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Motor imagery detection and classification techniques based on EEG signals from brains / Mahmoud Eid Abdelhafez Abdellahi Abdelhadi ; Supervised Reda Abdelwahab Ahmed Alkhoribi , Mahmoud Ahmed Ismail Shoman , Mohammed Ahmed Ahmed Refaey

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Mahmoud Eid Abdelhafez Abdellahi Abdelhadi , 2016Description: 125 Leaves : charts , facsimiles , photographs ; 30cmOther title:
  • اكتشاف و تصنيف الرغبة في الحركة اعتمادا على الاشارات الكهربية من المخ [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Technology Summary: Self-paced Brain Computer Interfaces (BCIs) is a preponderant trend nowadays for the most natural human-machine interaction. There is an increasing need to deal with critical disorders that involve death of neurons namely Amyotrophic Lateral Sclerosis (ALS), or brainstem stroke. Translating motor imagery activities of the brain can help any patient who suffers from these severe conditions. The detection of motor imagery is followed by a classification process. Results can be sent to a computer program or a wheel chair or a mind controlled prosthesis. Translating motor imagery into a decision requires a number of parameters to be optimized. These parameters were found varying from subject to another. Reliable features have to be extracted that describe the Motor Imagery (MI) related activity properly
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.01.M.Sc.2016.Ma.M (Browse shelf(Opens below)) Not for loan 01010110069801000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.20.01.M.Sc.2016.Ma.M (Browse shelf(Opens below)) 69801.CD Not for loan 01020110069801000

Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information Technology

Self-paced Brain Computer Interfaces (BCIs) is a preponderant trend nowadays for the most natural human-machine interaction. There is an increasing need to deal with critical disorders that involve death of neurons namely Amyotrophic Lateral Sclerosis (ALS), or brainstem stroke. Translating motor imagery activities of the brain can help any patient who suffers from these severe conditions. The detection of motor imagery is followed by a classification process. Results can be sent to a computer program or a wheel chair or a mind controlled prosthesis. Translating motor imagery into a decision requires a number of parameters to be optimized. These parameters were found varying from subject to another. Reliable features have to be extracted that describe the Motor Imagery (MI) related activity properly

Issued also as CD

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