Theoretical analysis of xDAWN algorithm: application to an efficient sensor selection in a P300 BCI - Archive ouverte HAL Access content directly
Conference Papers Year : 2011

Theoretical analysis of xDAWN algorithm: application to an efficient sensor selection in a P300 BCI

(1) , (1) , (2) , (3) , (3)
1
2
3

Abstract

A Brain-Computer Interface (BCI) is a specific type of human-machine interface that enables communication between a subject/patient and a computer by a direct control from the decoding of brain activity. To improve the ergonomics and to minimize the cost of such a BCI, reducing the number of electrodes is mandatory. A theoretical analysis of the subjacent model induced by the BCI paradigm leads to derive a closed form theoretical expression of the spatial filters which maximize the signal to signal-plus-noise ratio. Moreover, this new formulation is useful to improve a previously introduced method to automatically select relevant sensors. Experimental results on 20 subjects show that the proposed method is efficient to select the most relevant sensors: from 32 down to 8 sensors, the loss in classification accuracy is less than 2%. Furthermore, the computational time required to rank the 32 sensors is reduced by a 4.6 speed up factor allowing dynamical monitoring of sensor relevance as a marker of the user's mental state.
Fichier principal
Vignette du fichier
2011_EUSIPCO.pdf (313.38 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00619997 , version 1 (07-09-2011)

Identifiers

  • HAL Id : hal-00619997 , version 1

Cite

Bertrand Rivet, Hubert Cecotti, Antoine Souloumiac, Emmanuel Maby, Jérémie Mattout. Theoretical analysis of xDAWN algorithm: application to an efficient sensor selection in a P300 BCI. EUSIPCO 2011 - 19th European Signal Processing Conference, Aug 2011, Barcelone, Spain. pp.1382-1386. ⟨hal-00619997⟩
404 View
766 Download

Share

Gmail Facebook Twitter LinkedIn More