DFAspike: A new computational proposition for efficient recognition of epileptic spike in EEG

An automated method has been presented for the detection of epileptic spikes in the electroencephalogram (EEG) using a deterministic finite automata (DFA) and has been named as DFAspike. EEG data (sampled, 256 Hz) files are the inputs to the DFAspike. The DFAspike was tested with different data files containing epileptic spikes. The obtained recognition rate of epileptic spike was 99.13% on an average. This system does not require any kind of prior training or human intrusion. The result shows that the designed system can be very effectively used for the detection of spikes present in the recorded EEG signals.

[1]  H. Adeli,et al.  Analysis of EEG records in an epileptic patient using wavelet transform , 2003, Journal of Neuroscience Methods.

[2]  N. Chandrasekaran,et al.  Theory of Computer Science: Automata, Languages and Computation , 2006 .

[3]  Jeffrey D. Ullman,et al.  Introduction to Automata Theory, Languages and Computation , 1979 .

[4]  Rakesh Kumar Sinha Backpropagation Artificial Neural Network To Detect Hyperthermic Seizures In Rats , 2002 .

[5]  Rakesh Kumar Sinha,et al.  Parallel Algorithm to Analyze the Brain Signals: Application on Epileptic Spikes , 2011, Journal of Medical Systems.

[6]  Abdulhamit Subasi,et al.  Automatic recognition of alertness level by using wavelet transform and artificial neural network , 2004, Journal of Neuroscience Methods.

[7]  J. Gotman,et al.  Automatic seizure detection in the newborn: methods and initial evaluation. , 1997, Electroencephalography and clinical neurophysiology.

[8]  K. P. Indiradevi,et al.  A multi-level wavelet approach for automatic detection of epileptic spikes in the electroencephalogram , 2008, Comput. Biol. Medicine.

[9]  R. K. Sinha Electro-encephalogram disturbances in different sleep-wake states following exposure to high environmental heat , 2004, Medical and Biological Engineering and Computing.

[10]  Abdulhamit Subasi,et al.  EEG signal classification using wavelet feature extraction and a mixture of expert model , 2007, Expert Syst. Appl..

[11]  R. K. Sinha Artificial neural network detects changes in electro-encephalogram power spectrum of different sleep-wake states in an animal model of heat stress , 2003, Medical and Biological Engineering and Computing.

[12]  Christos H. Papadimitriou,et al.  Elements of the Theory of Computation , 1997, SIGA.

[13]  Rakesh Kumar Sinha,et al.  Epileptic Spike Recognition in Electroencephalogram Using Deterministic Finite Automata , 2009, Journal of Medical Systems.

[14]  Ali Yalcin,et al.  Deadlock avoidance in flexible manufacturing systems using finite automata , 2000, IEEE Trans. Robotics Autom..

[15]  Donald C. Wunsch,et al.  Recurrent neural network based prediction of epileptic seizures in intra- and extracranial EEG , 2000, Neurocomputing.

[16]  Hasan Ocak,et al.  Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy , 2009, Expert Syst. Appl..

[17]  S. Sarbadhikari A neural network confirms that physical exercise reverses EEG changes in depressed rats. , 1995, Medical engineering & physics.

[18]  Michael Unger,et al.  Weighted finite automata for video compression , 1998, IEEE J. Sel. Areas Commun..

[19]  W R Webber,et al.  An approach to seizure detection using an artificial neural network (ANN). , 1996, Electroencephalography and clinical neurophysiology.

[20]  Mehmet Kuntalp,et al.  A study on fuzzy C-means clustering-based systems in automatic spike detection , 2007, Comput. Biol. Medicine.

[21]  B. Litt,et al.  For Personal Use. Only Reproduce with Permission from the Lancet Publishing Group. Review Prediction of Epileptic Seizures Are Seizures Predictable? Prediction of Epileptic Seizures , 2022 .

[22]  Rakesh K Sinha,et al.  An artificial neural network to detect EEG seizures. , 2004, Neurology India.

[23]  Erik D. Goodman,et al.  Epileptic Seizure Detection Using Genetically Programmed Artificial Features , 2007, IEEE Transactions on Biomedical Engineering.