Function Classification of EEG Signals Based on ANN
Rajesh Singla1, Neha Sharma2
1Rajesh Singla,is with the Instrumentation and Control Engineering Department, National Institute of Technology Jalandhar, PIN-144011, India
2Neha Sharma, is with the Instrumentation and Control Engineering Department, National Institute of Technology Jalandhar, PIN-144011, India
Manuscript received on December 08, 2014. | Revised Manuscript received on December 15, 2014. | Manuscript published on January 05, 2014. | PP: 158-163 | Volume-3 Issue-6, January 2014. | Retrieval Number: F2032013614/2014©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The motor imagery is limited in pattern variety, so in our work, six motor imageries including wrist, elbow, wrist rotation clockwise/anticlockwise and ankle backward/forward moment were used in this system. This paper described the auditory paradigm for recording of motor imagery signals and the relevant coefficient was used for signal analysis and recognition. EEG signals were decomposed into wavelet coefficients by discrete wavelet transform on which SVD technique is applied to get singular value used as feature vectors, presenting them into ANN classifier.
Keywords: BCI, EEG, Wavelet Transform, SVD,ANN