BRAINWAVESCLASSIFICATION TOWARD HUMANEMOTION BASED ON EEG SIGNAL MOHAMMED ABDULKAREEM AHMED UNIVERSITI TEKNOLOGI MALAYSIA
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1 i BRAINWAVESCLASSIFICATION TOWARD HUMANEMOTION BASED ON EEG SIGNAL MOHAMMED ABDULKAREEM AHMED UNIVERSITI TEKNOLOGI MALAYSIA
2 iv BRAIN WAVESCLASSIFICATION TOWARDHUMAN EMOTION BASED ON EEG SIGNAL MOHAMMEDABDULKAREEMAHMED A dissertation submitted in partial fulfillment of the requirements for the award of the degree of Master of Science (Computer Science) Faculty of Computing Universiti Teknologi Malaysia MAY 2013
3 vi DEDICATION With love and gratitude to Allah, my beloved mother, father,brothers and sister for their support, patience and being till the moment of my dissertation completion.
4 vii ACKNOWLEDGMENTS In the name of Allah, the Most Gracious, the Most Merciful. Praise be toallah, Lord of the universe for making me able to undertake this research work until the end. I would like to present my sincere gratitude to my supervisor Dr. Ahmad Hoirul Basori for his invaluable guidance, dedication, time and earnest encouragement in working toward the development this research. In preparing this dissertation, I was in contact with many people, researchers, academicians, and practitioners. They have contributed towards my understanding and thoughts. I would like to deliver y gratitude towards the panels who give constructive opinions and suggestions in order to correct my way during the research development as follows : Prof. Dr. Dzulkifli Mohamad and Prof. Dr. Habibollah Haron. Special gratitudes to all my fellow colleagues and friends from Computer Science and Iraqi Student Society whom which I cannot write all of them here for their encouragement, discussion and friendship, in which I considered as my family. My gratitude also to the lecturers and staffs for their knowledge and support during the duration of study as the students in Universiti Teknologi Malaysia. Finally, I deliver my deepest and endless gratitude towards my dearest mother and father:hanah Abdulah Jasim and Abdulkareem Ahmed Taha, my brothers Ahmed, Mustafa and my sister Zainab, and also for all friends for their continuous encouragement, patience and support to pursue my study and at the same time being close at hand to render love, comfort and support. Without them I may not be able to achieve and pursue the study like this moment. May Allah return all your good deeds and provide His blessing and guidance to all of us..
5 viii ABSTRACT The important role of communication between human s brain and computer has been increased during the last years. In this research, the main focus of this thesis isanalysingbrain wavesthat associated with the internal emotion of human. The analysing processis achieved by reading the EEG signals from user brain.nia deviceis used in this research to read the signals from the frontal lobe of the brain. This sturdy base on reading brain wave signals in order to be representedas an avatar facial expression. The aim of this research is to show the influence of alpha and beta brain waves toward emotion classification through EEG signal. In addition,the researchis analysing brain signals in order to represent happy and sad emotions. The classification of human emotion through brain computer interface can be interpreted through speed of brain waves signal. The velocity is used to calculate the speed of brain signals for each emotion. The results provedthat the velocity of sad emotion is faster than happy emotion. As a conclusion, this research shows the speed for each emotion which can be used to specify the internal emotion characteristic of a user. User emotion is represented as a facial expression of virtual human in 3D environment. These results can be used to create a good classification because it specifies the average of speed for each emotion.
6 ix ABSTRAK Peranan komunikasi dan computer merupakan di antara otak manusia bidang yang semakin meningkat kepentingannya dalam beberapa tahun kebelakangan ini. Dalam kajian ini, focus utama adalah menganalisa hubungan di antara gelombang otak dan emosi dalaman manusia. Proses penganalisaan dapat dicapai dengan membaca isyarat EEG dari otak manusia. Peralatan NIA digunakan dalam kajian ini untuk membaca isyarat dari lobus hadapan otak. Isyarat gelombang otak dibaca dan diwakilkan melalui paparan ekspresi wajah. Matlamat kajian ini adalah untuk mengkaji pengaruh gelomban gotak alpha dan beta terhadap klasifikasi emosi melalui isyarat EEG. Kajian ini memfokus kepada analisa isyarat otak untuk menentukan emosi gembira atau sedih. Klasifikasi emosi manusia melalui antara muka otak-komputer boleh ditafsirkan melalui kelajuan isyarat gelombang otak. Halaju digunakan untuk mengukur kelajuan isyarat otak untuk setiap emosi. Hasil kajian mendapati halaju isyarat otak untuk emosi sedih adalah lebih tinggi dari emosi gembira. Kesimpulannya, kajian ini menunjukkan bahawa kelajuan isyarat gelombang otak boleh digunakan untuk menentukan emosi dalaman manusia. Hasil penentuan emosi manusia diwakilkan melalui ekspresi wajah manusia maya dalam persekitaran 3D. Hasil kajian boleh digunakan untuk mencapai klasifikasi yang baik kerana purata kelajuan isyarat gelombang otak untuk setiap emosi dapat ditentukan.
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