Non-Contact HR Monitoring via Smartphone and Webcam during Different Respiratory Maneuvers and Body Movements

Monay Mokhtar Shoushan, Bersain Alexander Reyes, Aldo Mejia Rodriguez, Jo Woon Chong

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

As a reliable indicator for individual's healthiness conditions, heart rate (HR) has been widely considered and used. Imaging photoplethysmography (iPPG) is recently highlighted as a promising HR measurement method, due to its non-contact characteristics, by extracting the HR from facial video recordings. In this study, we propose a camera-based HR monitoring technique that estimates HR information from iPPG signals extracted from a video sequence. Videos were recorded using a smartphone or a laptop camera. We adopted the plane-orthogonal-to-skin (POS) method to compute iPPG. The proposed method is evaluated by applying it to extract HR of 9 subjects at rest and during two motion conditions (lateral and frontal) while they were performing several respiratory maneuvers-spontaneous, metronome, and forced. Automatic face detection algorithms were implemented in the proposed method. Our experimental results show that mean values of HR have 0.56% error and 99.4% accuracy when compared to HR calculated from the gold-standard electrocardiography (ECG) reference in diverse conditions of motions and respiratory maneuvers.

Original languageEnglish
Article number9103223
Pages (from-to)602-612
Number of pages11
JournalIEEE Journal of Biomedical and Health Informatics
Volume25
Issue number2
DOIs
StatePublished - Feb 2021

Keywords

  • Breathing maneuvers
  • biomedical monit-oring
  • heart rate and variability
  • imaging photoplet-hysmography

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