A Novel Alcoholic EEG Signals Classification Approach Based on AdaBoost k-means Coupled with Statistical Model

Paper

Diykh, Mohammed, Abdulla, Shahab, Oudah, Atheer Y., Marhoon, Haydar Abdulameer and Siuly, Siuly. 2021. "A Novel Alcoholic EEG Signals Classification Approach Based on AdaBoost k-means Coupled with Statistical Model ." Siuly, Siuly, Wang, Hua, Chen, Lu, Guo, Yanhui and Xing, Chunxiao (ed.) 10th International Conference on Health Information Science (HIS 2021). Melbourne, Australia 25 - 28 Oct 2021 Cham, Switzerland. https://doi.org/10.1007/978-3-030-90885-0_8
Paper/Presentation Title

A Novel Alcoholic EEG Signals Classification Approach Based on AdaBoost k-means Coupled with Statistical Model

Presentation TypePaper
AuthorsDiykh, Mohammed (Author), Abdulla, Shahab (Author), Oudah, Atheer Y. (Author), Marhoon, Haydar Abdulameer (Author) and Siuly, Siuly (Author)
EditorsSiuly, Siuly, Wang, Hua, Chen, Lu, Guo, Yanhui and Xing, Chunxiao
Journal or Proceedings TitleProceedings of the 10th International Conference on Health Information Science (HIS 2021)
Journal Citation13079, pp. 82-92
Number of Pages11
Year2021
Place of PublicationCham, Switzerland
ISBN9783030908843
9783030908850
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-030-90885-0_8
Web Address (URL) of Paperhttps://link.springer.com/chapter/10.1007/978-3-030-90885-0_8
Web Address (URL) of Conference Proceedingshttps://link.springer.com/book/10.1007/978-3-030-90885-0
Conference/Event10th International Conference on Health Information Science (HIS 2021)
Event Details
10th International Conference on Health Information Science (HIS 2021)
Parent
International Conference on Health Information Science (HIS)
Delivery
In person
Event Date
25 to end of 28 Oct 2021
Event Location
Melbourne, Australia
Abstract

Identification of alcoholism is an important task because it affects the operation of the brain. Alcohol consumption, particularly heavier drinking is identified as an essential factor to develop health issues, such as high blood pressure, immune disorders, and heart diseases. To support health professionals in diagnosis disorders related with alcoholism with a high rate of accuracy, there is an urgent demand to develop an automated expert systems for identification of alcoholism. In this study, an expert system is proposed to identify alcoholism from multi-channel EEG signals. EEG signals are partitioned into small epochs, with each epoch is further divided into sub-segments. A covariance matrix method with its eigenvalues is utilised to extract representative features from each sub-segment. To select most relevant features, a statistic approach named Kolmogorov–Smirnov test is adopted to select the final features set. Finally, in the classification part, a robust algorithm called AdaBoost k-means (AB-k-means) is designed to classify EEG features into two categories alcoholic and non-alcoholic EEG segments. The results in this study show that the proposed model is more efficient than the previous models, and it yielded a high classification rate of 99%. In comparison with well-known classification algorithms such as K-nearest k-means and SVM on the same databases, our proposed model showed a promising result compared with the others. Our findings showed that the proposed model has a potential to implement in automated alcoholism detection systems to be used by experts to provide an accurate and reliable decisions related to alcoholism.

