Comparison of Region of Interest Segmentation Methods for Video-Based Heart Rate Measurements

Conventional contact photoplethysmography (PPG) sensors are not suitable in situations of skin damage or when unconstrained movement is required. As a consequence, remote photoplethysmography (rPPG) has recently emerged because it provides remote physiological measurements without expensive hardware...

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Bibliographic Details
Published in2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE) pp. 143 - 146
Main Authors Li, Peixi, Benezeth, Yannick, Nakamura, Keisuke, Gomez, Randy, Li, Chao, Yang, Fan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2018
Subjects
Face
Heart Rate (HR)
Heart rate measurement
Measurement
Region of Interest (ROI)
remote photoplethysmography (rPPG)
Signal to noise ratio
Skin
Videos
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Summary:Conventional contact photoplethysmography (PPG) sensors are not suitable in situations of skin damage or when unconstrained movement is required. As a consequence, remote photoplethysmography (rPPG) has recently emerged because it provides remote physiological measurements without expensive hardware and improves comfort for long term monitoring. RPPG estimation methods use the spatially averaged RGB values of pixels in a Region Of Interest (ROI) to generate a temporal RGB signal. The selection of ROI is a critical first step to obtain reliable pulse signals and must contain as many skin pixels as possible with a low percentage of non-skin pixels. In this paper, we experimentally compare seven ROI segmentation methods in the perspective of heart rate (HR) measurements with dedicated metrics. The algorithms are compared using our in-house database UBFC-RPPG, comprising of 53 videos specifically geared towards rPPG analysis.
ISSN:2471-7819
DOI:10.1109/BIBE.2018.00034