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Cited by 126Non-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlEmotion and Mood Recognition

The DOI matches its Crossref record; 40 of the 42 references it cites were found in a registry or an index.

Algorithms for Monitoring Heart Rate and Respiratory Rate From the Video of a User’s Face

Open access
Sanyal, Shourjya, Nundy, Koushik Kumar·2018·IEEE Journal of Translational Engineering in Health and Medicine
DOI 10.1109/jtehm.2018.2818687PMC PMC5957265
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Abstract

. In this pilot study, we have introduced a novel iPPG method where by measuring variations in color of reflected light, i.e., Hue, and can therefore measure both HR and respiratory rate (RR) from the video of a subject's face. This paper was performed on 25 healthy individuals (Ages 20-30, 15 males and 10 females, and skin color was Fitzpatrick scale 1-6). For each subject we took two 20 second video of the subject's face with minimal movement, one with flash ON and one with flash OFF. While recording the videos we simultaneously measuring HR using a Biosync B-50DL Finger Heart Rate Monitor, and RR using self-reporting. This paper shows that our proposed approach of measuring iPPG using Hue (range 0-0.1) gives more accurate readings than the Green channel. HR/Hue (range 0-0.1) ([Formula: see text], [Formula: see text]-value = 4.1617, and RMSE = 0.8887) is more accurate compared with HR/Green ([Formula: see text], [Formula: see text]-value = 11.60172, and RMSE = 0.9068). RR/Hue (range 0-0.1) ([Formula: see text], [Formula: see text]-value = 0.2885, and RMSE = 3.8884) is more accurate compared with RR/Green ([Formula: see text], [Formula: see text]-value = 0.5608, and RMSE = 5.6885). We hope that this hardware agnostic approach for detection of vital signals will have a huge potential impact in telemedicine, and can be used to tackle challenges, such as continuous non-contact monitoring of neo-natal and elderly patients. An implementation of the algorithm can be found at https://pulser.thinkbiosolution.com.

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Research works printed but not linked: 7

  1. 2016, RGB to HSL Color Conversion
  2. 2016, OpenCV Library
  3. 2016, Instant Heart Rate by Azumio Inc
  4. 2016, Fitbit
  5. 2016, Kinsa Smart Thermometer
  6. 2018, Vital Signs (Body Temperature Pulse Rate Respiration Rate Blood Pressure) Johns Hopkins Medicine Health Library
  7. 2016, CMS50DL Pulse Oximeter User Manual

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Metadata

Authors
Sanyal, S., & Nundy, K. K.
ORCID
Venue
IEEE Journal of Translational Engineering in Health and Medicine
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2018
Volume
6
Pages
1-11
ISSN
2168-2372 (ISSN-L)
DOI
10.1109/jtehm.2018.2818687
PMC
PMC5957265
OpenAlex
W2797516094
Cited by
125
References
42
Citations by year
2026: 8 · 2025: 12 · 2024: 13 · 2023: 16 · 2022: 19 · 2021: 26 · 2020: 16 · 2019: 14 · 2018: 1
FWCI
5.70
Type
journal article
Language
en
Open access
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/OAPA.html (vor)
Locations
  • IEEE Journal of Translational Engineering in Health and Medicine (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
  • Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Keywords
photoplethysmography, heart rate monitoring, respiratory rate estimation, facial video, hue, green channel, non-contact vital sign monitoring, telemedicine, neonatal monitoring, elderly patients

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