ABSTRACT
In this research, a Principal Component Analysis (PCA) with Genetic Algorithm based Machine Learning (ML) approach is developed for the binary classification of epileptic seizures from the EEG dataset. The proposed approach utilizes PCA to reduce the number of features for binary classification of epileptic seizures and is applied to the existing machine learning models to evaluate the model performance in comparison to the higher number of features. Here, Genetic Algorithm (GA) is employed to tune the hyperparameters of the machine learning models for identifying the best ML model. The proposed approach is applied to the UCI epileptic seizure recognition dataset, which is originated from the EEG dataset of Bonn University. As a preliminary analysis of the proposed approach, the data analysis result shows a significant reduction in the number of features but has minimal impact on the ML performance parameters in comparison to the existing ML method.
- M. Akter, A. Rahman, and A. K. Islam. 2014. An Improved Method of Automatic Exudates Detection in Retinal Images. International Journal Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering 2 (2014).Google Scholar
- R. G. Andrzejak, K. Lehnertz, F. Mormann, C. Rieke, P. David, and C. E. Elger. 2001. Indications of Nonlinear Deterministic and Finite-dimensional Structures in Time Series of Brain Electrical Activity: Dependence on Recording Region and Brain State. Physical Review E 64, 6 (2001), 061907.Google ScholarCross Ref
- G. Biau. 2012. Analysis of a Random Forests Model. The Journal of Machine Learning Research 13, 1 (2012), 1063--1095.Google ScholarDigital Library
- J. Birjandtalab, M. B. Pouyan, and M. Nourani. 2016. Nonlinear Dimension Reduction for EEG-based Epileptic Seizure Detection. In 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). IEEE, 595--598.Google Scholar
- G. Chen, W. Xie, T. D. Bui, and A. Krzyżak. 2017. Automatic Epileptic Seizure Detection in EEG Using Nonsubsampled Wavelet-fourier Features. Journal of Medical and Biological Engineering 37, 1 (2017), 123--131.Google ScholarCross Ref
- M. Fan and C. Chou. 2018. Detecting Abnormal Pattern of Epileptic Seizures via Temporal Synchronization of EEG Signals. IEEE Transactions on Biomedical Engineering 66, 3 (2018), 601--608.Google ScholarCross Ref
- L. Fraiwan and M. Alkhodari. 2020. Classification of Focal and Non-focal Epileptic Patients Using Single Channel EEG and Long Short-term Memory Learning System. IEEE Access 8 (2020), 77255--77262.Google ScholarCross Ref
- T. Gautama, D. P. Mandic, and M. M. V. Hulle. 2003. Indications of Nonlinear Structures in Brain Electrical Activity. Physical Review E 67, 4 (2003), 046204.Google ScholarCross Ref
- M. Geng, W. Zhou, G. Liu, C. Li, and Y. Zhang. 2020. Epileptic Seizure Detection Based on Stockwell Transform and Bidirectional Long Short-term Memory. IEEE Transactions on Neural Systems and Rehabilitation Engineering 28, 3 (2020), 573--580.Google ScholarCross Ref
- I. Güler and E. D. Übeyli. 2005. Adaptive Neuro-fuzzy Inference System for Classification of EEG Signals Using Wavelet Coefficients. Journal of neuroscience methods 148, 2 (2005), 113--121.Google ScholarCross Ref
- M. A. Haque, A. K. M. K. Islam, and M. I. Islam. 2009. Evaluation of Performances of Digital Adaptive Filters in Acoustic Echo Cancellation. In 2009 12th International Conference on Computers and Information Technology. IEEE, 215--219.Google Scholar
- M. A. Haque, A. K. M. K. Islam, and M. I. Islam. 2010. Demystifying the Digital Adaptive Filters Conducts in Acoustic Echo Cancellation. Journal of Multimedia 5, 6 (2010), 568.Google ScholarCross Ref
- K. P. Harikrishnan, R. Misra, G. Ambika, and A. K. Kembhavi. 2006. A Non-subjective Approach to the GP Algorithm for Analysing Noisy Time Series. Physica D: Nonlinear Phenomena 215, 2 (2006), 137--145.Google ScholarCross Ref
- D. P. He, Z. L. He, and C. Liu. 2020. Recommendation Algorithm Combining Tag Data and Naive Bayes Classification. In 2020 3rd International Conference on Electron Device and Mechanical Engineering (ICEDME). IEEE, 662--666.Google Scholar