Keywordsalcoholism, EEG, AdaBoost k-means, covariance matrix, Kolmogorov–Smirnov
ANZSRC Field of Research 2020429999. Other health sciences not elsewhere classified
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SeriesLecture Notes in Computer Science
Byline AffiliationsUniversity of Thi-Qar, Iraq
USQ College
Al-Ayen University, Iraq
Victoria University
Institution of OriginUniversity of Southern Queensland
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Sleep EEG signal analysis based on correlation graph similarity coupled with an ensemble extreme machine learning algorithm
Abdulla, Shahab, Diykh, Mohammed, Lafta, Raid Luaibi, Saleh, Khalid and Deo, Ravinesh C.. 2019. "Sleep EEG signal analysis based on correlation graph similarity coupled with an ensemble extreme machine learning algorithm." Expert Systems with Applications. 138, pp. 1-15. https://doi.org/10.1016/j.eswa.2019.07.007
A new design of mental state classification for subject independent BCI systems
Joadder, Md. A. M., Siuly, S., Kabir, E., Wang, H. and Zhang, Y.. 2019. "A new design of mental state classification for subject independent BCI systems." IRBM. 40 (5), pp. 297-305. https://doi.org/10.1016/j.irbm.2019.05.004
An Efficient Texture Descriptor for the Detection of License Plates From Vehicle Images in Difficult Conditions
Al-Shemarry, Meeras Salman, Li, Yan and Abdulla, Shahab. 2020. "An Efficient Texture Descriptor for the Detection of License Plates From Vehicle Images in Difficult Conditions." IEEE Transactions on Intelligent Transportation Systems. 21 (2), pp. 553-564. https://doi.org/10.1109/TITS.2019.2897990
A feature extraction technique based on tunable Q-factor wavelet transform for brain signal classification
Al Ghayab, Hadi Ratham, Li, Yan, Siuly, S. and Abdulla, Shahab. 2019. "A feature extraction technique based on tunable Q-factor wavelet transform for brain signal classification." Journal of Neuroscience Methods. 312, pp. 43-52. https://doi.org/10.1016/j.jneumeth.2018.11.014
A new approach to spread-spectrum OFDM
Alhasnawi, Mohammad Kaisb Layous, Addie, Ronald G. and Abdulla, Shahab. 2018. "A new approach to spread-spectrum OFDM." 15th International Joint Conference on e-Business and Telecommunications (ICETE 2018) - Volume 1: DCNET, ICE-B, OPTICS, SIGMAP and WINSYS. Porto, Portugal 26 - 28 Jul 2018 https://doi.org/10.5220/0006828602810288
An efficient approach for EEG sleep spindles detection based on fractal dimension coupled with time frequency image
Al-Salman, Wessam, Li, Yan, Wen, Peng and Diykh, Mohammed. 2018. "An efficient approach for EEG sleep spindles detection based on fractal dimension coupled with time frequency image." Biomedical Signal Processing and Control. 41, pp. 210-221. https://doi.org/10.1016/j.bspc.2017.11.019
Epileptic seizures detection in EEGs blending frequency domain with information gain technique
Al Ghayab, Hadi Ratham, Li, Yan, Siuly, Siuly and Abdulla, Shahab. 2019. "Epileptic seizures detection in EEGs blending frequency domain with information gain technique." Soft Computing. 23 (1), pp. 227-239. https://doi.org/10.1007/s00500-018-3487-0
A New Way of Channel Selection in the Motor Imagery Classification for BCI Applications
Joadder, Md. A. Mannan, Siuly, Siuly and Kabir, Enamul. 2018. "A New Way of Channel Selection in the Motor Imagery Classification for BCI Applications ." Siuly, Siuly, Lee, Ickjai, Huang, Zhisheng, Zhou, Rui, Wang, Hua and Xiang, Wei (ed.) 7th International Conference on Health Information Science (HIS 2018). Cairns, Australia 05 - 07 Oct 2018 Switzerland. https://doi.org/10.1007/978-3-030-01078-2_10
Developing new techniques to analyse and classify EEG signals
Diykh, Mohammed Abdalhadi. 2018. Developing new techniques to analyse and classify EEG signals . PhD Thesis Doctor of Philosophy. University of Southern Queensland.
Epileptic EEG signal classification using optimum allocation based power spectral density estimation
Al Ghayab, Hadi Ratham, Li, Yan, Siuly, Siuly and Abdulla, Shahab. 2018. "Epileptic EEG signal classification using optimum allocation based power spectral density estimation." IET Signal Processing. 12 (6), pp. 738-747. https://doi.org/10.1049/iet-spr.2017.0140
The perceived public value of social media in Queensland local Councils
Attiya, Ahmed Muyed, Cater-Steel, Aileen, Soar, Jeffrey and Abdulla, Shahab. 2017. "The perceived public value of social media in Queensland local Councils." Riemer, Kai, Indulska, Marta and Tuunainen, Virpi Kristiina (ed.) 28th Australasian Conference on Information Systems (ACIS 2017). Hobart, Australia 04 - 06 Dec 2017 Hobart, Australia.
