Real-time stress assessment through PPG sensor for VR biofeedback
| Autor: | Utkarsh Chauhan, John R. Mackey, Norbert Reithinger |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Discrete wavelet transform
business.industry Computer science 030503 health policy & services medicine.medical_treatment Wavelet transform Virtual reality Biofeedback computer.software_genre 03 medical and health sciences 0302 clinical medicine Photoplethysmogram medicine 030212 general & internal medicine AdaBoost Dialog system 0305 other medical science business computer Simulation Digital signal processing |
| Zdroj: | ICMI (adjunct) |
| Popis: | 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 cross-validation 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. |
| Databáze: | OpenAIRE |
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