• DocumentCode
    3603801
  • Title

    Motion Noise Cancelation in Heartbeat Sensing using Accelerometer and Adaptive Filter

  • Author

    Ardalan, Shahab ; Moghadami, Siavash ; Jaafari, Samira

  • Author_Institution
    Dept. of Electr. Eng., San Jose State Univ., San Jose, CA, USA
  • Volume
    7
  • Issue
    4
  • fYear
    2015
  • Firstpage
    101
  • Lastpage
    104
  • Abstract
    This letter focuses on suppressing the motion artifact of wrist photoplethysmographic heart rate signals using an accelerometer based adaptive filter. Monitoring of the heart signal can offer important insights with regard to health and wellness. The objective of the experiment conducted here is to recover the distorted signal resulting from body movement while measuring the heart rate signal noninvasively from the wrist. The class of filters, known as adaptive filters, that can extract meaningful information from the distorted signal, used predetermined initial conditions to equalize the signal distortion due to motion. Adaptive filters of least mean-square (LMS), Kalman filter, and recursive least-squares (RLS) were used in this study to recover the distorted heart rate signal. This study also presented a comparison on utilized filters that can be used for recovering of the heart rate signal.
  • Keywords
    accelerometers; adaptive Kalman filters; cardiology; feature extraction; least mean squares methods; medical signal processing; photoplethysmography; recursive estimation; Kalman filter; LMS; RLS; accelerometer; adaptive filter; heartbeat sensing; information extraction; least mean-square; motion noise cancelation; recursive least-squares; wrist photoplethysmographic heart rate signals; Adaptive filters; Body sensor networks; Heart rate; Kalman filters; Least squares approximations; Photoplethysmography; Wearable computers; Body sensors; health; heart rate signal; photoplethysmography; vital signs; wearable;
  • fLanguage
    English
  • Journal_Title
    Embedded Systems Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1943-0663
  • Type

    jour

  • DOI
    10.1109/LES.2015.2457933
  • Filename
    7161281