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Real-time Stress Assessment Through PPG Sensor for VR Biofeedback

Utkarsh Chauhan; Norbert Reithinger; John R. Mackey
In: Proceedings of the 20th International Conference on Multimodal Interaction: Adjunct. ACM International Conference on Multimodal Interaction (ICMI-2018), October 16-20, Boulder, CO, USA, Pages 5:1-5:5, ICMI '18, ISBN 978-1-4503-6002-9, ACM, 2018.


Existing stress measurement methods, including cortisol measurement, blood pressure monitoring, and psychometric testing, are invasive, impractical, or intermittent, limiting both clinical and biofeedback utility. Better stress measurement methods are needed for practical, widespread application. For the project ViRST, where we use a Virtual Reality (VR) environment controlled by a speech dialog system to provide chronic pain relief, we designed a novel stress biofeedback system. Our prototype employs an ear-clip Photoplethysmogram (PPG) sensor, an Arduino microcontroller, and a supervised learning algorithm. To acquire a training dataset, we ran stress induction experiments on 10 adult subjects aged 30-58 to track Heart Rate Variability (HRV) metrics and Discrete Wavelet Transform (DWT) coefficients. We trained an AdaBoost ensemble classifier to 93% 4-fold crossvalidation accuracy and 93% precision. We outline future work to better suit a VR environment and facilitate additional modes of interaction by simplifying the human interface.


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