A real-time heart rate estimation framework based on a facial video while wearing a mask.
Technol Health Care
; 2022 Nov 17.
Article
in English
| MEDLINE | ID: covidwho-2318785
ABSTRACT
BACKGROUND:
The imaging photoplethysmography (iPPG) method is a non-invasive, non-contact measurement method that uses a camera to detect physiological indicators. On the other hand, wearing a mask has become essential today when COVID-19 is rampant, which has become a new challenge for heart rate (HR) estimation from facial videos recorded by a camera.OBJECTIVE:
The aim is to propose an iPPG-based method that can accurately estimate HR with or without a mask.METHODS:
First, the facial regions of interest (ROI) were divided into two sub-ROIs, and the original signal was obtained through spatial averaging with different weights according to the result of judging whether wearing a mask or not, and the CDF, which emphasizes the main component signal, was combined with the improved POS suitable for real-time HR estimation to obtain the noise-removed BVP signal.RESULTS:
For self-collected data while wearing a mask, MAE, RMSE, and ACC were 1.09 bpm, 1.44 bpm, and 99.08%, respectively.CONCLUSION:
Experimental results show that the proposed framework can estimate HR stably in real-time in both cases of wearing a mask or not. This study expands the application range of HR estimation based on facial videos and has very practical value in real-time HR estimation in daily life.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Language:
English
Journal subject:
Biomedical Engineering
/
Health Services
Year:
2022
Document Type:
Article
Affiliation country:
THC-220322
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