Wireless Mobile Communication and Healthcare. Third International Conference, MobiHealth 2012, Paris, France, November 21-23, 2012, Revised Selected Papers

Research Article

Monitoring Respiratory Sounds: Compressed Sensing Reconstruction via OMP on Android Smartphone

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  • @INPROCEEDINGS{10.1007/978-3-642-37893-5_13,
        author={Dinko Oletic and Mateja Skrapec and Vedran Bilas},
        title={Monitoring Respiratory Sounds: Compressed Sensing Reconstruction via OMP on Android Smartphone},
        proceedings={Wireless Mobile Communication and Healthcare. Third International Conference, MobiHealth 2012, Paris, France, November 21-23, 2012, Revised Selected Papers},
        proceedings_a={MOBIHEALTH},
        year={2013},
        month={4},
        keywords={asthma m-health compressive sensing orthogonal matching pursuit smartphone Android},
        doi={10.1007/978-3-642-37893-5_13}
    }
    
  • Dinko Oletic
    Mateja Skrapec
    Vedran Bilas
    Year: 2013
    Monitoring Respiratory Sounds: Compressed Sensing Reconstruction via OMP on Android Smartphone
    MOBIHEALTH
    Springer
    DOI: 10.1007/978-3-642-37893-5_13
Dinko Oletic1,*, Mateja Skrapec1,*, Vedran Bilas1,*
  • 1: University of Zagreb
*Contact email: dinko.oletic@fer.hr, mateja.skrapec@fer.hr, vedran.bilas@fer.hr

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.