Novel fingertip image-based heart rate detection methods for a smartphone

Rifat Zaman, Chae Ho Cho, Konrad Hartmann-Vaccarezza, Tra Nguyen Phan, Gwonchan Yoon, Jo Woon Chong

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

We hypothesize that our smartphone-based fingertip image-based heart rate detection methods reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively.

Original languageEnglish
Article number358
JournalSensors (Switzerland)
Volume17
Issue number2
DOIs
StatePublished - Feb 12 2017

Keywords

  • Health monitoring
  • Heart rate detection
  • Smartphone discipline

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