Δ.72 Wearable Exam Stress Validation Report: Field Equation Verification and Biological Coherence Analysis
Description
This report presents an empirical validation of the Δ.72 field equation within a real-world physiological dataset measuring stress responses in students during examination periods. The Δ.72 model posits that coherence within biological systems arises from dynamic alignment between internal variability, environmental fields, and phase-synchronized information flow. Using the publicly available Wearable Exam Stress Dataset for Predicting Cognitive Performance in Real-World Settings (PhysioNet, Version 1.0.0), this study tests whether measurable alignment (A), phase coherence (λ), and emergent output (E) follow the theoretical relationships predicted by the Δ.72 equation. Results show statistically significant coupling between field alignment and emergent coherence, supporting the model’s claim that adaptive, not rigid, synchrony underlies systemic health.
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Additional details
Related works
- Cites
- Publication: 10.3389/fpubh.2017.00258 (DOI)
- Publication: 10.1038/35067550 (DOI)
- Publication: 10.1109/TITS.2005.848368 (DOI)
- Is derived from
- Dataset: 10.5281/zenodo.3823418 (DOI)
Dates
- Submitted
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2025-10-08Official public release on Zenodo
References
- Abedi, A., Jiang, Y., Chen, L., Alghowinem, S., & Calvo, R. A. (2020). A Wearable Exam Stress Dataset for Predicting Cognitive Performance in Real-World Settings (Version 1.0.0) [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.3823418
- Healey, J. A., & Picard, R. W. (2005). Detecting stress during real-world driving tasks using physiological sensors. IEEE Transactions on Intelligent Transportation Systems, 6(2), 156–166. https://doi.org/10.1109/TITS.2005.848368
- Shaffer, F., & Ginsberg, J. P. (2017). An Overview of Heart Rate Variability Metrics and Norms. Frontiers in Public Health, 5, 258. https://doi.org/10.3389/fpubh.2017.00258
- Varela, F. J., Lachaux, J. P., Rodriguez, E., & Martinerie, J. (2001). The brainweb: Phase synchronization and large-scale integration. Nature Reviews Neuroscience, 2(4), 229–239. https://doi.org/10.1038/35067550