Developing new techniques to analyse and classify EEG signals

PhD Thesis

Diykh, Mohammed Abdalhadi. 2018. Developing new techniques to analyse and classify EEG signals . PhD Thesis Doctor of Philosophy. University of Southern Queensland.
Title

Developing new techniques to analyse and classify EEG signals

TypePhD Thesis
Authors
AuthorDiykh, Mohammed Abdalhadi
SupervisorAbdulla, Shahab
Saleh, Khalid
Institution of OriginUniversity of Southern Queensland
Qualification NameDoctor of Philosophy
Number of Pages185
Year2018
Abstract

A massive amount of biomedical time series data such as Electroencephalograph (EEG), electrocardiography (ECG), Electromyography (EMG) signals are recorded daily to monitor human performance and diagnose different brain diseases. Effectively and accurately analysing these biomedical records is considered a challenge for researchers. Developing new techniques to analyse and classify these signals can help manage, inspect and diagnose these signals.

In this thesis novel methods are proposed for EEG signals classification and analysis based on complex networks, a statistical model and spectral graph wavelet transform. Different complex networks attributes were employed and studied in this thesis to investigate the main relationship between behaviours of EEG signals and changes in networks attributes. Three types of EEG signals were investigated and analysed; sleep stages, epileptic and anaesthesia.

The obtained results demonstrated the effectiveness of the proposed methods for analysing these three EEG signals types. The methods developed were applied to score sleep stages EEG signals, and to analyse epileptic, as well as anaesthesia EEG signals. The outcomes of the project will help support experts in the relevant medical fields and decrease the cost of diagnosing brain diseases.

Keywordsclassification; and analysis; EEG signal
ANZSRC Field of Research 2020400607. Signal processing
Byline AffiliationsSchool of Agricultural, Computational and Environmental Sciences
Permalink -

https://research.usq.edu.au/item/q4yy9/developing-new-techniques-to-analyse-and-classify-eeg-signals

Log in to edit

Download files

Published Version
clean_version_thesis_new.pdf
File access level: Anyone

  • 499
    total views
  • 402
    total downloads
  • 2
    views this month
  • 6
    downloads this month