- E. M. Imah and A. Widodo. 2017. A Comparative Study of Machine Learning Algorithms for Epileptic Seizure Classification on EEG Signals. In 2017 International Conference on Advanced Computer Science and Information Systems (ICACSIS). IEEE, 401--408.Google Scholar
- A. K. M. K. Islam and S. Belkasim. 2020. Ensemble of SVM for Colorectal Cancer Classification from Microarray Gene Expression Data. (2020).Google Scholar
- A. K. M. K. Islam and M. A. Haque. 2011. One Step Predictor Extended Kalman Filter in Heavily Clamorous System: A Strategic Approach of Noise Reduction. In 14th International Conference on Computer and Information Technology (ICCIT 2011). IEEE, 370--375.Google Scholar
- A. K. M. K. Islam, M. A. Haque, A. Rahman, and A. Bhuiyan. 2012. A Simplified Performance Evaluation for Delay of Voice End User (DOVE) in Micro Macro Cellular Mobile Communications System. In 2012 International Conference on Informatics, Electronics & Vision (ICIEV). IEEE, 1206--1210.Google Scholar
- D. Jacobs, T. Hilton, M. D. Campo, P. L. Carlen, and B. L. Bardakjian. 2018. Classification of Pre-clinical Seizure States Using Scalp EEG Cross-frequency Coupling Features. IEEE Transactions on Biomedical Engineering 65, 11 (2018), 2440--2449.Google ScholarCross Ref
- I. Jahan, K. M. A. Ali, A. K. M. K. Islam, M. Akter, and M. M. Islam. 2015. Active Network Service Composition. International Journal of Engineering Research and Development (2015).Google Scholar
- B. Karlik and Ş. B. Hayta. 2014. Comparison Machine Learning Algorithms for Recognition of Epileptic Seizures in EEG. Proceedings IWBBIO 2014 (2014).Google Scholar
- Y. Li, Y. Liu, W. Cui, Y. Guo, H. Huang, and Z. Hu. 2020. Epileptic Seizure Detection in EEG Signals Using a Unified Temporal-Spectral Squeeze-and-excitation Network. IEEE Transactions on Neural Systems and Rehabilitation Engineering 28, 4 (2020), 782--794.Google ScholarCross Ref
- P. Mirowski, D. Madhavan, Y. LeCun, and R. Kuzniecky. 2009. Classification of Patterns of EEG Synchronization for Seizure Prediction. Clinical Neurophysiology 120, 11 (2009), 1927--1940.Google ScholarCross Ref
- V. P. Nigam and D. Graupe. 2004. A Neural-network-based Detection of Epilepsy. Neurological Research 26, 1 (2004), 55--60.Google ScholarCross Ref
- E. Pippa, V. G. Kanas, E. I. Zacharaki, V. Tsirka, M. Koutroumanidis, and V. Megalooikonomou. 2016. EEG-based Classification of Epileptic and Non-epileptic Events Using Multi-array Decomposition. International Journal of Monitoring and Surveillance Technologies Research (IJMSTR) 4, 2 (2016), 1--15.Google ScholarDigital Library
- M. K. M. Rabby, M. S. Alam, and M. S. A. Shawkat. 2019. A Priority Based Energy Harvesting Scheme for Charging Embedded Sensor Nodes in Wireless Body Area Networks. PloS one 14, 4 (2019), e0214716.Google ScholarCross Ref
- M. K. M. Rabby, M. S. Alam, S. A. Shawkat, and M. A Hoque. 2017. A Scheduling Scheme for Efficient Wireless Charging of Sensor Nodes in WBAN. In 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE). IEEE, 31--36.Google ScholarDigital Library
- M. K. M. Rabby, B. Chowdhury, and J. H. Kim. 2018. A Modified Canny Edge Detection Algorithm for Fruit Detection & Classification. In 2018 10th international conference on electrical and computer engineering (ICECE). IEEE, 237--240.Google Scholar
- M. K. M. Rabby, M. M. Islam, and S. M. Imon. 2019. A Review of IoT Application in a Smart Traffic Management System. In 2019 5th International Conference on Advances in Electrical Engineering (ICAEE). IEEE, 280--285.Google Scholar
- M. K. M. Rabby, M. Khan, A. Karimoddini, and S. X. Jiang. 2019. An Effective Model for Human Cognitive Performance within a Human-robot Collaboration Framework. In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 3872--3877.Google Scholar
- M. K. M. Rabby, M. A. Khan, A. Karimoddini, and S. X. Jiang. 2020. Modeling of Trust Within a Human-robot Collaboration Framework. In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 4267--4272.Google Scholar
