Literature DB >> 21975364

Towards a system-paced near-infrared spectroscopy brain-computer interface: differentiating prefrontal activity due to mental arithmetic and mental singing from the no-control state.

Sarah D Power1, Azadeh Kushki, Tom Chau.   

Abstract

Near-infrared spectroscopy (NIRS) has recently been investigated as a non-invasive brain-computer interface (BCI) for individuals with severe motor impairments. For the most part, previous research has investigated the development of NIRS-BCIs operating under synchronous control paradigms, which require the user to exert conscious control over their mental activity whenever the system is vigilant. Though functional, this is mentally demanding and an unnatural way to communicate. An attractive alternative to the synchronous control paradigm is system-paced control, in which users are required to consciously modify their brain activity only when they wish to affect the BCI output, and can remain in a more natural, 'no-control' state at all other times. In this study, we investigated the feasibility of a system-paced NIRS-BCI with one intentional control (IC) state corresponding to the performance of either mental arithmetic or mental singing. In particular, this involved determining if these tasks could be distinguished, individually, from the unconstrained 'no-control' state. Deploying a dual-wavelength frequency domain near-infrared spectrometer, we interrogated nine sites around the frontopolar locations (International 10-20 System) while eight able-bodied adults performed mental arithmetic and mental singing to answer multiple-choice questions within a system-paced paradigm. With a linear classifier trained on a six-dimensional feature set, an overall classification accuracy of 71.2% across participants was achieved for the mental arithmetic versus no-control classification problem. While the mental singing versus no-control classification was less successful across participants (62.7% on average), four participants did attain accuracies well in excess of chance, three of which were above 70%. Analyses were performed offline. Collectively, these results are encouraging, and demonstrate the potential of a system-paced NIRS-BCI with one IC state corresponding to either mental arithmetic or mental singing.

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Mesh:

Year:  2011        PMID: 21975364     DOI: 10.1088/1741-2560/8/6/066004

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


  39 in total

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2.  Passive BCI based on drowsiness detection: an fNIRS study.

Authors:  M Jawad Khan; Keum-Shik Hong
Journal:  Biomed Opt Express       Date:  2015-09-22       Impact factor: 3.732

3.  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

4.  Detection and classification of three-class initial dips from prefrontal cortex.

Authors:  Amad Zafar; Keum-Shik Hong
Journal:  Biomed Opt Express       Date:  2016-12-19       Impact factor: 3.732

5.  Mental stress assessment using simultaneous measurement of EEG and fNIRS.

Authors:  Fares Al-Shargie; Masashi Kiguchi; Nasreen Badruddin; Sarat C Dass; Ahmad Fadzil Mohammad Hani; Tong Boon Tang
Journal:  Biomed Opt Express       Date:  2016-09-06       Impact factor: 3.732

6.  Performance measurement for brain-computer or brain-machine interfaces: a tutorial.

Authors:  David E Thompson; Lucia R Quitadamo; Luca Mainardi; Khalil Ur Rehman Laghari; Shangkai Gao; Pieter-Jan Kindermans; John D Simeral; Reza Fazel-Rezai; Matteo Matteucci; Tiago H Falk; Luigi Bianchi; Cynthia A Chestek; Jane E Huggins
Journal:  J Neural Eng       Date:  2014-05-19       Impact factor: 5.379

7.  Decoding different working memory states during an operation span task from prefrontal fNIRS signals.

Authors:  Ting Chen; Cui Zhao; Xingyu Pan; Junda Qu; Jing Wei; Chunlin Li; Ying Liang; Xu Zhang
Journal:  Biomed Opt Express       Date:  2021-05-18       Impact factor: 3.732

8.  Automatic single-trial discrimination of mental arithmetic, mental singing and the no-control state from prefrontal activity: toward a three-state NIRS-BCI.

Authors:  Sarah D Power; Azadeh Kushki; Tom Chau
Journal:  BMC Res Notes       Date:  2012-03-13

9.  Functional Brain Imaging Reliably Predicts Bimanual Motor Skill Performance in a Standardized Surgical Task.

Authors:  Yuanyuan Gao; Pingkun Yan; Uwe Kruger; Lora Cavuoto; Steven Schwaitzberg; Suvranu De; Xavier Intes
Journal:  IEEE Trans Biomed Eng       Date:  2021-06-18       Impact factor: 4.756

Review 10.  fNIRS-based brain-computer interfaces: a review.

Authors:  Noman Naseer; Keum-Shik Hong
Journal:  Front Hum Neurosci       Date:  2015-01-28       Impact factor: 3.169

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