Sensor Integration Module - Abstract Documentation

Purpose and Responsibility

Provides comprehensive integration framework for external physiological and biometric sensors including EEG, GSR, eye-tracking, heart rate, and other research-grade measurement devices. Enables multi-modal data collection with precise timestamp synchronization and real-time quality monitoring.

Key Data Structures and Relationships

Core Sensor Architecture

  • SensorSession: Complete multi-sensor recording session with synchronized data streams
  • SensorConfig: Individual sensor configuration and calibration parameters
  • SensorReading: Individual sensor measurements with timestamp and quality metrics
  • DataQuality: Real-time assessment of signal quality and measurement reliability

Sensor Type Hierarchy

  • EEG: Multi-channel brain activity recording with configurable montages
  • GSR: Galvanic skin response for autonomic arousal measurement
  • EyeTracking: Gaze position and pupil diameter monitoring
  • HeartRate: Cardiac rhythm and heart rate variability analysis
  • Environmental: Temperature, accelerometer, blood pressure monitoring

Synchronization Framework

  • SyncEvent: Cross-modal timestamp anchoring for data alignment
  • CalibrationData: Sensor-specific calibration parameters and drift correction
  • ConnectionType: USB, Bluetooth, WiFi, and custom protocol support

Main Data Flows and Transformations

Data Collection Pipeline

  1. Sensor Discovery: Automatic detection and configuration of available sensors
  2. Calibration Process: Individual sensor calibration and baseline establishment
  3. Synchronized Recording: Multi-modal data collection with microsecond timestamp precision
  4. Quality Monitoring: Real-time signal quality assessment and artifact detection

Processing Pipeline

  1. Artifact Detection: Automatic identification of movement artifacts and signal noise
  2. Signal Filtering: Real-time digital filtering for noise reduction
  3. Feature Extraction: Time-domain and frequency-domain feature computation
  4. Data Validation: Missing data detection and quality assessment

Export Pipeline

  • Raw Data: Unprocessed sensor streams with full temporal resolution
  • Processed Features: Computed metrics and derived measurements
  • Synchronized Datasets: Multi-modal data aligned to common timeline
  • Quality Reports: Comprehensive data quality assessment and validation

External Dependencies and Interfaces

Hardware Integration

  • EEG Systems: Biosemi, Brain Products, Emotiv, OpenBCI compatibility
  • Eye Trackers: Tobii, SR Research, Pupil Labs integration
  • GSR Devices: Biopac, iMotions, Shimmer sensor support
  • Custom Protocols: Extensible framework for proprietary sensor systems

Communication Protocols

  • USB Integration: High-speed data transfer with low latency
  • Wireless Protocols: Bluetooth LE, WiFi, and custom RF communication
  • Network Streaming: Real-time data streaming over TCP/IP and UDP
  • Serial Communication: RS-232 and custom serial protocol support

Platform Support

  • Cross-Platform: Windows, macOS, Linux sensor driver integration
  • Real-time Systems: Low-latency data collection with priority scheduling
  • Mobile Platforms: iOS and Android sensor integration where applicable

State Management Patterns

Sensor Lifecycle Management

Discovery → Configuration → Calibration → Recording → Quality Assessment → Export

Multi-Sensor Coordination

  • Synchronization: Master clock coordination across multiple sensor streams
  • Error Recovery: Graceful handling of individual sensor failures
  • Resource Management: CPU and bandwidth allocation across sensor channels

Data Integrity

  • Buffer Management: Circular buffers with overflow protection
  • Timestamp Validation: Clock synchronization and drift correction
  • Missing Data: Gap detection and interpolation strategies

Core Algorithms and Business Logic Abstractions

Signal Processing

  • Digital Filtering: Real-time IIR and FIR filter implementation
  • Artifact Rejection: Statistical and template-based artifact identification
  • Baseline Correction: Drift correction and baseline restoration
  • Frequency Analysis: Real-time spectral analysis and band power computation

EEG-Specific Processing

  • Channel Montaging: Flexible electrode configuration and re-referencing
  • Impedance Monitoring: Real-time electrode contact quality assessment
  • Event-Related Analysis: Stimulus-locked averaging and time-frequency analysis
  • Connectivity Analysis: Coherence and phase synchronization measurement

Eye-Tracking Analysis

  • Gaze Estimation: Pupil detection and gaze vector computation
  • Saccade Detection: Rapid eye movement identification and classification
  • Fixation Analysis: Stable gaze period detection and duration measurement
  • Pupil Response: Pupil diameter changes and cognitive load estimation

Physiological Monitoring

  • Heart Rate Variability: R-R interval analysis and autonomic assessment
  • GSR Analysis: Skin conductance level and response detection
  • Movement Analysis: Accelerometer data processing for motion artifacts
  • Environmental Correlation: Temperature and environmental factor integration

Performance Considerations

  • Real-time Processing: Sub-millisecond latency for time-critical applications
  • High-Throughput: Support for high sampling rates (up to 20kHz+) across multiple channels
  • Memory Management: Efficient buffering for long recording sessions
  • CPU Optimization: Multi-threaded processing with SIMD acceleration where applicable

Quality Assurance and Validation

Data Quality Metrics

  • Signal-to-Noise Ratio: Real-time SNR calculation and monitoring
  • Artifact Contamination: Percentage of data affected by artifacts
  • Missing Data: Temporal gaps and discontinuities in sensor streams
  • Calibration Drift: Long-term sensor stability and recalibration needs

Validation Protocols

  • Cross-Modal Validation: Consistency checking across sensor modalities
  • Known Signal Testing: Validation with synthetic and calibration signals
  • Inter-Device Reliability: Consistency across multiple sensor units
  • Temporal Validation: Synchronization accuracy verification

Research Integration and Applications

Experimental Design Support

  • Event Triggering: Synchronized stimulus presentation and sensor recording
  • Condition Marking: Experimental condition annotation in sensor streams
  • Real-time Feedback: Live biofeedback and neurofeedback applications
  • Multi-Session Studies: Longitudinal data collection and analysis

Analysis Integration

  • Statistical Software: Export compatibility with MATLAB, R, Python
  • Specialized Tools: Integration with EEGLAB, FieldTrip, MNE-Python
  • Machine Learning: Feature extraction for classification and prediction
  • Visualization: Real-time and offline data visualization tools

Privacy and Ethics Considerations

  • Biometric Privacy: Secure handling of physiological identifiers
  • Informed Consent: Comprehensive consent for invasive monitoring
  • Data Anonymization: Biometric feature removal and participant protection
  • Medical Compliance: Healthcare data handling and HIPAA considerations where applicable