AwareOne: A Wrist System for Daily Stress Monitoring using Mid-Level Physiological Fusion and Late-Fusion with Survey-Based Labels

Background: Multi-sensor fusion can improve daily stress monitoring. Methods: A wrist-worn device includes a system of the Galvanic Skin Response (GSR), PPG-derived Heart Rate Variability (HRV), skin temperature, and SpO₂, paired with self-reported questionnaires. The device streams data to a mobile app over Bluetooth Low Energy and updates the UI within 1-2 seconds. The physiological features are taken within a fixed window around each questionnaire time and performs a mid-level fusion; late fusion is also evaluated with self-reports. Results: Against a commercial reference device, AwareOne achieved a mean absolute error of 0.23 for SpO₂ and 4.94 for BPM in a one-day benchmark session. The system was validated through a technical evaluation using representative inputs and simulated survey labels. A Support Vector Machine algorithm reached a mean squared error of 0.08 on stress prediction. Temperature showed to have the strongest correlation with simulated stress levels at −0.43, followed by Heart Rate Variability (HRV) at 0.36, while SpO₂ had negligible correlation at 0.09 in the current dataset. Conclusion: The system integrates multi-sensing, on device preprocessing, BLE transmission, and a clear fusion workflow that creates a useful predictive performance of daily stress monitoring.