Abstract
Loss of complexity and chaos of heart rate variability (HRV) of an individual increases the risk of mortality from cardiovascular diseases. Abnormalities in HRV associated with intractable epilepsy may even lead to “sudden death in epilepsy” (SUDEP). By activating the parasympathetic division of the autonomic nervous system, Vagus Nerve Stimulation (VNS) has the potential to restore the natural chaotic behavior of the heart which can be measured by the increase in complexity of HRV as indicated by complexity measures such as Effort-To-Compress (ETC) and Lempel-Ziv Complexity (LZC). In this study, we formulate and test two hypothesis–(A) chaotic time series exhibit lower temporal correlation of complexity measures such as LZ and ETC than uniformly random time series, and (B) Vagus Nerve Stimulation (VNS ON) results in chaotic cardiovascular dynamics. Hypothesis-A is verified by a simulated study on chaotic time series from the Logistic map where we see a clear decrease in temporal correlation between ETC and LZC values as the degree of chaos increases. Hypothesis-B is supported by an experimental study on a VNS implanted patient and not implanted controls. A temporal correlation analysis between complexity measures (ETC and LZC) on HRV data samples shows that VNS during sleep increases chaotic behavior in contrast to lack of VNS and in control subjects. Surrogate analysis further confirmed that VNS activation led to deterministic chaos and not stochastic randomness. Our approach proposes a clear methodology to determine the efficacy of VNS intervention in restoring the chaoticity of cardiovascular dynamics.
Original language | English (US) |
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Pages (from-to) | 3809-3815 |
Number of pages | 7 |
Journal | IETE Journal of Research |
Volume | 68 |
Issue number | 5 |
DOIs | |
State | Published - 2022 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2022 IETE.
Keywords
- Complexity
- Effort-to-compress complexity
- Heart rate variability
- Lempel-Ziv complexity
- Logistic map
- Sudden death in epilepsy
- Surrogate analysis