Developing a tunable Q-factor wavelet transform based algorithm for epileptic EEG feature extraction
Al Ghayab, Hadi Ratham, Li, Yan, Siuly, Siuly, Abdulla, Shahab and Wen, Paul. 2017. "Developing a tunable Q-factor wavelet transform based algorithm for epileptic EEG feature extraction." Siuly, Siuly, Huang, Zhisheng, Aickelin, Uwe, Zhou, Rui, Wang, Hua, Zhang, Yanchun and Klimenko, Stanislav (ed.) 6th International Conference on Health Information Science (HIS 2017). Moscow, Russian Federation 07 - 09 Oct 2017 Germany. https://doi.org/10.1007/978-3-319-69182-4_6
Nursing students’ readiness for the numeracy needs of their program: students’ perspective
Galligan, Linda, Frederiks, Anita, Wandel, Andrew P., Robinson, Clare, Abdulla, Shahab and Hussain, Zanubia. 2017. "Nursing students’ readiness for the numeracy needs of their program: students’ perspective." Adults Learning Mathematics: An International Journal. 12 (1), pp. 27-38.
Classify epileptic EEG signals using weighted complex networks based community structure detection
Diykh, Mohammed, Li, Yan and Wen, Peng. 2017. "Classify epileptic EEG signals using weighted complex networks based community structure detection." Expert Systems with Applications. 90, pp. 87-100. https://doi.org/10.1016/j.eswa.2017.08.012
An Efficient DDoS TCP Flood Attack Detection and Prevention System in a Cloud Environment
Sahi, Aqeel, Lai, David, Li, Yan and Diykh, Mohammed. 2017. "An Efficient DDoS TCP Flood Attack Detection and Prevention System in a Cloud Environment ." IEEE Access. 5, pp. 6036-6048. https://doi.org/10.1109/ACCESS.2017.2688460
A computer aided analysis scheme for detecting epileptic seizure from EEG data
Kabir, Enamul, Siuly, Siuly, Cao, Jinli and Wang, Hua. 2018. "A computer aided analysis scheme for detecting epileptic seizure from EEG data." International Journal of Computational Intelligence Systems. 11, pp. 663-671. https://doi.org/10.2991/ijcis.11.1.51
Person identification by gait analysis using photogrammetry techniques and foot pressure sensing matt
Majeed, Ammar, Chong, Albert K. and Abdulla, Shahab. 2017. "Person identification by gait analysis using photogrammetry techniques and foot pressure sensing matt." Al-Jumaily, Adel Ali, Barifcani, Ahmed and Al-Jumaily, Ahmed (ed.) 1st MoHESR and HCED Iraqi Scholars Conference in Australasia 2017 (ISCA 2017). Melbourne, Australia 05 - 06 Dec 2017 Melbourne, Australia.
Ensemble of adaboost cascades of 3L-LBPs classifiers for license plates detection with low quality images
Al-Shemarry, Meeras Salman, Li, Yan and Abdulla, Shahab. 2018. "Ensemble of adaboost cascades of 3L-LBPs classifiers for license plates detection with low quality images." Expert Systems with Applications. 92, pp. 216-235. https://doi.org/10.1016/j.eswa.2017.09.036
Complex networks approach for EEG signal sleep stages classification
Diykh, Mohammed and Li, Yan. 2016. "Complex networks approach for EEG signal sleep stages classification." Expert Systems with Applications. 63, pp. 241-248. https://doi.org/10.1016/j.eswa.2016.07.004
EEG sleep stages classification based on time domain features and structural graph similarity
Diykh, Mohammed, Li, Yan and Wen, Peng. 2016. "EEG sleep stages classification based on time domain features and structural graph similarity." IEEE Transactions on Neural Systems and Rehabilitation Engineering. 24 (11), pp. 1159-1168. https://doi.org/10.1109/TNSRE.2016.2552539
EEG signal analysis and classification: techniques and applications
Siuly, Siuly, Li, Yan and Zhang, Yanchun. 2017. EEG signal analysis and classification: techniques and applications. Switzerland. Springer.
Depth of anaesthesia patient models and control
Abdulla, Shahab and Wen, Peng. 2011. "Depth of anaesthesia patient models and control." Guo, Shuxiang, Touge, Tetsuo and Xiufen, Ye (ed.) 2011 IEEE/ICME International Conference on Complex Medical Engineering (ICME 2011). Harbin, China 22 - 25 May 2011 Piscataway, NJ. United States. https://doi.org/10.1109/ICCME.2011.5876701
Fuzzy and non-fuzzy approaches for digital image classification
Diykh, Mohammed and Li, Yan. 2016. "Fuzzy and non-fuzzy approaches for digital image classification." Journal of Theoretical and Applied Information Technology. 95 (4), pp. 858-870.
