| Autor: |
Wickramasuriya DS, Faghih RT |
| Jazyk: |
angličtina |
| Zdroj: |
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2019 Jul; Vol. 2019, pp. 599-602. |
| DOI: |
10.1109/EMBC.2019.8857917 |
| Abstrakt: |
Determining the relationship between neurocognitive stress and changes in physiological signals is an important aspect of wearable monitoring. We present a state-space approach for tracking stress from skin conductance and electrocardiography measurements. Individual skin conductance responses (SCRs) are a primary source of information in a skin conductance signal and their rate of occurrence is related to psychological arousal. Likewise, heart rate too varies with emotion. We model SCRs and heartbeats as two different stress-related point processes linked to the same sympathetic nervous system activation. We derive Kalman-like filter equations for tracking stress and use both expectation-maximization and maximum likelihood estimation for parameter recovery. Our preliminary results show that stress is high when a task is unfamiliar, but reduces gradually with familiarity, albeit in the presence of other external stressors. The method demonstrates the feasibility of tracking real-world stress using skin conductance and heart rate measurements. It also serves as a novel state estimation framework for multiple point process observations on different time scales. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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