Computer processing of artifact and arrhythmias in heart rate variability analysis

Area of Science:

• Cardiology
• Biomedical Engineering
• Data Science

Background:

• Heart rate variability (HRV) analysis using Holter monitoring is challenged by artifacts and arrhythmias.
• Standard preprocessing methods struggle with slow HR variations and specific arrhythmias, distorting analysis.
• Accurate HRV analysis requires robust preprocessing to handle data complexities.

Purpose of the Study:

• To evaluate different HR data preprocessing methods for HRV analysis.
• To develop and present an improved computer-based approach for HR data preprocessing.
• To address limitations of existing methods in handling artifacts and specific arrhythmias.

Main Methods:

• A combined method using absolute differences for artifact and arrhythmia removal.
• Detection of sudden HR surges, noise, slow variations, and optional wild point removal.
• Identification of special cases like T-waves, bigeminal rhythm, and nocturnal HR increases.

Main Results:

• The developed combined method effectively removes artifacts and arrhythmias.
• The approach successfully identifies and handles challenging HR variations and arrhythmias.
• The computer analysis proved superior to simplified methods for HRV data preparation.

Conclusions:

• The proposed preprocessing method enhances the quality of HR data for HRV analysis.
• This advanced computer analysis offers a more robust solution for complex Holter monitoring data.
• The findings contribute to more reliable HRV interpretation in clinical and research settings.