Literature DB >> 12899263

Real-world applications for brain-computer interface technology.

Melody M Moore1.   

Abstract

The mission of the Georgia State University BrainLab is to create and adapt methods of human-computer interaction that will allow brain-computer interface (BCI) technologies to effectively control real-world applications. Most of the existing BCI applications were designed largely for training and demonstration purposes. Our goal is to research ways of transitioning BCI control skills learned in training to real-world scenarios. Our research explores some of the problems and challenges of combining BCI outputs with human-computer interface paradigms in order to achieve optimal interaction. We utilize a variety of application domains to compare and validate BCI interactions, including communication, environmental control, neural prosthetics, and creative expression. The goal of this research is to improve quality of life for those with severe disabilities.

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Year:  2003        PMID: 12899263     DOI: 10.1109/TNSRE.2003.814433

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  16 in total

Review 1.  Brain computer interfaces, a review.

Authors:  Luis Fernando Nicolas-Alonso; Jaime Gomez-Gil
Journal:  Sensors (Basel)       Date:  2012-01-31       Impact factor: 3.576

2.  Evaluation of a wireless wearable tongue-computer interface by individuals with high-level spinal cord injuries.

Authors:  Xueliang Huo; Maysam Ghovanloo
Journal:  J Neural Eng       Date:  2010-03-23       Impact factor: 5.379

3.  Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects.

Authors:  Joseph N Mak; Jonathan R Wolpaw
Journal:  IEEE Rev Biomed Eng       Date:  2009

4.  A P300-based brain-computer interface aimed at operating electronic devices at home for severely disabled people.

Authors:  Rebeca Corralejo; Luis F Nicolás-Alonso; Daniel Alvarez; Roberto Hornero
Journal:  Med Biol Eng Comput       Date:  2014-08-28       Impact factor: 2.602

Review 5.  Functional source separation and hand cortical representation for a brain-computer interface feature extraction.

Authors:  Franca Tecchio; Camillo Porcaro; Giulia Barbati; Filippo Zappasodi
Journal:  J Physiol       Date:  2007-03-01       Impact factor: 5.182

6.  Command detection and classification in tongue drive assistive technology.

Authors:  Elnaz Banan Sadeghian; Xueliang Huo; Maysam Ghovanloo
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

7.  A magneto-inductive sensor based wireless tongue-computer interface.

Authors:  Xueliang Huo; Jia Wang; Maysam Ghovanloo
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2008-10       Impact factor: 3.802

8.  The Promise of Neurotechnology in Clinical Translational Science.

Authors:  Susan W White; John A Richey; Denis Gracanin; Martha Ann Bell; Stephen LaConte; Marika Coffman; Andrea Trubanova; Inyoung Kim
Journal:  Clin Psychol Sci       Date:  2014-10-17

9.  Asynchronous BCI control using high-frequency SSVEP.

Authors:  Pablo F Diez; Vicente A Mut; Enrique M Avila Perona; Eric Laciar Leber
Journal:  J Neuroeng Rehabil       Date:  2011-07-14       Impact factor: 4.262

10.  Audio-visual feedback improves the BCI performance in the navigational control of a humanoid robot.

Authors:  Emmanuele Tidoni; Pierre Gergondet; Abderrahmane Kheddar; Salvatore M Aglioti
Journal:  Front Neurorobot       Date:  2014-06-17       Impact factor: 2.650

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