A Novel Filter for Tracking Real-World Cognitive Stress using Multi-Time-Scale Point Process Observations

Dilranjan S. Wickramasuriya, Rose T. Faghih

    Research output: Contribution to journalArticlepeer-review

    Abstract

    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.

    Original languageEnglish (US)
    Pages (from-to)599-602
    Number of pages4
    JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
    Volume2019
    DOIs
    StatePublished - Jul 1 2019

    ASJC Scopus subject areas

    • Signal Processing
    • Biomedical Engineering
    • Computer Vision and Pattern Recognition
    • Health Informatics

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