- A. Sharma, JK Rai, and RP Tewari. 2018. Epileptic Seizure Anticipation and Localisation of Epileptogenic Region Using EEG Signals. Journal of Medical Engineering & Technology 42, 3 (2018), 203--216.Google ScholarCross Ref
- M. Sharma, R. B. Pachori, and U. R. Acharya. 2017. A New Approach to Characterize Epileptic Seizures Using Analytic Time-frequency Flexible Wavelet Transform and Fractal Dimension. Pattern Recognition Letters 94 (2017), 172--179.Google ScholarDigital Library
- S. Sheykhivand, T. Y. Rezaii, Z. Mousavi, A. Delpak, and A. Farzamnia. 2020. Automatic Identification of Epileptic Seizures from EEG Signals Using Sparse Representation-based Classification. IEEE Access 8 (2020), 138834--138845.Google ScholarCross Ref
- J. Song, Q. Li, B. Zhang, B. Westover, and R. Zhang. 2019. A New Neural Mass Model Driven Method and its Application in Early Epileptic Seizure Detection. IEEE Transactions on Biomedical Engineering (2019).Google Scholar
- A. Subasi, J. Kevric, and M. A. Canbaz. 2019. Epileptic Seizure Detection Using Hybrid Machine Learning Methods. Neural Computing and Applications 31, 1 (2019), 317--325.Google ScholarDigital Library
- N. D. Truong, A. D. Nguyen, L. Kuhlmann, M. R. Bonyadi, J. Yang, S. Ippolito, and O. Kavehei. 2018. Convolutional Neural Networks for Seizure Prediction Using Intracranial and Scalp Electroencephalogram. Neural Networks 105 (2018), 104--111.Google ScholarDigital Library
- K. M. Tsiouris, V. C. Pezoulas, M. Zervakis, S. Konitsiotis, D. D. Koutsouris, and D. I. Fotiadis. 2018. A Long Short-term Memory Deep Learning Network for the Prediction of Epileptic Seizures Using EEG Signals. Computers in Biology and Medicine 99 (2018), 24--37.Google ScholarCross Ref
- S. M. Usman, M. Usman, and S. Fong. 2017. Epileptic Seizures Prediction Using Machine Learning Methods. Computational and Mathematical Methods in Medicine 2017 (2017).Google Scholar
- S. Wang, W. A. Chaovalitwongse, and S. Wong. 2013. Online Seizure Prediction Using an Adaptive Learning Approach. IEEE Transactions on Knowledge and Data Engineering 25, 12 (2013), 2854--2866.Google ScholarDigital Library
- X. Wei, L. Zhou, Z. Zhang, Z. Chen, and Y. Zhou. 2019. Early Prediction of Epileptic Seizures Using a Long-term Recurrent Convolutional Network. Journal of Neuroscience Methods 327 (2019), 108395.Google ScholarCross Ref
- J. Yu. 2019. Epileptic Seizure Classification ML Algorithms. https://towardsdatascience.com/seizure-classification-d0bb92d19962.Google Scholar
- X. Zhang, L. Yao, M. Dong, Z. Liu, Y. Zhang, and Y. Li. 2020. Adversarial Representation Learning for Robust Patient-independent Epileptic Seizure Detection. IEEE Journal of Biomedical and Health Informatics (2020).Google Scholar
Index Terms
- Epileptic seizures classification in EEG using PCA based genetic algorithm through machine learning
Recommendations
Prediction of epileptic seizures using fNIRS and machine learning
Research to predict epileptic seizures has been mainly focused on the analysis of electroencephalography (EEG) signals; however, recent research efforts have encouraged the use of a relatively new optical signal modality, called functional Near-Infrared ...
Classification of single-channel EEG signals for epileptic seizures detection based on hybrid features
Papers from the 6th International Conference on Biomedical Engineering and Biotechnology (iCBEB2017), 17–20 October 2017, Guangzhou, ChinaBACKGROUND:Epilepsy is a common chronic neurological disorder of the brain. Clinically, epileptic seizures are usually detected via the continuous monitoring of electroencephalogram (EEG) signals by experienced ...
Multi-Resolution EEG AND EEG Sub-Band Features Optimization for Epileptic Classification Using Hybrid Evolutionary Computing Technique
AbstractEpilepsy is one of the neurological issues causing interminable irregular electrical release in the mind. The electroencephalogram (EEG) has developed as a critical instrument in the cerebrum movement checking for epilepsy conclusion. Hereditary ...
Comments