Purpose: This study explores the use of heart rate variability (HRV) analysis, a noninvasive technique for assessing the autonomic nervous system, by applying nonlinear dynamics and chaos theory to detect chaotic behavior in RR intervals and assess cardiovascular health.
Methods: Employing the "System Analysis of Heart Rate Dynamics" (SADR) program, this research combines chaos analysis with the short-time Fourier transform to assess nonlinear dynamic parameters in HRV. It includes constructing phase portraits in Takens space and calculating measures of chaos to identify deterministic chaos indicators.
Results: The analysis identifies distinct chaos indicators in the cardiac rhythm of healthy volunteers compared to tachyarrhythmia patients, both before and after catheter treatment. Post-radiofrequency ablation (RFA) analysis shows promise as a predictive tool for arrhythmia recurrence.
Conclusions: The findings suggest that HRV analysis, through nonlinear dynamics, can be an effective noninvasive method for predicting arrhythmia recurrence following treatments like catheter ablation. This approach has the potential for early and precise detection of arrhythmia, pending further validation.
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