Papers by Eng. Ammar Alhamadani
Journal of Fundamental and Applied Sciences, 2018
The service quality of any information based system could be evaluated by the high end user in su... more The service quality of any information based system could be evaluated by the high end user in such a way that the system developer or responsible intently might use these user experiences to improve, develop and benchmark their system. In this paper, questionnaire implemented to rate to what extent the academic admission system as a web site achieves performance. Data were collected from 21 users of the system; all of them are highly educated and have the experience of using the site. Quadrant and gap analysis were implemented to evaluate the weakness and strength of the data. The major data analyses were performed on the data collected in terms of its importance and satisfaction to the users. A number of statistical tools have been utilized such as average value and standard deviation to accomplish the objective of this paper.
New Inverse Kinematic based Brain Computer Interface (IK-BCI) system was proposed. the system per... more New Inverse Kinematic based Brain Computer Interface (IK-BCI) system was proposed. the system performs aim selection intended by user through acquiring user's EEG signal, extract the signal's feature, classify the intention behind the signal, and performs inverse kinematic on the predicted position to make the robotic arm be reached to the desired position. Three types of five-classes EEG mental tasks signals were acquired using EMOTIV EPOC EEG head set in separate sessions and compared in terms of online system's performance after using each one as input signal. The proposed feature extraction method was hybrid feature extraction that include Multiclass Support Vector Machine (M-CSP) with Autoregressive (AR) coefficients features. Multiclass Support Vector Machine with Radial Basis kernel Function (SVM-RBF) was used for machine learning processing based on LIBSVM MATLAB library. Analytical solution was proposed to perform the Inverse Kinematic (IK) on 5-DOF Humanoid Robotic Arm (HRA) to be controlled in online basis. The practical results showed a successful cooperation between the IK and BCI with highest classification accuracy of 88.75% which leads to successful reach of the desired target.
In this paper, feature extraction methods such as time domain, frequency domain and spatial domai... more In this paper, feature extraction methods such as time domain, frequency domain and spatial domain were investigated. Where Mean Absolute Value (MAV), Integrated Absolute Value (IAV), Zero Crossing (ZC), Root Mean Square (RMS), Waveform Length (WL) and Slope Sign Change (SSC) are the used time domain features.
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Papers by Eng. Ammar Alhamadani