Improving emotion recognition using brain signals / Mohammed Ahmed Abdelaal Ahmed ; Supervised Hesham Hefny , Assem Alsawy
Material type: TextLanguage: English Publication details: Cairo : Mohammed Ahmed Abdelaal Ahmed , 2018Description: 98 Leaves : charts , facsimiles ; 30cmOther title:- تحسين التعرف علي المشاعر باستخدام إشارات المخ [Added title page title]
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Thesis | قاعة الرسائل الجامعية - الدور الاول | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.18.02.M.Sc.2018.Mo.I (Browse shelf(Opens below)) | Not for loan | 01010110079122000 | |||
CD - Rom | مخـــزن الرســائل الجـــامعية - البدروم | المكتبة المركزبة الجديدة - جامعة القاهرة | Cai01.18.02.M.Sc.2018.Mo.I (Browse shelf(Opens below)) | 79122.CD | Not for loan | 01020110079122000 |
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Cai01.18.02.M.Sc.2018.Mo.E An enhanced hybrid approach for word segmentation / | Cai01.18.02.M.Sc.2018.Mo.F A fuzzy logic based approach for voip quality maintaining / | Cai01.18.02.M.Sc.2018.Mo.F A fuzzy logic based approach for voip quality maintaining / | Cai01.18.02.M.Sc.2018.Mo.I Improving emotion recognition using brain signals / | Cai01.18.02.M.Sc.2018.Mo.I Improving emotion recognition using brain signals / | Cai01.18.02.M.Sc.2018.Ne.D Developing an evaluating module for human resource management system / | Cai01.18.02.M.Sc.2018.Ne.D Developing an evaluating module for human resource management system / |
Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information Science
Emotion recognition has become an important factor for easier and effective interaction between human and computer. Despite the importance of emotions in people communications, most of currently human-computer interaction systems lack the ability to recognize and interpret user emotions. Emotions can be recognized by monitoring external phenomena of human body, such as facial expression, voice intonation and body movement. Emotions can also be recognized by monitoring internal physiological signals, such as heart rate, respiration and brain signals. Physiological signals are considered more reliable in emotion recognition specially brain signals. During the last few years, many researchers and companies became interested in interpreting user intentions by monitoring brain signals. Electroencephalography (EEG) is the most used modality to monitor brain signals. EEG measures the electrical activities of the brain through a set of electrodes placed on the scalp. It has a high temporal resolution with no risks, and it is relatively cheap. During the last decades, many commercial EEG devices were produced, and these devices are even easier to setup and use than those devices used in laboratories
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