The Classification of Eye State by Using kNN and MLP Classification Models According to the EEG Signals
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2015, Vol 3, Issue 4
Abstract
What is widely used for classification of eye state to detect human’s cognition state is electroencephalography (EEG). In this study, the usage of EEG signals for online eye state detection method was proposed. In this study, EEG eye state dataset that is obtained from UCI machine learning repository database was used. Continuous 14 EEG measurements forms the basic of the dataset. The duration of the measurement is 117 seconds (each measurement has14980 sample). Weka (Waikato Environment for Knowledge Analysis) program is used for classification of eye state. Classification success was calculated by using k-Nearest Neighbors algorithm and multilayer perceptron neural networks models. The obtained success of classification methods were compared. The classification success rates were calculated for various number of neurons in the hidden layer of a multilayer perceptron neural network model. The highest classification success rate have been obtained when the number of neurons in the hidden layer was equal to 7. And it was 56.45%. The classification success rates were calculated with k-nearest neighbors algorithm for different neighbourhood values. The highest success was achieved in the classification made with kNN algorithm. In kNN models, the success rate for 3 nearest neighbor were calculated as 84.05%.
Authors and Affiliations
Kadir Sabancı| Karamanoglu Mehmetbey University, Faculty of Engineering, ElectricalElectronic Engineering Department, Karaman, Turkey, Murat Koklu*| Selcuk University, Faculty of Technology, Computer Engineering, Department, Konya, Turkey
Keywords
Related Articles
- EP ID EP785
- DOI 10.18201/ijisae.75836
- Views 477
- Downloads 44
An Analysis of Archive Update for Vector Evaluated Particle Swarm Optimization
Multi-objective optimization problem is commonly found in many real world problems. In computational intelligence, Particle Swarm Optimization (PSO) algorithm is a popular method in solving optimization problems. An exte...
A fuzzy approach for determination of prostate cancer
Goal of this study is a design of a fuzzy expert system, its application aspects in the medicine area and its introduction for calculation of numeric value of prostate cancer risk. For this aim it was used prostate speci...
The Principal Component Analysis Method Based Descriptor for Visual Object Classification
In the field of machine learning, which values / data labeling or recognition is done by pattern recognition. Visual object classification is an example of pattern recognition, which attempts prompt to assign each object...
Cloud Computing Environments Which Can Be Used in Health Education
At the present time, it is known that cloud computing technologies began to be used widely in information technology. The purpose of this study is to provide information about cloud technologies that can be used in healt...
A Low Cost Single Board Computer Based Mobile Robot Motion Planning System for Indoor Environments
In this study, a low cost, flexible and modular structure is proposed for mobile robot motion planning systems in an indoor environment with obstacles. In this system, the mobile robot has to follow the shortest path to...