Literature DB >> 15382823

On the suitability of near-infrared (NIR) systems for next-generation brain-computer interfaces.

Shirley Coyle1, Tomás Ward, Charles Markham, Gary McDarby.   

Abstract

A brain-computer interface (BCI) gives those suffering from neuromuscular impairments a means to interact and communicate with their surrounding environment. A BCI translates physiological signals, typically electrical, detected from the brain to control an output device. A significant problem with current BCIs is the lengthy training periods involved for proficient usage, which can often lead to frustration and anxiety on the part of the user. Ultimately this can lead to abandonment of the device. The primary reason for this is that relatively indirect measures of cognitive function, as can be gleaned from the electroencephalogram (EEG), are harnessed. A more suitable and usable interface would need to measure cognitive function more directly. In order to do this, new measurement modalities, signal acquisition and processing, and translation algorithms need to be addressed. In this paper, we propose a novel approach, using non-invasive near-infrared imaging technology to develop a user-friendly optical BCI. As an alternative to the traditional EEG-based devices, we have used practical non-invasive optical techniques to detect characteristic haemodynamic responses due to motor imagery and consequently created an accessible BCI that is simple to attach and requires little user training.

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Year:  2004        PMID: 15382823     DOI: 10.1088/0967-3334/25/4/003

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  53 in total

1.  NIRS-based hyperscanning reveals increased interpersonal coherence in superior frontal cortex during cooperation.

Authors:  Xu Cui; Daniel M Bryant; Allan L Reiss
Journal:  Neuroimage       Date:  2011-09-10       Impact factor: 6.556

Review 2.  Brain computer interfaces, a review.

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

3.  A quantitative comparison of NIRS and fMRI across multiple cognitive tasks.

Authors:  Xu Cui; Signe Bray; Daniel M Bryant; Gary H Glover; Allan L Reiss
Journal:  Neuroimage       Date:  2010-11-01       Impact factor: 6.556

4.  Single-trial classification of antagonistic oxyhemoglobin responses during mental arithmetic.

Authors:  Günther Bauernfeind; Reinhold Scherer; Gert Pfurtscheller; Christa Neuper
Journal:  Med Biol Eng Comput       Date:  2011-06-24       Impact factor: 2.602

5.  Can time-resolved NIRS provide the sensitivity to detect brain activity during motor imagery consistently?

Authors:  Androu Abdalmalak; Daniel Milej; Mamadou Diop; Mahsa Shokouhi; Lorina Naci; Adrian M Owen; Keith St Lawrence
Journal:  Biomed Opt Express       Date:  2017-03-13       Impact factor: 3.732

6.  Usability and performance-informed selection of personalized mental tasks for an online near-infrared spectroscopy brain-computer interface.

Authors:  Sabine Weyand; Larissa Schudlo; Kaori Takehara-Nishiuchi; Tom Chau
Journal:  Neurophotonics       Date:  2015-05-12       Impact factor: 3.593

7.  Classification of hemodynamic responses associated with force and speed imagery for a brain-computer interface.

Authors:  Xuxian Yin; Baolei Xu; Changhao Jiang; Yunfa Fu; Zhidong Wang; Hongyi Li; Gang Shi
Journal:  J Med Syst       Date:  2015-03-03       Impact factor: 4.460

8.  An inter-subject model to reduce the calibration time for motion imagination-based brain-computer interface.

Authors:  Yijun Zou; Xingang Zhao; Yaqi Chu; Yiwen Zhao; Weiliang Xu; Jianda Han
Journal:  Med Biol Eng Comput       Date:  2018-11-29       Impact factor: 2.602

9.  An MEG-based brain-computer interface (BCI).

Authors:  Jürgen Mellinger; Gerwin Schalk; Christoph Braun; Hubert Preissl; Wolfgang Rosenstiel; Niels Birbaumer; Andrea Kübler
Journal:  Neuroimage       Date:  2007-03-27       Impact factor: 6.556

10.  P300-Based Brain-Computer Interface Communication: Evaluation and Follow-up in Amyotrophic Lateral Sclerosis.

Authors:  Stefano Silvoni; Chiara Volpato; Marianna Cavinato; Mauro Marchetti; Konstantinos Priftis; Antonio Merico; Paolo Tonin; Konstantinos Koutsikos; Fabrizio Beverina; Francesco Piccione
Journal:  Front Neurosci       Date:  2009-06-19       Impact factor: 4.677

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