EEG-Beats

EEG-Beats analyzes heart rate variability (HRV) from signals recorded by a single-channel, chest-mounted electroencephalography (EEG) sensor to detect interbeat intervals and compute HRV metrics synchronized with EEG recordings.

Key Features:

• MATLAB implementation: provided as a MATLAB toolbox for HRV analysis from EEG-derived cardiac signals.
• Artifact-Robust Detection: an automated algorithm processes raw chest EEG signals to detect heartbeat peaks and calculate interbeat intervals with robustness to artifacts.
• Synchronization with EEG Data: aligns heart rate and interbeat interval time series with EEG recordings for precise temporal correspondence.
• Comprehensive HRV Metrics: computes standard time-domain and frequency-domain HRV indicators.
• Automated Processing: processes entire datasets autonomously without manual intervention.

Scientific Applications:

• Longitudinal cohort analysis: applied in a study of 17 subjects across 6 tasks and 854 datasets to evaluate HRV from chest EEG recordings.
• Integrated EEG–HRV research: enables exploration of dynamic interactions between physiological responses and cognitive or emotional states via synchronized EEG and HRV data.

Methodology:

An automated algorithm processes raw single-channel chest EEG signals to detect heartbeat peaks, calculate interbeat intervals, compute standard time-domain and frequency-domain HRV metrics, and synchronize heart rate data with EEG recordings.