Night Watch

Detecting Nocturnal Stress and Autonomic Drift

NightWatch is an ongoing research project studying overnight physiological changes to detect early signs of stress, fatigue, and autonomic imbalance during sleep.

By analyzing data from Apple Watch (HRV, HR trend, SpO₂, movement) and Muse S EEG headband, the project focuses on the 3–6 a.m. window, when sympathetic activity peaks and cardiac events are most common.

The goal is to design a wearable-based system that provides early insight into stress vulnerability before it manifests the next day.

Research Goals

Identify HRV, HR slope, and SpO₂ patterns that indicate pre-stress or autonomic drift during sleep.
Integrate EEG alpha/theta arousal detection for neural validation of stress response.
Build a multi-sensor Early Warning Index (EWI) combining cardiovascular, respiratory, and neural data.
Correlate physiological metrics with self-reported next-day mood and alertness.
Create a visual NightWatch Report summarizing sleep-stage risk markers and recovery scores.

Research Goals

Imported and aligned Apple HealthKit and Muse EEG data streams, accounting for time drift and sampling differences.
Processed HRV signals (RMSSD, SDNN, pNN50) with artifact filtering and motion masking for higher accuracy.
Calculated SpO₂ desaturation metrics (depth, duration, recovery) to measure respiratory stability.
Extracted EEG micro-arousals and integrated them with HRV and HR slope data to visualize autonomic-neural coupling.
Developed multi-night visualization dashboards highlighting pre-wake autonomic drift trends.
Currently testing threshold tuning and rolling baseline models for a predictive Early Warning Index (EWI).

Ongoing Activity

Conducting multi-week data collection with Apple Watch and Muse S to validate pattern consistency.
Refining the EWI algorithm for better correlation with next-day self-assessment surveys.
Expanding the dataset to include sleep quality and fatigue questionnaires.
Preparing data plots and a graphical abstract for a poster and upcoming research presentation.
Drafting a research paper (2025) documenting findings on early detection of nocturnal stress patterns.

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