Export as

Related outputs

An intelligent model involving multi-channels spectrum patterns based features for automatic sleep stage classification
Abdulla, Shahab, Diykh, Mohammed, Siuly, Siuly and Ali, Mumtaz. 2023. "An intelligent model involving multi-channels spectrum patterns based features for automatic sleep stage classification." International Journal of Medical Informatics. 171, pp. 1-10. https://doi.org/10.1016/j.ijmedinf.2023.105001
Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition
Diykh, Mohammed, Abdulla, Shahab, Deo, Ravinesh C, Siuly, Siuly and Ali, Mumtaz. 2023. "Developing a novel hybrid method based on dispersion entropy and adaptive boosting algorithm for human activity recognition." Computer Methods and Programs in Biomedicine. 229, pp. 1-11. https://doi.org/https://doi.org/10.1016/j.cmpb.2022.107305
ECG Signals Classification Model Based on Frequency domain Features Coupled with Least Square Support Vector Machine (LSSVM)
Azeez, Rand Ameen, Alkhafaji, Sarmad K. D., Diykh, Mohammed and Abdulla, Shahab. 2022. "ECG Signals Classification Model Based on Frequency domain Features Coupled with Least Square Support Vector Machine (LSSVM)." Agma, Traina, Wang, Hua, Zhang, Yong, Siuly, Siuly, Zhou, Rui and Chen, Lui (ed.) 11th International Conference on Health Information Science (HIS 2022). Biarritz, France 28 - 30 Oct 2022 Switzerland. https://doi.org/10.1007/978-3-031-20627-6_28
An Intelligence Approach for Blood Pressure Estimation from Photoplethysmography Signal
Abdulla, Shahab, Diykh, Mohammed, AlKhafaji, Sarmad K. D., Oudah, Atheer Y, Marhoon, Haydar Abdulameer and Azeez, Rand Ameen. 2022. "An Intelligence Approach for Blood Pressure Estimation from Photoplethysmography Signal ." Agma, Traina, Wang, Hua, Zhang, Yong, Siuly, Siuly, Zhou, Rui and Chen, Lu (ed.) 11th International Conference on Health Information Science (HIS 2022). Biarritz, France 28 - 30 Oct 2022 Switzerland. https://doi.org/10.1007/978-3-031-20627-6_6
An Eigenvalues-Based Covariance Matrix Bootstrap Model Integrated With Support Vector Machines for Multichannel EEG Signals Analysis
Al-Hadeethi, Hanan, Abdulla, Shahab, Diykh, Mohammed, Deo, Ravinesh C. and Green, Jonathan H.. 2022. "An Eigenvalues-Based Covariance Matrix Bootstrap Model Integrated With Support Vector Machines for Multichannel EEG Signals Analysis." Frontiers in Neuroinformatics. 15, pp. 1-15. https://doi.org/10.3389/fninf.2021.808339
Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals
Diykh, Mohammed, Miften, Firas Sabar, Abdulla, Shahab, Deo, Ravinesh C., Siuly, Siuly, Green, Jonathan H. and Oudah, Atheer Y.. 2022. "Texture analysis based graph approach for automatic detection of neonatal seizure from multi-channel EEG signals." Measurement. 190 (110731), pp. 1-13. https://doi.org/10.1016/j.measurement.2022.110731
Developing Smart Self Orienting Solar Tracker for Mobile PV Power Generation Systems
Al-Saadi, Yousif R., Tapou, Monaf S., Badi, Areej A., Abdulla, Shahab and Diykh, Mohammed. 2022. "Developing Smart Self Orienting Solar Tracker for Mobile PV Power Generation Systems." IEEE Access. 10, pp. 79090-79099. https://doi.org/10.1109/ACCESS.2022.3194026
A Novel Alcoholic EEG Signals Classification Approach Based on AdaBoost k-means Coupled with Statistical Model
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
Determinant of Covariance Matrix Model Coupled with AdaBoost Classification Algorithm for EEG Seizure Detection
Al-Hadeethi, Hanan, Abdulla, Shahab, Diykh, Mohammed and Green, Jonathan H.. 2021. "Determinant of Covariance Matrix Model Coupled with AdaBoost Classification Algorithm for EEG Seizure Detection." Diagnostics. 12 (1), pp. 1-18. https://doi.org/10.3390/diagnostics12010074
A new framework for classification of multi-category hand grasps using EMG signals
Miften, Firas Sabar, Diykh, Mohammed, Abdulla, Shahab, Siuly, Siuly, Green, Jonathan H. and Deo, Ravinesh C.. 2021. "A new framework for classification of multi-category hand grasps using EMG signals." Artificial Intelligence in Medicine. 112, pp. 1-14. https://doi.org/10.1016/j.artmed.2020.102005
Epileptic Seizures Detection Based on Non-linear Characteristics Coupled with Machine Learning Techniques
Miften, Firas Sabar, Diykh, Mohammed, Abdulla, Shahab and Green, Jonathan H.. 2020. "Epileptic Seizures Detection Based on Non-linear Characteristics Coupled with Machine Learning Techniques." Rahman, Atta-ur- and Amtul, Zareen (ed.) Frontiers in Clinical Drug Research: CNS and Neurological Disorders. Sharjah, United Arab Emirates. Bentham Science Publishers. pp. 23-39
Adaptive boost LS-SVM classification approach for time-series signal classification in epileptic seizure diagnosis applications
Al-Hadeethi, Hanan, Abdulla, Shahab, Diykh, Mohammed, Deo, Ravinesh C. and Green, Jonathan H.. 2020. "Adaptive boost LS-SVM classification approach for time-series signal classification in epileptic seizure diagnosis applications." Expert Systems with Applications. 161. https://doi.org/10.1016/j.eswa.2020.113676
A structural graph-coupled advanced machine learning ensemble model for disease risk prediction in a telehealthcare environment
Lafta, Raid, Zhang, Ji, Tao, Xiaohui, Li, Yan, Diykh, Mohammed and Lin, Jerry Chun-Wei. 2018. "A structural graph-coupled advanced machine learning ensemble model for disease risk prediction in a telehealthcare environment." Roy, Sanjiban Sekhar, Samui, Pijushi, Deo, Ravinesh and Ntalampiras, Stalampiras (ed.) Big data in engineering applications. Singapore. Springer. pp. 363-384
Robust approach for depth of anaesthesia assessment based on hybrid transform and statistical features
Diykh, Mohammed, Miften, Firas Sabar, Abdulla, Shahab, Saleh, Khalid and Green, Jonathan H.. 2020. "Robust approach for depth of anaesthesia assessment based on hybrid transform and statistical features." IET Science, Measurement and Technology. 14 (1), pp. 128-136. https://doi.org/10.1049/iet-smt.2018.5393
Complex networks approach for depth of anesthesia assessment
Diykh, Mohammed, Li, Yan, Wen, Peng and Li, Tianning. 2018. "Complex networks approach for depth of anesthesia assessment." Measurement. 119, pp. 178-189. https://doi.org/10.1016/j.measurement.2018.01.024
EEG sleep stages identification based on weighted undirected complex networks
Diykh, Mohammed, Li, Yan and Abdulla, Shahab. 2020. "EEG sleep stages identification based on weighted undirected complex networks." Computer Methods and Programs in Biomedicine. 184, pp. 1-14. https://doi.org/10.1016/j.cmpb.2019.105116
Fractal dimension undirected correlation graph-based support vector machine model for identification of focal and non-focal electroencephalography signals
Diykh, Mohammed, Abdulla, Shahab, Saleh, Khalid and Deo, Ravinesh C.. 2019. "Fractal dimension undirected correlation graph-based support vector machine model for identification of focal and non-focal electroencephalography signals." Biomedical Signal Processing and Control. 54, pp. 1-10. https://doi.org/10.1016/j.bspc.2019.101611
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
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
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
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
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.
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