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Non-contact in-car monitoring of heart rate: evaluating the eulerian video magnification algorithm in a driving simulator study
Citation Link: https://doi.org/10.15480/882.14167
Publikationstyp
Conference Paper
Date Issued
2024-09
Sprache
English
TORE-DOI
Start Page
651
End Page
654
Citation
Proceedings of Mensch und Computer 2024: 651-654
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
Association for Computing Machinery
ISBN
979-8-4007-0998-2
Peer Reviewed
true
Monitoring drivers' health is crucial for saving lives in emergencies and enabling in-car health applications. The state of the art in pulse monitoring is contact-based sensors which impair the driving experience and have to be applied manually before driving. This paper focuses on automated hyper parameter optimizing the Eulerian Video Magnification (EVM) algorithm, which detects heart rates through non-contact facial camera images, for use in driving scenarios. We conducted a user study where 21 participants performed a driving simulation while their heart rates were recorded by a wearable fitness tracker (serving as ground truth) and facial images with an RGB camera. Our findings indicate that, despite using the optuna library for hyper parameter tuning, the Eulerian Video Magnification algorithm is insufficient for accurate pulse detection in a driving simulator environment.
Subjects
Automotive Health | Driving Simulator | Eulerian Video Magnification | Heart Rate | User Study
DDC Class
006: Special computer methods
Publication version
publishedVersion
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Name
3670653.3677493.pdf
Type
Main Article
Size
1.87 MB
Format
Adobe PDF