Prototype of respiratory sounds monitoring system based on compressive sampling

Abstract

In this study we demonstrate end-to-end prototype of the respiratory sounds monitoring m-health system based on compressive sampling (CS). We show a low power implementation of the involved pseudorandom sampling on the wearable wireless acoustic sensor featuring a 16-bit microcontroller and Bluetooth radio chip. CS reconstruction using the orthogonal matching pursuit (OMP) reconstruction algorithm was implemented on the Android smartphone.We measure network datarate reduction in comparison with associated reconstruction accuracy of compressible DCT spectrum on synthetically generated harmonic signals and prerecorded respiratory sounds containing asthmatic wheezing.