CLASSIFICATION OF EEG SIGNAL DATA USING HYBRID OF NEURO-FUZZY
Journal Title: International Journal of Engineering Sciences & Research Technology - Year 30, Vol 5, Issue 5
Abstract
Brain Computing interface technology represents a very highly growing field now-a-days for the research because of its unique applications system. In this paper we investigate classification methods of mental commands based on EEG data for BCI. The aim of this study is to present the work of training an artificial neural network (ANN) and Neuro-Fuzzy system provided with the data of a few healthy people who are in different mental states thinking about different activities like eating, walking or sleeping etc. It creates a mutual understanding between mind wave signals and the machine or surrounding system. In recent years’ applications based on the brain computing interface have gained a rather huge popularity because of its benefits like providing disabled people with a communication and control environment along with different types of movement restorations. It is proving to be revolutionary in the fields of medical and robotics, mind reading and remote communication etc. This paper puts forward the idea of using a classification algorithm based on a new hybrid approach using neural networks and fuzzy logic that can collectively detect and recognize the state of mind. The EEG brain signals tend to change as our mind state changes because of the voltage fluctuations resulting from the ionic currents in the neurons of the Brain. Features are extracted from the raw electroencephalography (EEG) data using data processing technique PPCA (probabilistic principle component analysis) and are fed to the classifier. The features extracted have been used to train the neural network by using the MATLAB toolbox (Bronzino, J. D. 2010). The work carried out here is to be later on compared with the outputs generated by using just a neural networks based classification algorithm.
Authors and Affiliations
Pratibha Rana*,
Keywords
Related Articles
- EP ID EP154131
- DOI 10.5281/zenodo.51017
- Views 67
- Downloads 0
Retrieving Best Web Pages Using Genetic Algorithm
This paper is concerned with extraction of top web pages from the search engine. We use an effective algorithm for extracting the target file from the search engine. The majority of search engines like Google prov...
Data Mining: Exploring Big Data Analytics, Hadoop and Mapreduce
Most internal auditors, especially those working in customer-focused industries, are aware of data mining and what it can do for an organization — reduce the cost of acquiring new customers and improve the sales r...
CYCLE TIME REDUCTION THROUGH MINIMIZATION OF TRANSPORTATION AT A PALLET MANUFACTURING COMPANY IN THE PHILIPPINES
In the pursuit of profitability and competitiveness, more companies are turning to lean manufacturing to reduce or eliminate waste in their production processes. Cycle Time Reduction to increase productivity was t...
A REVIEW OF SELECTIVE HARMONIC ELIMINATION TECHNIQUE BASED DIFFERENT OPTIMIZATION TECHNIQUES
The review of multilevel inverter utilization has been increased since the last decade. These new type of inverters are suitable in various high voltage and high power applications due to their ability to synthesiz...
SINGLE - PHASE INVERTER CONTROL TECHNIQUES FOR INTERFACING RENEWABLE ENERGY SOURCES
novel current control technique is proposed to control power flow from a renewable energy source feeding a microgrid system through a three - phase parallel - connected inverter. The parallel -...