Literature DB >> 22255356

EEG auditory steady state responses classification for the novel BCI.

Hiroshi Higashi1, Tomasz M Rutkowski, Yoshikazu Washizawa, Andrzej Cichocki, Toshihisa Tanaka.   

Abstract

An auditory modality brain computer interface (BCI) is a novel and interesting paradigm in neurotechnology applications. The paper presents a concept of auditory steady state responses (ASSR) utilization for the novel BCI paradigm. Two EEG feature extraction approaches based on a bandpass filtering and an AR spectrum estimation are tested together with two classification schemes in order to validate the proposed auditory BCI paradigm. The resulting good classification scores of users intentional choices, of attending or not to the presented stimuli, support the hypothesis of the ASSR stimuli validity for a solid BCI paradigm.

Mesh:

Year:  2011        PMID: 22255356     DOI: 10.1109/IEMBS.2011.6091133

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  6 in total

Review 1.  Guidelines for Feature Matching Assessment of Brain-Computer Interfaces for Augmentative and Alternative Communication.

Authors:  Kevin M Pitt; Jonathan S Brumberg
Journal:  Am J Speech Lang Pathol       Date:  2018-08-06       Impact factor: 2.408

2.  A Novel Approach for Classifying Native Chinese and Malay Speaking Persons According to Cortical Auditory Evoked Responses.

Authors:  Ibrahim Amer Ibrahim; Hua-Nong Ting; Mahmoud Moghavvemi
Journal:  J Int Adv Otol       Date:  2019-04       Impact factor: 1.017

3.  An exploration of spatial auditory BCI paradigms with different sounds: music notes versus beeps.

Authors:  Minqiang Huang; Ian Daly; Jing Jin; Yu Zhang; Xingyu Wang; Andrzej Cichocki
Journal:  Cogn Neurodyn       Date:  2016-01-23       Impact factor: 5.082

4.  Effects of augmentative visual training on audio-motor mapping.

Authors:  Gabrielle L Hands; Eric Larson; Cara E Stepp
Journal:  Hum Mov Sci       Date:  2014-02-12       Impact factor: 2.161

5.  Combined Auditory and Vibrotactile Feedback for Human-Machine-Interface Control.

Authors:  Elias B Thorp; Eric Larson; Cara E Stepp
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2013-07-31       Impact factor: 3.802

6.  Categorical vowel perception enhances the effectiveness and generalization of auditory feedback in human-machine-interfaces.

Authors:  Eric Larson; Howard P Terry; Margaux M Canevari; Cara E Stepp
Journal:  PLoS One       Date:  2013-03-19       Impact factor: 3.240

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.