Publication Type:

Journal Article

Source:

International Journal of Applied Engineering Research, Research India Publications, Volume 10, Number 10, p.25475-25492 (2015)

URL:

http://www.scopus.com/inward/record.url?eid=2-s2.0-84932152701&partnerID=40&md5=7b3675d372aa558ba74e01641f444484

Abstract:

Epilepsy is a chronic disorder of the central nervous system that causes individuals to experience recurrent seizures. Epilepsy is identified as the world’s second most common brain disorder after stroke affecting nearly and over 40 million people worldwide. The work presented in this paper describes a novel method to predict the EEG (Electroencephalogram) signal with maximum possible accuracy. The feature used for the entire signal analysis and prediction is AR (Autoregression) Coefficients. The predicted signal was found to be highly accurate with least Root Mean Square Error. The classification and detection of seizure from the predicted signal is left for future implementation. © Research India Publications.

Notes:

cited By 0

Cite this Research Publication

S. A. Hari Prasad, Gowtham, S., Radhika, R., Arvind, K. S., Renny, G., and K.A. Pradeep Kumar, “A novel method for seizure prediction based on autoregressive modelling and a real-time error correction algorithm”, International Journal of Applied Engineering Research, vol. 10, pp. 25475-25492, 2015.