Abstract
We present a novel respiratory sounds monitoring concept based on compressive sensing (CS). Respiratory sounds are streamed from a body-worn sensor node to a smartphone where processing is conducted. CS is used to simultaneously lower sampling frequency on the sensor node and over-the-air data rate. In this study we emphasize compressed sensing reconstruction via orthogonal matching pursuit (OMP) on Android smartphone. Accuracy of the reconstruction and execution speed are investigated using synthetic signals. We demonstrate applicability of the technique in real-time reconstruction of at least 10 components of compressible DCT spectrum of respiratory sounds containing asthmatic wheezing, acquired at 4x lower sampling rate.
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© 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Oletic, D., Skrapec, M., Bilas, V. (2013). Monitoring Respiratory Sounds: Compressed Sensing Reconstruction via OMP on Android Smartphone. In: Godara, B., Nikita, K.S. (eds) Wireless Mobile Communication and Healthcare. MobiHealth 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 61. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37893-5_13
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DOI: https://doi.org/10.1007/978-3-642-37893-5_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37892-8
Online ISBN: 978-3-642-37893-5
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