CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

k- NN based Object Recognition System using Brain Computer Interface

by Anupama H S, Cauvery N K, Lingaraju G M
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 2
Year of Publication: 2015
Authors: Anupama H S, Cauvery N K, Lingaraju G M
10.5120/21202-3878

Anupama H S, Cauvery N K, Lingaraju G M . k- NN based Object Recognition System using Brain Computer Interface. International Journal of Computer Applications. 120, 2 ( June 2015), 35-38. DOI=10.5120/21202-3878

@article{ 10.5120/21202-3878,
author = { Anupama H S, Cauvery N K, Lingaraju G M },
title = { k- NN based Object Recognition System using Brain Computer Interface },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 2 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 35-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number2/21202-3878/ },
doi = { 10.5120/21202-3878 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:05:13.418171+05:30
%A Anupama H S
%A Cauvery N K
%A Lingaraju G M
%T k- NN based Object Recognition System using Brain Computer Interface
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 2
%P 35-38
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Brain Computer Interface is a device which provides the communication between the human brain and the computer. This paper provides an idea of object recognition system using Principal Component Analysis (PCA) and Singular Value Decomposition (SVD). This is used to recognize the object by analyzing EEG signals in real time. K-Nearest Neighbors algorithm is implemented to classify the intended object. Multiple training sets and users are taken into account during the experiment and the efficiency of the algorithm is calculated.

References
  1. Anupama. H. S, N. K. Cauvery, Lingaraju. G. M, "Brain computer interface and its types - a study", International Journal of Advances in Engineering & Technology, May 2012.
  2. Anupama. H. S, N. K. Cauvery, Lingaraju. G. M, "Real Time EEG Based Object Recognition system using Barin Computer Interface", Nov 2014, pg no-1046-1051.
  3. G. Lorina Naci, Martin M. Monti, Damian Cruse, Andrea Ku¨ bler, Bettina Sorger, Rainer Goebel, Boris Kotchoubey, and Adrian M. Owen, "Brain–Computer Interfaces for communication with nonresponsive patients", unpublished.
  4. W. Lutzenberger, T. Elbert, N. Birbaumer, W. J. Ray, and H. Schupp, "The scalp distribution of the fractal dimension of the EEG and its variation with mental tasks," Brain Topography, vol. 5, 1992, pp. 27-34.
  5. About Emotive Epoc. http://emotiv. com/epoc/
  6. Nicolas-Alonso, Luis Fernando, and Jaime Gomez-Gil. "Brain computer interfaces, a review. " Sensors 12, no. 2 (2012): 1211-1279.
  7. Yisi Liu, Olga Sourina, and Minh Khoa Nguyen, "Real-time EEG-based Human Emotion Recognition and Visualization," unpublished.
  8. Emotiv Software Development Kit, User Manual for Release 1. 0. 0. 3.
  9. Mitchell, T. M. , "Machine Learning", McGraw-Hill, New York, NY, 2nd Edition, 1997.
  10. Ravindra Changala, Annapurna Gummadi, G Yedukondalu, UNPG Raju ,"Classification by Decision Tree Induction Algorithm to Learn Decision Trees from the class-Labeled Training Tuples ", International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 4, April 2012.
  11. Fayyad, U. M. , Irani, K. B. , "On the handling of continuous-valued attributes in decision tree generation," Machine Learning, 1992.
  12. J. Goleberger, S. Roweis, G. Hinton, and R. Salahhutidnov, "neighbourhood components analysis", Advances in Neural Information Processing Systems 17, Cambridge, MA, 2005.
  13. Lal, T. N, Schr¨oder, M. T, Hinterberger, J. , Weston, M. , Bogdan, N. , Birbaumer, B and Sch¨olkopf, "Support Vector Channel Selection in BCI", in the proceedings of IEEE Transactions on Biomedical Engineering, Special Issue on Brain-Computer Interfaces, June 2004.
  14. Mason, Steven G. , and Gary E. Birch. "A general framework for brain-computer interface design. " Neural Systems and Rehabilitation Engineering, IEEE Transactions on 11, no. 1 (2003): 70-85.
  15. Zhang, Hao, et al. "SVM-KNN: Discriminative nearest neighbor classification for visual category recognition. " Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on. Vol. 2. IEEE, 2006.
  16. Python. https://docs. python. org/2. 7/library
  17. K-NearestNeighbour. http://saravananthirumuruganathan. wordpress. com/2010/05/17/a-detailed-introduction-to-k-nearest-neighbor-knn-algorithm/
Index Terms

Computer Science
Information Sciences

Keywords

Brain Computer Interface Invasive and Non-Invasive Electroencephalography (EEG) Emotive epoc K-Nearest Neighbors Object recognition

Powered by PhDFocusTM