The possibility to develop compact, cost effective Brain-Computer Interface (BCI) solutions could take another step into transferring and spreading such technologies outside the labs. We present here our compact EEG hardware unit, and compare its performance against a commercial device. Then, we will demonstrate its use in a SSVEP-based BCI. The signal processing chain is briefly discussed. We also present a strategy for improving classification accuracy and false positives immunity by introducing an indicator related to the prediction confidence. A method for adaptively changing the length of the observed EEG window is also discussed. All these ideas are tested in an online, self-paced 4 class SSVEP-based BCI Moreover, tests are performed on the subject population as a whole, in an effort to produce subject-independent methods. Good performance is achieved, both in terms of true positive rate (>94%), as well as low false positive rate (0.26 min-1)

Exploitation of a compact, cost-effective EEG module for plug-and-play, SSVEP-based BCI / Mora, Niccolo'; DE MUNARI, Ilaria; Ciampolini, Paolo. - ELETTRONICO. - 2015-July:(2015), pp. 142-145. (Intervento presentato al convegno 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 tenutosi a Montpellier; France nel 22 April 2015 - 24 April 2015) [10.1109/NER.2015.7146580].

Exploitation of a compact, cost-effective EEG module for plug-and-play, SSVEP-based BCI

MORA, Niccolo';DE MUNARI, Ilaria;CIAMPOLINI, Paolo
2015-01-01

Abstract

The possibility to develop compact, cost effective Brain-Computer Interface (BCI) solutions could take another step into transferring and spreading such technologies outside the labs. We present here our compact EEG hardware unit, and compare its performance against a commercial device. Then, we will demonstrate its use in a SSVEP-based BCI. The signal processing chain is briefly discussed. We also present a strategy for improving classification accuracy and false positives immunity by introducing an indicator related to the prediction confidence. A method for adaptively changing the length of the observed EEG window is also discussed. All these ideas are tested in an online, self-paced 4 class SSVEP-based BCI Moreover, tests are performed on the subject population as a whole, in an effort to produce subject-independent methods. Good performance is achieved, both in terms of true positive rate (>94%), as well as low false positive rate (0.26 min-1)
2015
978-146736389-1
Exploitation of a compact, cost-effective EEG module for plug-and-play, SSVEP-based BCI / Mora, Niccolo'; DE MUNARI, Ilaria; Ciampolini, Paolo. - ELETTRONICO. - 2015-July:(2015), pp. 142-145. (Intervento presentato al convegno 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 tenutosi a Montpellier; France nel 22 April 2015 - 24 April 2015) [10.1109/NER.2015.7146580].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2797998
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