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[Research on adaptive pulse signal extraction algorithm based on fingertip video image].

Jiangjun Yu1, Liang Zhou2, Zhaohui Liu2

  • 1Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, P.R.China;University of Chinese Academy of Sciences, Beijing 100049, P.R.China.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi
|February 26, 2020
PubMed
Summary

This study introduces an iterative algorithm to extract pulse signals from fingertip video, overcoming saturation distortion for accurate heart rate detection on smartphones.

Keywords:
heart rate detectionpulse signal extractionsmartphonevideo image processing

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Area of Science:

  • Biomedical Engineering
  • Digital Image Processing
  • Physiological Monitoring

Background:

  • Saturation distortion in fingertip video R-component affects pulse signal extraction.
  • Pulse signals often exhibit baseline drift and high-frequency noise.
  • Variations in fingertip pressure impact measurement accuracy.

Purpose of the Study:

  • To develop an algorithm for accurate pulse signal extraction from fingertip video.
  • To address saturation distortion and noise in physiological signals.
  • To evaluate the algorithm's performance across different smartphones and pressures for heart rate detection.

Main Methods:

  • An iterative threshold segmentation algorithm was developed to identify the region of interest for the R-component.
  • The gray mean value of the detected region was calculated to extract the pulse signal.
  • A zero-phase digital filter was designed to mitigate baseline drift and high-frequency noise.
  • Experiments were conducted using fingertip video images from various smartphones under different pressure conditions.

Main Results:

  • The proposed algorithm successfully extracted pulse signals by adaptively generating the region to be detected.
  • A zero-phase digital filter effectively removed noise and baseline drift from the pulse signal.
  • Comparative analysis showed the algorithm's robustness to varying fingertip pressures.
  • Experimental validation confirmed the algorithm's accuracy in heart rate detection.

Conclusions:

  • The developed iterative segmentation algorithm accurately extracts human heart rate information from fingertip video.
  • The algorithm demonstrates portability across different smartphone devices.
  • This research provides a theoretical foundation for smartphone-based physiological monitoring applications.