• DocumentCode
    591165
  • Title

    Asynchronous ECG time sampling: Saving bits with Golomb-Rice encoding

  • Author

    Marisa, Thanks ; Niederhauser, Thomas ; Haeberlin, Andreas ; Goette, Josef ; Jacomet, Marcel ; Vogel, Rolf

  • Author_Institution
    HuCE-microLab., Bern Univ. of Appl. Sci., Biel, Switzerland
  • fYear
    2012
  • fDate
    9-12 Sept. 2012
  • Firstpage
    61
  • Lastpage
    64
  • Abstract
    We present a technique for online compression of ECG signals using the Golomb-Rice encoding algorithm. This is facilitated by a novel time encoding asynchronous analog-to-digital converter targeted for low-power, implantable, long-term bio-medical sensing applications. In contrast to capturing the actual signal (voltage) values the asynchronous time encoder captures and encodes the time information at which predefined changes occur in the signal thereby minimizing the sensor´s energy use and the number of bits we store to represent the information by not capturing unnecessary samples. The time encoder transforms the ECG signal data to pure time information that has a geometric distribution such that the Golomb-Rice encoding algorithm can be used to further compress the data. An overall online compression rate of about 6 times is achievable without the usual computations associated with most compression methods.
  • Keywords
    analogue-digital conversion; data compression; electrocardiography; encoding; medical signal processing; signal sampling; Golomb-Rice encoding algorithm; actual signal voltage values; asynchronous ECG time sampling; asynchronous time encoder capturing; data compression; geometric distribution; low-power implantable long-term biomedical sensing applications; novel time encoding asynchronous analog-to-digital converter; online ECG signal compression; online compression rate; sensor energy use; time information; Educational institutions; Electrocardiography; Encoding; Heart beat; Memory management; Signal resolution; Surface waves;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing in Cardiology (CinC), 2012
  • Conference_Location
    Krakow
  • ISSN
    2325-8861
  • Print_ISBN
    978-1-4673-2076-4
  • Type

    conf

  • Filename
    6420330