Literature DB >> 21436524

A hybrid brain-computer interface based on the fusion of electroencephalographic and electromyographic activities.

Robert Leeb1, Hesam Sagha, Ricardo Chavarriaga, José Del R Millán.   

Abstract

Hybrid brain-computer interfaces (BCIs) are representing a recent approach to develop practical BCIs. In such a system disabled users are able to use all their remaining functionalities as control possibilities in parallel with the BCI. Sometimes these people have residual activity of their muscles. Therefore, in the presented hybrid BCI framework we want to explore the parallel usage of electroencephalographic (EEG) and electromyographic (EMG) activity, whereby the control abilities of both channels are fused. Results showed that the participants could achieve a good control of their hybrid BCI independently of their level of muscular fatigue. Thereby the multimodal fusion approach of muscular and brain activity yielded better and more stable performance compared to the single conditions. Even in the case of an increasing muscular fatigue a good control (moderate and graceful degradation of the performance compared to the non-fatigued case) and a smooth handover could be achieved. Therefore, such systems allow the users a very reliable hybrid BCI control although they are getting more and more exhausted or fatigued during the day.

Entities:  

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Year:  2011        PMID: 21436524     DOI: 10.1088/1741-2560/8/2/025011

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  32 in total

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4.  Hierarchical Graphical Models for Context-Aware Hybrid Brain-Machine Interfaces.

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Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2018-07

5.  Decoding with limited neural data: a mixture of time-warped trajectory models for directional reaches.

Authors:  Elaine A Corbett; Eric J Perreault; Konrad P Körding
Journal:  J Neural Eng       Date:  2012-04-10       Impact factor: 5.379

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7.  Tools for Brain-Computer Interaction: A General Concept for a Hybrid BCI.

Authors:  Gernot R Müller-Putz; Christian Breitwieser; Febo Cincotti; Robert Leeb; Martijn Schreuder; Francesco Leotta; Michele Tavella; Luigi Bianchi; Alex Kreilinger; Andrew Ramsay; Martin Rohm; Max Sagebaum; Luca Tonin; Christa Neuper; José Del R Millán
Journal:  Front Neuroinform       Date:  2011-11-24       Impact factor: 4.081

8.  Switching between Manual Control and Brain-Computer Interface Using Long Term and Short Term Quality Measures.

Authors:  Alex Kreilinger; Vera Kaiser; Christian Breitwieser; John Williamson; Christa Neuper; Gernot R Müller-Putz
Journal:  Front Neurosci       Date:  2012-01-18       Impact factor: 4.677

9.  A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.

Authors:  Bongjae Choi; Sungho Jo
Journal:  PLoS One       Date:  2013-09-04       Impact factor: 3.240

10.  Homology Characteristics of EEG and EMG for Lower Limb Voluntary Movement Intention.

Authors:  Xiaodong Zhang; Hanzhe Li; Zhufeng Lu; Gui Yin
Journal:  Front Neurorobot       Date:  2021-06-18       Impact factor: 2.650

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