Prediction of Epileptic Seizures using digital signal processing and support vector machine
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.
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Brac University
2021
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| Sarrera elektronikoa: | http://hdl.handle.net/10361/14458 |
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10361-14458 |
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10361-144582022-01-26T10:15:51Z Prediction of Epileptic Seizures using digital signal processing and support vector machine Siddique, Nusayer Masud Sayeed, Samee Mohammad Ahmed, Zaziba Ahmad, Shaikh Rezwan Rafid Parvez, Mohammad Zavid Department of Computer Science and Engineering, Brac University Epilepsy Seizure Phase Angle Power Spectral Density Support Vector Machine This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020. Cataloged from PDF version of thesis. Includes bibliographical references (pages 34-38). Epilepsy is a neurological disorder that causes abnormal behavior and recurrent seizures due to unusual brain activity. Our study has attempted to predict seizures in epileptic patients through the process of feature extraction from EEG signals during preictal and ictal periods, classification and regularization. EEG signals from various parts of the brain from 10 epileptic patients were collected. The signals were converted into its frequency components using a method called fast Fourier transform or FFT. It was then used to determine the three features- the phase angle, the amplitude and the power spectral density of the signals. In order to classify the signals, these features were then used. Regularization was then used to make better predictions i.e. increase the prediction accuracy and decrease the rate of false alarm rate. Through this study, we hope to contribute to the development of better and advanced seizure predicting devices in the medical field. Nusayer Masud Siddique Samee Mohammad Sayeed Zaziba Ahmed Shaikh Rezwan Rafid Ahmad B. Computer Science 2021-06-01T04:19:48Z 2021-06-01T04:19:48Z 2020 2020-04 Thesis ID: 16301102 ID: 16301229 ID: 15201018 ID: 16341005 http://hdl.handle.net/10361/14458 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 38 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
en_US |
| topic |
Epilepsy Seizure Phase Angle Power Spectral Density Support Vector Machine |
| spellingShingle |
Epilepsy Seizure Phase Angle Power Spectral Density Support Vector Machine Siddique, Nusayer Masud Sayeed, Samee Mohammad Ahmed, Zaziba Ahmad, Shaikh Rezwan Rafid Prediction of Epileptic Seizures using digital signal processing and support vector machine |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020. |
| author2 |
Parvez, Mohammad Zavid |
| author_facet |
Parvez, Mohammad Zavid Siddique, Nusayer Masud Sayeed, Samee Mohammad Ahmed, Zaziba Ahmad, Shaikh Rezwan Rafid |
| format |
Thesis |
| author |
Siddique, Nusayer Masud Sayeed, Samee Mohammad Ahmed, Zaziba Ahmad, Shaikh Rezwan Rafid |
| author_sort |
Siddique, Nusayer Masud |
| title |
Prediction of Epileptic Seizures using digital signal processing and support vector machine |
| title_short |
Prediction of Epileptic Seizures using digital signal processing and support vector machine |
| title_full |
Prediction of Epileptic Seizures using digital signal processing and support vector machine |
| title_fullStr |
Prediction of Epileptic Seizures using digital signal processing and support vector machine |
| title_full_unstemmed |
Prediction of Epileptic Seizures using digital signal processing and support vector machine |
| title_sort |
prediction of epileptic seizures using digital signal processing and support vector machine |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14458 |
| work_keys_str_mv |
AT siddiquenusayermasud predictionofepilepticseizuresusingdigitalsignalprocessingandsupportvectormachine AT sayeedsameemohammad predictionofepilepticseizuresusingdigitalsignalprocessingandsupportvectormachine AT ahmedzaziba predictionofepilepticseizuresusingdigitalsignalprocessingandsupportvectormachine AT ahmadshaikhrezwanrafid predictionofepilepticseizuresusingdigitalsignalprocessingandsupportvectormachine |
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1814308381019602944 |