Feature selection for brain-computer interface using nearest neighbor information

Yung Kyun Noh, Byoung-Kyong Min

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We consider the feature selection problem for a braincomputer interface (BCI). A BCI collects data from sensors, and the data are discriminated using information in a high-dimensional space. We show how relevant features in a high dimensional space can be selected using a simple nearest neighbor method for estimating an information-theoretic measure, Jensen-Shannon divergence. Conventional nonparametric estimation using nearest neighbors already works very well for the feature selection problem and outperforms many other methods. In this paper, we show how this nearest neighbor method can be further exploited by properly trimming the non-informative direction for a distance calculation, and estimate the Jensen-Shannon divergence more accurately. Through experiments with synthetic data, we show how the proposed method outperforms a conventional nearest neighbor method as well as other feature selection methods with a large margin.

Original languageEnglish
Title of host publication2014 International Winter Workshop on Brain-Computer Interface, BCI 2014
PublisherIEEE Computer Society
DOIs
Publication statusPublished - 2014 Jan 1
Event2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 - Gangwon, Korea, Republic of
Duration: 2014 Feb 172014 Feb 19

Other

Other2014 International Winter Workshop on Brain-Computer Interface, BCI 2014
CountryKorea, Republic of
CityGangwon
Period14/2/1714/2/19

Keywords

  • component
  • feature selection
  • information theory
  • Jensen-Shannon divergence
  • nearest neighbor

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Human Factors and Ergonomics

Fingerprint Dive into the research topics of 'Feature selection for brain-computer interface using nearest neighbor information'. Together they form a unique fingerprint.

  • Cite this

    Noh, Y. K., & Min, B-K. (2014). Feature selection for brain-computer interface using nearest neighbor information. In 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 [6782553] IEEE Computer Society. https://doi.org/10.1109/iww-BCI.2014.6782553