Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning
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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| Online pristup: | http://hdl.handle.net/10361/14724 |
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10361-147242022-01-26T10:05:00Z Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning Saleque, Shahriar Spriha, Gul-A-Zannat Kamal, MD Rasheeq Ishraq Khan, Rafia Tabassum Chakrabarty, Amitabha Department of Computer Science and Engineering, Brac University MDD Absolute delta power LR SVM NB EEG Machine learning. Image processing. 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 54-61). Depression is accorded as one of the leading causes to all the problems related to mental health in the Global disease burden study (GBD). Major depressive disorder (MDD) is when this depression reaches to a larger extent, when depression persists for two weeks or more. Sadly, many individuals of our society tend to neglect depression and refuse to label it as a mental disease and has a tendency to not seek medical help. Not only this, they are being curbed because of the few or very limited biological indicators for MDD and depression identification. Our main objective is to develop a non-intrusive approach that will detect and differentiate brain signals of patients with MDD from healthy patients. We were able to obtain an optimized model with an accuracy of (82%). Primarily we obtained a raw EEG data-set upon research and since it matched our requirements, we performed noise removal on them. Afterwards we extracted relevant features for depression detection, such as one feature was Absolute delta power. Finally, we entered these features into three classification algorithms; Logistic Regression (LR), Support Vector Machine (SVM) and Negative-Bayes (NB). To check the accuracy and precision, we performed a ten-fold cross validation on them. Hopefully, our results will encourage and motivate people suffering from this to seek the proper and effective medical help and to eradicate the negative stigma around it. Shahriar Saleque Gul-A-Zannat Spriha MD Rasheeq Ishraq Kamal Rafia Tabassum Khan B. Computer Science 2021-07-03T13:47:11Z 2021-07-03T13:47:11Z 2020 2020-04 Thesis ID 19341016 ID 16301089 ID 16101074 ID 16301081 http://hdl.handle.net/10361/14724 en 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. 61 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
MDD Absolute delta power LR SVM NB EEG Machine learning. Image processing. |
| spellingShingle |
MDD Absolute delta power LR SVM NB EEG Machine learning. Image processing. Saleque, Shahriar Spriha, Gul-A-Zannat Kamal, MD Rasheeq Ishraq Khan, Rafia Tabassum Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning |
| 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 |
Chakrabarty, Amitabha |
| author_facet |
Chakrabarty, Amitabha Saleque, Shahriar Spriha, Gul-A-Zannat Kamal, MD Rasheeq Ishraq Khan, Rafia Tabassum |
| format |
Thesis |
| author |
Saleque, Shahriar Spriha, Gul-A-Zannat Kamal, MD Rasheeq Ishraq Khan, Rafia Tabassum |
| author_sort |
Saleque, Shahriar |
| title |
Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning |
| title_short |
Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning |
| title_full |
Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning |
| title_fullStr |
Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning |
| title_full_unstemmed |
Depression classification with MDD (Major Depressive Disorder) using signal processing and machine learning |
| title_sort |
depression classification with mdd (major depressive disorder) using signal processing and machine learning |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14724 |
| work_keys_str_mv |
AT salequeshahriar depressionclassificationwithmddmajordepressivedisorderusingsignalprocessingandmachinelearning AT sprihagulazannat depressionclassificationwithmddmajordepressivedisorderusingsignalprocessingandmachinelearning AT kamalmdrasheeqishraq depressionclassificationwithmddmajordepressivedisorderusingsignalprocessingandmachinelearning AT khanrafiatabassum depressionclassificationwithmddmajordepressivedisorderusingsignalprocessingandmachinelearning |
| _version_ |
1814307130204749824 |