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Low complexity heart rate measurement from wearable wrist-type photoplethysmographic sensors robust to motion artifacts

Boloursaz Mashhadi, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/ICASSP.2018.8461520
  3. Abstract:
  4. This paper presents a low complexity while accurate Heart Rate (HR) estimation technique from signals captured by Photoplethysmographic (PPG) sensors worn on the wrist during intensive physical exercise. Wrist-type PPG signals experience severe Motion Artifacts (MA) that hinder efficient HR estimation especially during intensive physical exercises. To suppress the motion artifacts efficiently, simultaneous 3 dimensional acceleration signals are used as reference MAs. The proposed method achieves an Average Absolute Error (AAE) of 1.19 Beats Per Minute (BPM) on the 12 benchmark PPG recordings in which subjects run at speeds of up to 15 km/h. This method also achieves an AAE of 2.17 BPM on the whole benchmark database of 23 recordings that include both running and arm movement activities. This performance is comparable with state-of-the-art algorithms while at a significantly reduced computational cost which makes its standalone implementation on wearable devices feasible. The proposed algorithm achieves an average processing time of 32 milliseconds per input frames of length 8 seconds (2 channel PPG and 3D ACC signals) on a 3.2 GHz processor. © 2018 IEEE
  5. Keywords:
  6. Realtime heart rate monitoring ; Wearable photoplethysmography (PPG) technology ; Wristbands and smartwatches
  7. Source: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 15 April 2018 through 20 April 2018 ; Volume 2018-April , 2018 , Pages 921-924 ; 15206149 (ISSN) ; 9781538646588 (ISBN)
  8. URL: https://ieeexplore.ieee.org/document/8461520