Literature DB >> 36151487

Effective 2-D cursor control system using hybrid SSVEP + P300 visual brain computer interface.

Deepak Kapgate1.   

Abstract

A cursor control system based on brain-computer interface (BCI) provides efficient computer access. These systems operate without any muscular activity from the user. Conventional BCI-based cursor control systems have several limitations. Therefore, hybrid SSVEP + P300 visual BCI (VBCI)-based cursor control is needed to overcome these limitations. This paper explores the feasibility of using noninvasive hybrid SSVEP + P300 VBCI for cursor control as a universal form of computer access. The proposed cursor control system has a graphical user interface (GUI) design that simultaneously evokes both SSVEP and P300 signals in the human cortex. The performance metrics of the proposed system are compared with conventional SSVEP VBCI and P300 VBCI-based cursor control systems. The proposed hybrid SSVEP + P300 BCI-based cursor control system achieves a maximum accuracy of 97.51% with a 27.15 bit/min information transfer rate (ITR). The results proved that the proposed system performed more efficiently than other systems. The proposed system was tested in a noisy environment and found to be suitable for real-world applications.
© 2022. International Federation for Medical and Biological Engineering.

Entities:  

Keywords:  BCI-based cursor control system; Hybrid SSVEP + P300 BCI; P300 signal; SSVEP signal

Mesh:

Year:  2022        PMID: 36151487     DOI: 10.1007/s11517-022-02675-0

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   3.079


  11 in total

1.  Conversion of EEG activity into cursor movement by a brain-computer interface (BCI).

Authors:  Georg E Fabiani; Dennis J McFarland; Jonathan R Wolpaw; Gert Pfurtscheller
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2004-09       Impact factor: 3.802

2.  An EEG-based BCI system for 2-D cursor control by combining Mu/Beta rhythm and P300 potential.

Authors:  Yuanqing Li; Jinyi Long; Tianyou Yu; Zhuliang Yu; Chuanchu Wang; Haihong Zhang; Cuntai Guan
Journal:  IEEE Trans Biomed Eng       Date:  2010-07-08       Impact factor: 4.538

3.  Emotional faces boost up steady-state visual responses for brain-computer interface.

Authors:  Hovagim Bakardjian; Toshihisa Tanaka; Andrzej Cichocki
Journal:  Neuroreport       Date:  2011-02-16       Impact factor: 1.837

4.  Sensorimotor rhythm-based brain-computer interface (BCI): feature selection by regression improves performance.

Authors:  Dennis J McFarland; Jonathan R Wolpaw
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2005-09       Impact factor: 3.802

5.  Brain-computer interfaces for 1-D and 2-D cursor control: designs using volitional control of the EEG spectrum or steady-state visual evoked potentials.

Authors:  Leonard J Trejo; Roman Rosipal; Bryan Matthews
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2006-06       Impact factor: 3.802

6.  P300-based BCI mouse with genetically-optimized analogue control.

Authors:  Luca Citi; Riccardo Poli; Caterina Cinel; Francisco Sepulveda
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2008-02       Impact factor: 3.802

Review 7.  Visual and auditory brain-computer interfaces.

Authors:  Shangkai Gao; Yijun Wang; Xiaorong Gao; Bo Hong
Journal:  IEEE Trans Biomed Eng       Date:  2014-05       Impact factor: 4.538

Review 8.  Connecting cortex to machines: recent advances in brain interfaces.

Authors:  John P Donoghue
Journal:  Nat Neurosci       Date:  2002-11       Impact factor: 24.884

9.  Neuronal ensemble control of prosthetic devices by a human with tetraplegia.

Authors:  Leigh R Hochberg; Mijail D Serruya; Gerhard M Friehs; Jon A Mukand; Maryam Saleh; Abraham H Caplan; Almut Branner; David Chen; Richard D Penn; John P Donoghue
Journal:  Nature       Date:  2006-07-13       Impact factor: 49.962

10.  Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans.

Authors:  Jonathan R Wolpaw; Dennis J McFarland
Journal:  Proc Natl Acad Sci U S A       Date:  2004-12-07       Impact factor: 11.205

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