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There is a growing interest of research being conducted on detecting eye blink to assist physically impaired people for verbal communication and controlling devices using electroencephalogram (EEG) signal. One particular eye blink can be determined from use of peak points. Therefore, the purpose of peak detection algorithm is to distinguish an actual peak location from a list of peak candidates. The need of a good peak model is important in ensuring a satisfy classification performance. In general, there are various peak models available in literature, which have been tested in several peak detection algorithms. In this study, performance evaluation of the existing peak models is conducted based on Artificial Neural Network (ANN) with particle swarm optimization (PSO) as learning algorithm. This study evaluates the performance of eye blink EEG signal peak detection algorithm for four different peak models which are Dumpala’s, Acir’s, Liu’s, and Dingle’s peak models. To generalize the performance evaluation, two case studies of eye blink EEG signal are considered, which are single and double eye blink signals. It has been observed that the best test performance, in average, is 91.94% and 87.47% for single and double eye blink signals, respectively. These results indicate that the Acir’s peak model offers high accuracy of peak detection for the two eye blink EEG signals as compared to other peak models. The result of statistical analysis also indicates that the Acir’s peak model is better than Dingle’s and Dumpala’s peak models.

Pensyarah FKEE UMP Kongsi Kepakaran Dalam Pengaturcaraan dan Pembinaan Lego Mindstrom

Pekan 23 Februari - Fakulti Kejuruteraan Elektrik dan Elektronik (FKEE) Universiti Malaysia Pahang (UMP) dengan kerjasama Pejabat Pendidikan Daerah Pekan (PPD) menganjurkan Bengkel Traning of Trainers (TOT), Pekan baru-baru ini.

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Innovate 2017 - the STEM EcoSystem

UMP Pekan 14 July - As the Pahang State Level host for this year’s championship, we welcome you to the 2017 Young Innovate Malaysia Competition. YI 2017 provides a highly competitive platform for academicians, teachers, industries and most importantly the future generation - our school children.

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On 17th May 2017, 20 of the faculty staffs were involved in “Santai Sains Bersama FKEE”: a STEM outreach program at Sek. Keb. Sri Maulana in Pekan, Pahang. This is.

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Program GTEX ENHANCING GRADUATE SKILLS TOWARDS EMPLOYABILITY ini merupakan program persedian kepada pelajar universiti tahun akhir yang bakal melalui alam pekerjaan.

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