Emotion recognition using brian signals based on time-frequency analysis and supervised learning algorithm
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
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| Sprache: | English |
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BRAC University
2018
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| Online Zugang: | http://hdl.handle.net/10361/10188 |
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10361-10188 |
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10361-101882022-01-26T10:15:48Z Emotion recognition using brian signals based on time-frequency analysis and supervised learning algorithm Hossain, Prommy Sultana Ferdawoos Shaikat, Istiaque Mannafee George, Fabian Parsia Uddin, Jia Department of Computer Science and Engineering, BRAC University Brain Computer Interface (BCI) DEAP IAPS Emotion recognition Brian signals Learning algorithm This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 40-49). Over the years many groundbreaking research involving Brain Computer Interface (BCI), has been conducted in order to study emotions of human beings, to build better-quality human-machine interaction systems. On the other hand, it is also quite possible to log the activities of brain in real-time and then use it to distinguish patterns related to emotional status. BCI creates a mutual understanding between the users and its environment for measuring emotions through brain activities. Electroencephalogram (EEG) is a well-accepted method to measure the brain activities. Once the system records the EEG signals, we analyze and process these activities to distinguish different emotions. Previous researchers used standard and pre-defined methods of signal processing area with fewer channels and participations to record their EEG signals. In this thesis, a novel method was proposed that extracted features from EEG signals based on time-frequencies analysis and supervised learning algorithm was used to classify different emotional states. Our proposed method provides 92.36% accuracy by using a benchmark dataset, where 32 participants were used to carry out this experiment. Prommy Sultana Ferdawoos Hossain Fabian Parsia George Istiaque Mannafee Shaikat B. Computer Science and Engineering 2018-05-22T03:44:50Z 2018-05-22T03:44:50Z 2018 2018-04 Thesis ID 16241002 ID 14101072 ID 14301059 http://hdl.handle.net/10361/10188 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. 49 pages application/pdf BRAC University |
| institution |
Brac University |
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Institutional Repository |
| language |
English |
| topic |
Brain Computer Interface (BCI) DEAP IAPS Emotion recognition Brian signals Learning algorithm |
| spellingShingle |
Brain Computer Interface (BCI) DEAP IAPS Emotion recognition Brian signals Learning algorithm Hossain, Prommy Sultana Ferdawoos Shaikat, Istiaque Mannafee George, Fabian Parsia Emotion recognition using brian signals based on time-frequency analysis and supervised learning algorithm |
| description |
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. |
| author2 |
Uddin, Jia |
| author_facet |
Uddin, Jia Hossain, Prommy Sultana Ferdawoos Shaikat, Istiaque Mannafee George, Fabian Parsia |
| format |
Thesis |
| author |
Hossain, Prommy Sultana Ferdawoos Shaikat, Istiaque Mannafee George, Fabian Parsia |
| author_sort |
Hossain, Prommy Sultana Ferdawoos |
| title |
Emotion recognition using brian signals based on time-frequency analysis and supervised learning algorithm |
| title_short |
Emotion recognition using brian signals based on time-frequency analysis and supervised learning algorithm |
| title_full |
Emotion recognition using brian signals based on time-frequency analysis and supervised learning algorithm |
| title_fullStr |
Emotion recognition using brian signals based on time-frequency analysis and supervised learning algorithm |
| title_full_unstemmed |
Emotion recognition using brian signals based on time-frequency analysis and supervised learning algorithm |
| title_sort |
emotion recognition using brian signals based on time-frequency analysis and supervised learning algorithm |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/10188 |
| work_keys_str_mv |
AT hossainprommysultanaferdawoos emotionrecognitionusingbriansignalsbasedontimefrequencyanalysisandsupervisedlearningalgorithm AT shaikatistiaquemannafee emotionrecognitionusingbriansignalsbasedontimefrequencyanalysisandsupervisedlearningalgorithm AT georgefabianparsia emotionrecognitionusingbriansignalsbasedontimefrequencyanalysisandsupervisedlearningalgorithm |
| _version_ |
1814308312597921792 |