System for automatic heart rate calculation in epileptic seizures.

Area of Science:

• Biomedical Engineering
• Signal Processing
• Clinical Monitoring

Background:

• Epileptic seizures can cause significant physiological changes, including alterations in heart rate (HR).
• Accurate HR monitoring during seizures is crucial for patient care and research.
• Existing methods for HR detection can be unreliable due to noise and artifacts common during seizures.

Purpose of the Study:

• To develop and validate a robust automatic system for heart rate (HR) detection.
• To ensure the system's resilience against noise, interferences, and artifacts, particularly those occurring during epileptic seizures.
• To assess the system's performance in clinical settings for patients with temporal lobe epilepsy.

Main Methods:

• Preprocessing involved Infinite Impulse Response (IIR) filtration and normalization of ECG signals.
• A reference QRS complex pattern was individually calculated for each ECG recording.
• Cross-correlation of the QRS pattern with normalized ECG windows identified R-wave locations for RR interval and HR/HRV calculation.

Main Results:

• The algorithm demonstrated high accuracy in QRS complex detection.
• The system exhibited high sensitivity and specificity in simulated and real-world conditions.
• Tested with added noise several times higher than standard deviation, the algorithm maintained performance.

Conclusions:

• The developed system provides accurate and robust automatic heart rate (HR) detection.
• The algorithm is effective in challenging conditions, including during epileptic seizures.
• The system is clinically useful for monitoring HR in patients with intractable temporal lobe epilepsy.