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Heart rate detection from the supratrochlear vessels using a virtual reality headset integrated PPG sensor.

Gnacek, M., Garrido-Leal, D., Nieto Lopez, R., Mavridou, I., Seiss, E., Kostoulas, T., Balaguer-Ballester, E. and Nduka, C., 2020. Heart rate detection from the supratrochlear vessels using a virtual reality headset integrated PPG sensor. In: 1st International Workshop on Multimodal Affect and Aesthetic Experience on ICMI 2020: 22nd ACM International Conference on Multimodal Interaction, 25-29 October 2020, Utrecht, the Netherlands.

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Official URL: https://icmi.acm.org/2020/index.php?id=workshops

Abstract

An increasing amount of virtual reality (VR) research is carried out to support the vast number of applications across mental health, exercise and entertainment fields. Often, this research involves the recording of physiological measures such as heart rate recordings with an electrocardiogram (ECG). One challenge is to enable remote, reliable and unobtrusive VR and heart rate data collection which would allow a wider application of VR research and practice in the field in future. To address the challenge, this work assessed the viability of replacing standard ECG devices with a photoplethysmography (PPG) sensor that is directly integrated into a VR headset over the branches of the supratrochlear vessels. The objective of this study was to investigate the reliability of the PPG sensor for heart-rate detection. A total of 21 participants were recruited. They were asked to wear an ECG belt as ground truth and a VR headset with the embedded PPG sensor. Signals from both sensors were captured in free standing and sitting positions. Results showed that VR headset with an integrated PPG sensor is a viable alternative to an ECG for heart rate measurements in optimal conditions with limited movement. Future research will extend on this finding by testing it in more interactive VR settings.

Item Type:Conference or Workshop Item (Lecture)
Group:Faculty of Science & Technology
ID Code:34761
Deposited By: Symplectic RT2
Deposited On:02 Nov 2020 11:55
Last Modified:14 Mar 2022 14:24

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