A new feature and associated optimal spatial filter for EEG signal classification: Waveform Length - Archive ouverte HAL Access content directly
Conference Papers Year : 2012

A new feature and associated optimal spatial filter for EEG signal classification: Waveform Length

(1, 2)
1
2

Abstract

In this paper, we introduce Waveform Length (WL), a new feature for ElectroEncephaloGraphy (EEG) signal classification which measures the signal complexity. We also propose the Waveformlength Optimal Spatial Filter (WOSF), an optimal spatial filter to classify EEG signals based on WL features. Evaluations on 15 subjects suggested that WOSF with WL features provide performances that are competitive with that of Common Spatial Patterns (CSP) with Band Power (BP) features, CSP being the optimal spatial filter for BP features. More interestingly, our results suggested that combining WOSF with CSP features leads to classification performances that are significantly better than that of CSP alone (80% versus 77% average accuracy respectively).
Fichier principal
Vignette du fichier
lotte12.pdf (142.31 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00717617 , version 1 (13-07-2012)

Identifiers

  • HAL Id : hal-00717617 , version 1

Cite

Fabien Lotte. A new feature and associated optimal spatial filter for EEG signal classification: Waveform Length. International Conference on Pattern Recognition (ICPR), Nov 2012, Tsukuba, Japan. ⟨hal-00717617⟩

Collections

CNRS INRIA INRIA2
154 View
969 Download

Share

Gmail Facebook Twitter LinkedIn More