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Multifractal Approach for Quantification of Autonomic Deregulation Due to Epileptic Seizure with ECG Data

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Multifractals and Chronic Diseases of the Central Nervous System

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Abstract

Since the autonomic function affecting the sympathetic, parasympathetic nervous system changes due to epileptic seizure, the corresponding changes in cardiac signals may be effectively used as potential biomarker providing an extracerebral indicator of ictal onset in some cases. Patients suffering from epilepsy may experience serious cardiac malfunctions leading to sudden unexpected death (SUDEP). Thus the heart rate fluctuations during seizure are non-linear and extremely complex. This chapter presents a report on the analysis of ECG signals of postictal patients using a modern and rigorous chaos-based non-linear technique.

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Authors and Affiliations

  1. Department of Physics, Sir C V Raman Centre for Physics and Music, Jadavpur University, Kolkata, West Bengal, India

    Dipak Ghosh

  2. Department for Physics, Seacom Engineering College, Howrah, West Bengal, India

    Shukla Samanta

  3. Electrical and Electronics Engineering, ICFAI University, Agartala, Tripura, India

    Sayantan Chakraborty

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  2. Shukla Samanta
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Ghosh, D., Samanta, S., Chakraborty, S. (2019). Multifractal Approach for Quantification of Autonomic Deregulation Due to Epileptic Seizure with ECG Data. In: Multifractals and Chronic Diseases of the Central Nervous System. Springer, Singapore. https://doi.org/10.1007/978-981-13-3552-5_3

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