Discriminating the brain activities for brain–computer interface applications through the optimal allocation-based approach
Siuly, Siuly and Li, Yan. 2015. "Discriminating the brain activities for brain–computer interface applications through the optimal allocation-based approach." Neural Computing and Applications. 26 (4), pp. 799-811. https://doi.org/10.1007/s00521-014-1753-3
Classification of epileptic EEG signals based on simple random sampling and sequential feature selection
Al Ghayab, Hadi, Li, Yan, Abdulla, Shahab, Diykh, Mohammed and Wan, Xiangkui. 2016. "Classification of epileptic EEG signals based on simple random sampling and sequential feature selection." Brain Informatics. 3 (2), pp. 85-91. https://doi.org/10.1007/s40708-016-0039-1
Excel files of bispectral index (BIS), anaesthesia levels and nominal patient data based on sensitivity to anaesthesia
Abdulla, Shahab. Excel files of bispectral index (BIS), anaesthesia levels and nominal patient data based on sensitivity to anaesthesia. Toowoomba.
Designing a robust feature extraction method based on optimum allocation and principal component analysis for epileptic EEG signal classification
Siuly, Siuly and Li, Yan. 2015. "Designing a robust feature extraction method based on optimum allocation and principal component analysis for epileptic EEG signal classification." Computer Methods and Programs in Biomedicine. 119 (1), pp. 29-42. https://doi.org/10.1016/j.cmpb.2015.01.002
Epileptic seizure detection from EEG signals using logistic model trees
Kabir, Enamul, Siuly, . and Zhang, Yanchun. 2016. "Epileptic seizure detection from EEG signals using logistic model trees." Brain Informatics. 3 (2), pp. 93-100. https://doi.org/10.1007/s40708-015-0030-2
Exploring sampling in the detection of multicategory EEG signals
Siuly, Siuly, Kabir, Enamul, Wang, Hua and Zhang, Yanchun. 2015. "Exploring sampling in the detection of multicategory EEG signals." Computational and Mathematical Methods in Medicine. 2015. https://doi.org/10.1155/2015/576437
Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain–computer interface
Siuly, Siuly, Li, Yan and Wen, Peng (Paul). 2014. "Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain–computer interface ." Computer Methods and Programs in Biomedicine. 113 (3), pp. 767-780. https://doi.org/10.1016/j.cmpb.2013.12.020
A novel statistical algorithm for multiclass EEG signal classification
Siuly and Li, Yan. 2014. "A novel statistical algorithm for multiclass EEG signal classification." Engineering Applications of Artificial Intelligence. 34, pp. 154-167. https://doi.org/10.1016/j.engappai.2014.05.011
Students' mathematical preparation: differences in staff and student perceptions
Wandel, Andrew P., Robinson, Clare, Abdulla, Shahab, Dalby, Tim, Frederiks, Anita and Galligan, Linda. 2015. "Students' mathematical preparation: differences in staff and student perceptions." International Journal of Innovation in Science and Mathematics Education. 23 (1), pp. 82-93.
Students' mathematical preparation Part A: lecturers' perceptions
Galligan, Linda, Wandel, Andrew, Pigozzo, Robyn, Frederiks, Anita, Robinson, Clare, Abdulla, Shahab and Dalby, Tim. 2013. "Students' mathematical preparation Part A: lecturers' perceptions." Deborah, King, Birgit, Loch and Leanne, Rylands (ed.) 9th Delta Conference of Teaching and Learning of Undergraduate Mathematics and Statistics 2013: Shining Through the Fog. Kiama, Australia 24 - 29 Nov 2013 Sydney, Australia.
Students' mathematical preparation Part B: students' perceptions
Dalby, Tim, Robinson, Clare, Abdulla, Shahab, Galligan, Linda, Frederiks, Anita, Pigozzo, Robyn and Wandel, Andrew. 2013. "Students' mathematical preparation Part B: students' perceptions." King, Deborah, Loch, Birgit and Rylands, Leanne (ed.) 9th Delta Conference of Teaching and Learning of Undergraduate Mathematics and Statistics 2013: Shining Through the Fog. Kiama, Australia 24 - 29 Nov 2013 Sydney, Australia.
