Effect of EKG Sampling Rate on Heart Rate Variability Analysis

Area of Science:

• Biomedical Engineering
• Neonatal Cardiology
• Physiological Monitoring

Background:

• Therapeutic hypothermia is crucial for hypoxic-ischemic encephalopathic infants.
• Accurate heart rate variability (HRV) analysis is vital for monitoring infant health.
• Electrocardiogram (EKG) sampling rates can influence HRV metric reliability.

Purpose of the Study:

• To evaluate the impact of EKG downsampling on HRV metrics in neonates.
• To compare HRV analysis using different EKG sampling rates (1000 Hz, 500 Hz, 250 Hz, 125 Hz) and a data warehouse (250 Hz).

Main Methods:

• Acquired continuous EKG from four infants undergoing therapeutic hypothermia.
• Calculated various HRV metrics (nLF, nHF, LF, HF, DFA exponents, RMSS, RMSL) from EKGs at different sampling rates.
• Utilized intraclass correlation coefficient (ICC) to compare HRV metrics across sampling rates.

Main Results:

• High correlation (r > 0.8) was observed between reference EKG (1000 Hz) and downsampled EKGs for most HRV metrics.
• Significant correlation (r = 0.7) was found between 250 Hz EKG and data warehouse EKG (250 Hz) for most HRV metrics.
• High-frequency (HF) power showed compromised correlation (r = 0.276) in the data warehouse EKG signal.

Conclusions:

• Downsampling EKG signals to 250 Hz or higher generally preserves HRV analysis accuracy in this population.
• Caution is advised when interpreting HF power from EKG signals stored at 250 Hz in a data warehouse.
• Further research is needed to optimize EKG acquisition and processing for neonatal HRV monitoring.