited hardware computational capabilities, and constrained transmission bit rates. To address these issues, we propose a physiological sound compression system using compressive sensing with self-adaptive compression ratio across sound types to implement physiological sound compression and Optimized Discrete Cosine Transform (ODCT) reconstruction to reduce loss in effective bands. Evaluated on SPRSound and PhysioNet 2016, our approach attains correlation coefficients of 0.863 and 0.883 for respiratory and cardiac sounds, with -3.14 dB and -1.84 dB signal-to-noise ratio loss at 3.5 and 3.0 compression ratios. Implemented on a custom healthcare sensor, our approach optimizes bit rate to 1.73× and power consumption to 0.82× compared to the uncompressed system.