Improving the Separability of Motor Imagery EEG Signals Using a Cross Correlation-Based Least Square Support Vector Machine for Brain–Computer Interface
Siuly, Siuly and Li, Yan. 2012. "Improving the Separability of Motor Imagery EEG Signals Using a Cross Correlation-Based Least Square Support Vector Machine for Brain–Computer Interface." IEEE Transactions on Neural Systems and Rehabilitation Engineering. 20 (4), pp. 526-538. https://doi.org/10.1109/TNSRE.2012.2184838
Model based predictive control of depth of anaesthesia
Abdulla, Shahab, Wen, Peng, Zude, Zhou and Quan, Liu. 2012. "Model based predictive control of depth of anaesthesia." Chih-Hsing, Chu, Smith, Shana and Hong, Hocheng (ed.) 2012 International Conference on Innovative Design and Manufacturing (ICIDM 2012). Taipei, Taiwan 12 - 14 Dec 2012 Taiwan.
The effects of time-delay on feedback control of depth of anesthesia
Abdulla, Shahab A. and Wen, Peng. 2012. "The effects of time-delay on feedback control of depth of anesthesia." Zhang, Yuan-Ting, Naghavi, Morteza, Bonato, Paolo and Carmen, C. Y. Poon (ed.) 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics (BHI 2012). Hong Kong and Shenzhen, China 02 - 07 Jan 2012 Hong Kong, China. https://doi.org/10.1109/BHI.2012.6211747
Depth of anaesthesia control investigation using robust deadbeat control technique
Abdulla, Shahab and Wen, Peng. 2012. "Depth of anaesthesia control investigation using robust deadbeat control technique." Tetsuo, Kobayashi, Tetsuo, Touge, Hisao, Tachibana and Jinglong, Wu (ed.) 2012 International Conference on Complex Medical Engineering (ICME 2012). Kobe, Japan 01 - 04 Jul 2012 Piscataway, NJ. United States. https://doi.org/10.1109/ICCME.2012.6275636
Clustering technique-based least square support vector machine for EEG signal classification
Siuly, S., Li, Yan and Wen, Peng (Paul). 2011. "Clustering technique-based least square support vector machine for EEG signal classification." Computer Methods and Programs in Biomedicine. 104 (3), pp. 358-372. https://doi.org/10.1016/j.cmpb.2010.11.014
Depth of anaesthesia control techniques and human body models
Abdulla, Shahab Anna. 2012. Depth of anaesthesia control techniques and human body models. PhD Thesis Doctor of Philosophy. University of Southern Queensland.
Convection drying process modeling and simulation study based on tomato
Shahab, Anna, Wen, Peng and Richard, George. 2009. "Convection drying process modeling and simulation study based on tomato." Giannoccaro, Nicola Ivan and Klingajay, Mongkorn (ed.) International Conference on Robotics, Informatics, Intelligence Control System Technology (RIIT 2009). Bangkok, Thailand 11 - 14 Dec 2009 Bangkok, Thailand.
Fruit drying process: analysis, modeling and simulation
Abdulla, Shahab, Wen, Paul, Landers, Richard and Yousif, B. F.. 2011. "Fruit drying process: analysis, modeling and simulation." Scientific Research and Essays. 6 (23), pp. 4915-4924.
Robust internal model control for depth of anaesthesia
Abdulla, Shahab Anna and Wen, Peng. 2011. "Robust internal model control for depth of anaesthesia." International Journal of Mechatronics and Automation. 1 (1), pp. 1-8. https://doi.org/10.1504/IJMA.2011.039150
The design and investigation of model based internal model control for the regulation of hypnosis
Abdulla, Shahab, Wen, Peng and Xiang, Wei. 2010. "The design and investigation of model based internal model control for the regulation of hypnosis." Kuo, Way, Tsui, Lap Chee and Sung, Jao Yiu (ed.) IEEE/NANOMED 2010: Promoting Good Health with Nanotechnology. Hong Kong, China 05 - 09 Dec 2010 Hong Kong. https://doi.org/10.1109/NANOMED.2010.5749833
Depth of anesthesia control using internal model control techniques
Anna, Shahab and Wen, Peng. 2010. "Depth of anesthesia control using internal model control techniques." Li, Yan, Yang, Jiajia, Wen, Peng and Wu, Jinglong (ed.) 2010 IEEE/ICME International Conference on Complex Medical Engineering (ICME 2010). Gold Coast, Australia 13 - 15 Jul 2010 Piscataway, NJ. United States. https://doi.org/10.1109/ICCME.2010.5558825