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Classification of finger pairs from one hand based on spectral features in human EEG.

Publication ,  Conference
Xiao, R; Ding, L
Published in: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
January 2014

Individual finger movements are well-articulated movements of fine body parts, the successful decoding of which can provide extra degrees of freedom to drive brain computer interface (BCI) applications. Past studies present some unique features revealed from spectral principal component analysis (PCA) on electrophysiological data recorded in both the surface of the brain (electrocorticography, ECoG) and the scalp (electroencephalography, EEG). These features contain discriminable information about fine individual finger movements from one hand. However, the efficacy of these spectral features has not been well investigated under the application of various classifiers. In the present study, we set out to investigate the topic using noninvasive human EEG. Several classifiers were chosen to explore their capability in capturing the spectral PC features to decode individual finger movements pairwisely from one hand using noninvasive EEG, aiming to investigate the efficacy of these spectral features in a decoding task.

Duke Scholars

Published In

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

DOI

EISSN

2694-0604

ISSN

2375-7477

Publication Date

January 2014

Volume

2014

Start / End Page

1263 / 1266

Related Subject Headings

  • Principal Component Analysis
  • Male
  • Humans
  • Hand
  • Fingers
  • Female
  • Electroencephalography
  • Algorithms
  • Adult
 

Citation

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Xiao, R., & Ding, L. (2014). Classification of finger pairs from one hand based on spectral features in human EEG. In Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference (Vol. 2014, pp. 1263–1266). https://doi.org/10.1109/embc.2014.6943827
Xiao, Ran, and Lei Ding. “Classification of finger pairs from one hand based on spectral features in human EEG.” In Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2014:1263–66, 2014. https://doi.org/10.1109/embc.2014.6943827.
Xiao R, Ding L. Classification of finger pairs from one hand based on spectral features in human EEG. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual International Conference. 2014. p. 1263–6.
Xiao, Ran, and Lei Ding. “Classification of finger pairs from one hand based on spectral features in human EEG.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, vol. 2014, 2014, pp. 1263–66. Epmc, doi:10.1109/embc.2014.6943827.
Xiao R, Ding L. Classification of finger pairs from one hand based on spectral features in human EEG. Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual International Conference. 2014. p. 1263–1266.

Published In

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

DOI

EISSN

2694-0604

ISSN

2375-7477

Publication Date

January 2014

Volume

2014

Start / End Page

1263 / 1266

Related Subject Headings

  • Principal Component Analysis
  • Male
  • Humans
  • Hand
  • Fingers
  • Female
  • Electroencephalography
  • Algorithms
  • Adult