Feasibility of error-related potential detection as novelty detection problem in P300 mind spelling

Nikolay V. Manyakov; Adrien Combaz; Nikolay Chumerin; Arne Robben; Marijn van Vliet; Marc M. Van Hulle

doi:10.1007/978-3-642-29350-4-35

Feasibility of error-related potential detection as novelty detection problem in P300 mind spelling

Nikolay V. Manyakov^*, Adrien Combaz, Nikolay Chumerin, Arne Robben, Marijn van Vliet, Marc M. Van Hulle

^*Corresponding author for this work

Not published at Aalto University

KU Leuven

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

2 Citations (Scopus)

Abstract

In this paper, we report on the feasibility of the Error-Related Potential (ErrP) integration in a particular type of Brain-Computer Interface (BCI) called the P300 Mind Speller. With the latter, the subject can type text only by means of his/her brain activity without having to rely on speech or muscular activity. Hereto, electroencephalography (EEG) signals are recorded from the subject's scalp. But, as with any BCI paradigm, decoding mistakes occur, and when they do, an EEG potential is evoked, known as the Error-Related Potential (ErrP), locked to the subject's realization of the mistake. When the BCI would be able to also detect the ErrP, the last typed character could be automatically corrected. However, since the P300 Mind Speller is optimized to correctly operate in the first place, we have much less ErrP's than responses to correctly typed characters. In fact, exactly because it is supposed to be a rare phenomenon, we advocate that ErrP detection can be treated as a novelty detection problem. We consider in this paper different one-class classification algorithms based on novelty detection together with a correction algorithm for the P300 Mind Speller.

Original language	English
Title of host publication	Artificial Intelligence and Soft Computing - 11th International Conference, ICAISC 2012, Proceedings
Pages	293-301
Number of pages	9
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-29350-4-35
Publication status	Published - 21 May 2012
MoE publication type	A4 Conference publication
Event	International Conference on Artificial Intelligence and Soft Computing - Zakopane, Poland Duration: 29 Apr 2012 → 3 May 2012 Conference number: 11

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7268 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Artificial Intelligence and Soft Computing
Abbreviated title	ICAISC
Country/Territory	Poland
City	Zakopane
Period	29/04/2012 → 03/05/2012

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10.1007/978-3-642-29350-4-35

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Manyakov, N. V., Combaz, A., Chumerin, N., Robben, A., van Vliet, M., & Van Hulle, M. M. (2012). Feasibility of error-related potential detection as novelty detection problem in P300 mind spelling. In Artificial Intelligence and Soft Computing - 11th International Conference, ICAISC 2012, Proceedings (PART 2 ed., pp. 293-301). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7268 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-29350-4-35

Manyakov, Nikolay V. ; Combaz, Adrien ; Chumerin, Nikolay et al. / Feasibility of error-related potential detection as novelty detection problem in P300 mind spelling. Artificial Intelligence and Soft Computing - 11th International Conference, ICAISC 2012, Proceedings. PART 2. ed. 2012. pp. 293-301 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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abstract = "In this paper, we report on the feasibility of the Error-Related Potential (ErrP) integration in a particular type of Brain-Computer Interface (BCI) called the P300 Mind Speller. With the latter, the subject can type text only by means of his/her brain activity without having to rely on speech or muscular activity. Hereto, electroencephalography (EEG) signals are recorded from the subject's scalp. But, as with any BCI paradigm, decoding mistakes occur, and when they do, an EEG potential is evoked, known as the Error-Related Potential (ErrP), locked to the subject's realization of the mistake. When the BCI would be able to also detect the ErrP, the last typed character could be automatically corrected. However, since the P300 Mind Speller is optimized to correctly operate in the first place, we have much less ErrP's than responses to correctly typed characters. In fact, exactly because it is supposed to be a rare phenomenon, we advocate that ErrP detection can be treated as a novelty detection problem. We consider in this paper different one-class classification algorithms based on novelty detection together with a correction algorithm for the P300 Mind Speller.",

author = "Manyakov, {Nikolay V.} and Adrien Combaz and Nikolay Chumerin and Arne Robben and {van Vliet}, Marijn and {Van Hulle}, {Marc M.}",

year = "2012",

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Manyakov, NV, Combaz, A, Chumerin, N, Robben, A, van Vliet, M & Van Hulle, MM 2012, Feasibility of error-related potential detection as novelty detection problem in P300 mind spelling. in Artificial Intelligence and Soft Computing - 11th International Conference, ICAISC 2012, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7268 LNAI, pp. 293-301, International Conference on Artificial Intelligence and Soft Computing, Zakopane, Poland, 29/04/2012. https://doi.org/10.1007/978-3-642-29350-4-35

Feasibility of error-related potential detection as novelty detection problem in P300 mind spelling. / Manyakov, Nikolay V.; Combaz, Adrien; Chumerin, Nikolay et al.
Artificial Intelligence and Soft Computing - 11th International Conference, ICAISC 2012, Proceedings. PART 2. ed. 2012. p. 293-301 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7268 LNAI, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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N2 - In this paper, we report on the feasibility of the Error-Related Potential (ErrP) integration in a particular type of Brain-Computer Interface (BCI) called the P300 Mind Speller. With the latter, the subject can type text only by means of his/her brain activity without having to rely on speech or muscular activity. Hereto, electroencephalography (EEG) signals are recorded from the subject's scalp. But, as with any BCI paradigm, decoding mistakes occur, and when they do, an EEG potential is evoked, known as the Error-Related Potential (ErrP), locked to the subject's realization of the mistake. When the BCI would be able to also detect the ErrP, the last typed character could be automatically corrected. However, since the P300 Mind Speller is optimized to correctly operate in the first place, we have much less ErrP's than responses to correctly typed characters. In fact, exactly because it is supposed to be a rare phenomenon, we advocate that ErrP detection can be treated as a novelty detection problem. We consider in this paper different one-class classification algorithms based on novelty detection together with a correction algorithm for the P300 Mind Speller.

AB - In this paper, we report on the feasibility of the Error-Related Potential (ErrP) integration in a particular type of Brain-Computer Interface (BCI) called the P300 Mind Speller. With the latter, the subject can type text only by means of his/her brain activity without having to rely on speech or muscular activity. Hereto, electroencephalography (EEG) signals are recorded from the subject's scalp. But, as with any BCI paradigm, decoding mistakes occur, and when they do, an EEG potential is evoked, known as the Error-Related Potential (ErrP), locked to the subject's realization of the mistake. When the BCI would be able to also detect the ErrP, the last typed character could be automatically corrected. However, since the P300 Mind Speller is optimized to correctly operate in the first place, we have much less ErrP's than responses to correctly typed characters. In fact, exactly because it is supposed to be a rare phenomenon, we advocate that ErrP detection can be treated as a novelty detection problem. We consider in this paper different one-class classification algorithms based on novelty detection together with a correction algorithm for the P300 Mind Speller.

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Manyakov NV, Combaz A, Chumerin N, Robben A, van Vliet M, Van Hulle MM. Feasibility of error-related potential detection as novelty detection problem in P300 mind spelling. In Artificial Intelligence and Soft Computing - 11th International Conference, ICAISC 2012, Proceedings. PART 2 ed. 2012. p. 293-301. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-29350-4-35

Feasibility of error-related potential detection as novelty detection problem in P300 mind spelling

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