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[PDF] Top 20 Subject-Specific Channel Selection Using Time Information for Motor Imagery Brain–Computer Interfaces

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Subject-Specific Channel Selection Using Time Information for Motor Imagery Brain–Computer Interfaces

Subject-Specific Channel Selection Using Time Information for Motor Imagery Brain–Computer Interfaces

... essential for designing a portable braincomputer interface system for daily ...spatial information without optimization of time segment for ...novel ... Voir le document complet

15

Ensemble learning for brain computer-interface using uncooperative democratic echo state communities

Ensemble learning for brain computer-interface using uncooperative democratic echo state communities

... NTRODUCTION Brain-Computer Interfaces (BCIs) aim at establishing a direct communication pathway between users will and electronic ...severe motor diseases with a tool to re- store ... Voir le document complet

7

A Study on the Effect of Electrical Stimulation During Motor Imagery Learning in Brain-Computer Interfacing

A Study on the Effect of Electrical Stimulation During Motor Imagery Learning in Brain-Computer Interfacing

... schematic time representation of the experimental task displayed to the ...on motor imagery suggests the presence of ERD/ERS in the µ-rhythm (8-12 Hz) and central β band (16-24 ...Hz using an ... Voir le document complet

7

Time-frequency Selection in Two Bipolar Channels for Improving the Classification of Motor Imagery EEG

Time-frequency Selection in Two Bipolar Channels for Improving the Classification of Motor Imagery EEG

... spatial information, time and frequency informa- tion is also very important for classification, because motor imagery elicits ERD/ERS in specific bands within specific ... Voir le document complet

5

EEG signal analysis for brain-computer interfaces for large public applications

EEG signal analysis for brain-computer interfaces for large public applications

... of brain function ...record motor imagery ...identify subject-specific time-frequency characteristics, so as to extract effective band power ...to time-frequency selec- ... Voir le document complet

191

Subject-specific time-frequency selection for multi-class motor imagery-based BCIs using few Laplacian EEG channels

Subject-specific time-frequency selection for multi-class motor imagery-based BCIs using few Laplacian EEG channels

... [54] T. Solis-Escalante, G. Müller-Putz, G. Pfurtscheller, Overt foot movement detection in one single Laplacian EEG derivation, J. Neurosci. Methods 175 (2008) 148–153. [55] S. Fitzgibbon, D. DeLosAngeles, T. Lewis, D. ... Voir le document complet

11

Subject-specific channel selection for classification of motor imagery electroencephalographic data

Subject-specific channel selection for classification of motor imagery electroencephalographic data

... Terms— Brain computer interfaces, electroencephalog- raphy, biomedical signal processing, machine learning ...INTRODUCTION Brain-computer interface (BCI) systems capture subject’s ... Voir le document complet

5

The bidirectional algorithm for channel selection using a two-radio model

The bidirectional algorithm for channel selection using a two-radio model

... the channel numbers consecutively on a ring of size m, as in Figure ...to channel zero, scanning channels clockwise ...to channel three, scanning counterclockwise ...the channel ring, scanning ... Voir le document complet

6

Channel selection using a multiple radio model

Channel selection using a multiple radio model

... room for new services and accommodating ...used. For instance, a limited number of frequencies allocated to television, space exploration and defense are occupied every-time, ...spectrum. For ... Voir le document complet

37

Using Riemannian geometry for SSVEP-based Brain Computer Interface

Using Riemannian geometry for SSVEP-based Brain Computer Interface

... computed for the different estimators and trial ...reference for improvement, as this is the most popular es- timator in the ...method for longer trials. However for trial lengths compatible ... Voir le document complet

30

Towards next generation human-computer interaction -- brain-computer interfaces: applications and challenges

Towards next generation human-computer interaction -- brain-computer interfaces: applications and challenges

... nizing brain signals corresponding to the imagination (motor imagery) of hand ...Several brain signal datasets for classifying motor imagery are available in BCI competi- ... Voir le document complet

3

A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update

A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update

... DNNs for EEG-based BCIs have been rather unconvincing in demonstrating their actual relevance and superiority to state-of-the-art BCI methods in ...parameters for the state-of-the- art competitors or with ... Voir le document complet

56

Automatic motor task selection via a bandit algorithm for a brain-controlled button

Automatic motor task selection via a bandit algorithm for a brain-controlled button

... Centre de recherche INRIA Paris – Rocquencourt : Domaine de Voluceau - Rocquencourt - BP 105 - 78153 Le Chesnay Cedex Centre de recherche INRIA Rennes – Bretagne Atlantique : IRISA, Camp[r] ... Voir le document complet

18

Channel Selection Procedure using Riemannian distance for BCI applications

Channel Selection Procedure using Riemannian distance for BCI applications

... new channel selection procedure based on the Riemannian distance between co- variance ...perspectives for cost-effective attractive EEG cap design. Patient specific and application ... Voir le document complet

5

Adaptive machine  learning methods for event related potential-based brain computer interfaces

Adaptive machine learning methods for event related potential-based brain computer interfaces

... all for every moment: Theo, Ragini, Demian, Marco, Rutger, Brahim, Kai, Nathanael, Amandine, Mauro, Patryk, Abib, Matteo, Ivana, Sara, Romain, It’s been an honor and a ...you for putting up with me all this ... Voir le document complet

169

Reducing Calibration Time for the P300 Brain-Computer Interface Speller

Reducing Calibration Time for the P300 Brain-Computer Interface Speller

... severe motor disabilities who are unable to com- municate through any other ...means. For these per- sons, a BCI is the only way to communicate and the main challenge is to have a functional ...the ... Voir le document complet

6

Uncued brain-computer interfaces: a variational hidden markov model of mental state dynamics

Uncued brain-computer interfaces: a variational hidden markov model of mental state dynamics

... HAL Id: hal-00384879 https://hal.archives-ouvertes.fr/hal-00384879 Submitted on 16 May 2009 HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, ... Voir le document complet

7

Looking for cortical patterns of successful motor imagery-based BCI learning

Looking for cortical patterns of successful motor imagery-based BCI learning

... the subject level via a paired t-test. Statistics were corrected for multiple comparisons using the cluster approach [24], [34], with a statistical threshold to ...by using the sum of the ... Voir le document complet

7

IoT-enabled Channel Selection Approach for WBANs

IoT-enabled Channel Selection Approach for WBANs

... frames, for interference ...module for selecting a different ...stable channel for interfering sensors that will be used later within the FBTDMA frame for data ... Voir le document complet

8

Comparative Study of Band-Power Extraction Techniques for Motor Imagery Classification

Comparative Study of Band-Power Extraction Techniques for Motor Imagery Classification

... in time and frequency, so the pre-filtering does not necessary help in this ...penalizing for real-time applications. Table I mentions “hp” for a high-pass filter where the 0Hz component is ... Voir le document complet

7

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