Intra-class Correlation among Heart Rate Variability analysis softwares across different physiological postures.

Area of Science:

• Physiology
• Biomedical Engineering
• Cardiology

Background:

• Heart rate variability (HRV) assesses cardiac autonomic activity.
• Standardization is needed as different hardware and software are used for HRV analysis.
• Lack of agreement between HRV analysis software hinders cross-laboratory comparisons.

Purpose of the Study:

• To evaluate the correlation between three commonly used HRV analysis software.
• To determine if short-term HRV data analysis is comparable across different software platforms.
• To assess the reliability of HRV analysis for clinical and research applications.

Main Methods:

• Intra-class correlation coefficient (ICC) test was employed.
• ECG data was acquired from 26 healthy volunteers in various body positions.
• Short-term HRV analysis was performed using Kubios HRV, HRV soft, and Nevrokard software.

Main Results:

• A highly significant (p<0.001) positive correlation (ICC > 0.8) was observed among the three software programs.
• This strong agreement was found for both time and frequency domain HRV parameters.
• The correlation remained consistent across supine, sitting, and standing positions.

Conclusions:

• The three analyzed HRV software programs demonstrate excellent agreement for short-term analysis.
• Findings support the comparability of HRV interpretations across different laboratories and software.
• This facilitates more reliable and standardized clinical and research applications of HRV.