Mutual information between brain and heart activity before an epileptic seizure
Main Article Content
Abstract
The paper analyzes the relation between the brain and cardiovascular system activity in patients with epilepsy in the period before an epileptic seizure. Quantification of the connection by mutual information between full power of electroencephalogram and cardiorhythmogram in time windows for an hour before the seizure is proposed. Clinical study results for ten signals containing seizures showed a significant reduction of the mutual information in 5 minutes before the seizure. Ref. 19, Figs. 3.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
Cao Y., Wen-wen Tung, J. B. Gao, V. A. Protopopescu, and L. M. Hively. (2004), Detecting dynamical changes in time series using the permutation entropy. Physical review E70.
Chen W., C.-L. Guo, P.-S. Zhang, C. Liu, H. Qiao, J.-G. Zhang, and F.-G. Meng, (2014), Heart rate changes in partial seizures: analysis of influencing factors among refractory patients.,” BMC Neurol., vol. 14, no. 1, p. 135, Jan. 2014.
Cover, T.M., Thomas. (1991), Elements of information theory. New York: Wiley.
Doquire, G., Verleysen, M. A (2012), “Comparison of Multivariate Mutual Information Estimators for Feature Selection,” SciTePress. Science and and Technology Publications.
Evrengül H., H. Tanriverdi, D. Dursunoglu, A. Kaftan, O. Kuru, U. Unlu, and M. Kilic, “Time and frequency domain analyses of heart rate variability in patients with epilepsy.,” Epilepsy Res., vol. 63, no. 2–3, pp. 131–9, Feb. 2005.
Finsterer J., Wahbi K. (2014), “CNS-Disease Affecting the Heart: Brain–heart Disorders,” Journal of the Neurological Sciences. Vol. 345(1-2). Pp. 8-14.
Kolsal E., A. Serdaroğlu, E. Cilsal, S. Kula, A. Ş. Soysal, A. N. Ç. Kurt, and E. Arhan. (2014), “Can heart rate variability in children with epilepsy be used to predict seizures?,” Seizure, Vol. 23, No. 5, Pp. 357–62, May 2014.
Legg, P.A., Rosin, P.L., Marshall, D., Morgan, J.E. (2007), Improving accuracy and efficiency of registration by mutual information using Sturges’ histogram rule,” Proc. Med. Image Understand. Anal. Pp. 26–30.
Lehnertz K. (1999), “Chaos in Brain”, World Scientific, Singapore, ISBN [978-981-4493-58-1.]
Li X., Ouyang G., Richards D.A. (2007), “Predictability analysis of absence seizures with permutation entropy,” Epilepsy Research, Vol. 77, Pp. 70-74.
Marek, T., Tichavsky, P.(2008), “On the estimation of mutual information,” ROBUST 2008, Pp. 263–269.
Mormann F., Andrzejak R.G., Elger C.E., Lehnertz K. (2007), “Seizure prediction: the long and winding road,” Brain, Vol. 130, No. Pt 2. Pp. 314–333.
Popov A., Avilov O. Oleksii Kanaykin, (2013), “Permutation entropy of EEG signals for different sampling rate and time lag combinations,” Proceedings of Signal Processing Symposium SPS. Pp. 1-4.
A. Popov, S. Zaunseder, H. Malberg. (2012), “Interdependency estimation between brain and cardiovascular activity,” XXXII International Scientific Conference "ELNANO 2012", April 10 12, 2012: Proceedings. Kyiv (Ukraine). Pp. 150-151.
O. Avilov, A. Popov, O. Kanaikin. (2013), “Saturation of electroencephalogram permutation entropy for large time lags,” XXXIII International Scientific Conference Electronics and Nanotechnology, 16-19 April 2013: proceedings. Kyiv, Pp. 251-254.
Schiecke K., Wacker M., D. Piper, F. Benninger, M. Feucht, and H. Witte. (2014), “Time-variant, frequency- selective, linear and nonlinear analysis of heart rate variability in children with temporal lobe epilepsy.,” IEEE Trans. Biomed. Eng., Vol. 61, No. 6, Pp. 1798–1808, Jun. 2014.
Sorjamaa, A., Hao, J., Lendasse, A. (2005), Mutual information and k-nearest neighbors approximator
for time series prediction. Springer.
Zhukov M. (2014), Analysis of interconnection between central nervous and cardiovascular systems. Electronics and Communications, Vol. 19. No 1(78). Pp. 26-36.
Zhukov, M.; Popov, A. (2014), "Bin number selection for equidistant mutual information estimaton," 2014 IEEE 34th International Conference on Electronics and Nanotechnology (ELNANO), Pp.259,263, 15-18 April 2014.