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Physiological Sensors

The Brain FM system ingests signals from multiple physiological monitoring modalities, collectively referred to as PPMs (Psychophysiological Monitors). Each modality captures a different window into the operator's cognitive and physiological state.

Modality Summary

Modality Signal Type Sensor Form Factor Sampling Rate Cognitive Relevance
EEG Electrical cortical activity Head-worn electrode cap/headset 250–500 Hz Direct neural correlate of workload, attention, fatigue
ECG Cardiac electrical activity Chest electrode patch 250 Hz HRV → autonomic stress and arousal
PPG / BVP Peripheral blood volume pulse Wrist wristband 64 Hz Heart rate, HRV → stress and load
Eye Gaze Gaze position on display Camera-based tracker 60–120 Hz Attentional allocation, situational awareness
Pupillometry Pupil diameter Same camera as gaze 60–120 Hz LC-NE arousal, cognitive effort
Speech Acoustic vocal features Microphone 16–44.1 kHz Para-linguistic stress and load markers

Invasiveness and Practicality

The modalities vary significantly in how intrusive they are to wear and operate. EEG provides the richest cognitive information - millisecond-resolution neural dynamics - but requires a head-worn device that is uncomfortable for long shifts and conspicuous in operational settings.

Speech is the most practical modality for voice-heavy environments: it requires only a microphone already present in the environment, produces no body-worn sensor burden, and is continuously available whenever the operator is communicating.

PPG offers a middle ground: a wristband is comfortable enough for all-day wear, and while the cognitive information content is lower than EEG, it provides reliable heart rate and HRV features that correlate with stress and workload.

Multimodal Combination

Combining multiple modalities improves prediction robustness:

  • EEG + PPG: Neural and autonomic signals are complementary; high workload increases both frontal theta power and sympathetic HRV markers.
  • EEG + Eye gaze: Neural and attentional signals together characterise situational awareness more completely than either alone.
  • Speech + EEG: Speech provides near-zero-overhead monitoring; EEG can be activated as a higher-fidelity backup during critical events.

See Multimodal Learning for the technical approach to combining modalities.

Data Availability by Modality

The Brain FM's cross-modal alignment strategy directly addresses the availability imbalance:

Modality Public Pre-training Data Status
EEG > 30,000 hours (TUH EEG Corpus) Large-scale SSL possible
ECG Clinical archives; moderate SSL feasible
PPG Sparse cognitive datasets Needs cross-modal alignment
Eye gaze Very sparse Needs cross-modal alignment
Speech Large general ASR corpora (not physiological) Domain gap issue