What we can and cannot (yet) do with functional near infrared spectroscopy
Functional near infrared spectroscopy (NIRS) is a relatively new technique complimentary to EEG for the development of brain-computer interfaces (BCIs). NIRS-based systems for detecting various cognitive and affective states such as mental and emotional stress have already been demonstrated in a ra...
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doaj-4cb707b8b7d449859caa804fb54512fc2020-11-24T22:29:53ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2014-05-01810.3389/fnins.2014.0011783507What we can and cannot (yet) do with functional near infrared spectroscopyMegan eStrait0Matthias eScheutz1Tufts UniversityTufts UniversityFunctional near infrared spectroscopy (NIRS) is a relatively new technique complimentary to EEG for the development of brain-computer interfaces (BCIs). NIRS-based systems for detecting various cognitive and affective states such as mental and emotional stress have already been demonstrated in a range of adaptive human-computer interaction (HCI) applications. However, before NIRS-BCIs can be used reliably in realistic HCI settings, substantial challenges concerning signal processing and modeling must be addressed. Although many of those challenges have been identified previously, the solutions to overcome them remain scant.<br/><br/> In this paper, we first review what can be currently done with NIRS, specifically, NIRS-based approaches to measuring cognitive and affective user states as well as demonstrations of passive NIRS-BCIs. We then discuss some of the primary challenges these systems would face if deployed in more realistic settings, including detection latencies and motion artifacts. Lastly, we investigate the effects of some of these challenges on signal reliability via a quantitative comparison of three NIRS models. The hope is that this paper will actively engage researchers to facilitate the advancement of NIRS as a more robust and useful tool to the BCI community.http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00117/fullfunctional near-infrared spectroscopy (NIRS)human-computer interactionReliabilitySignal processingbrain-computer interface (BCI) |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Megan eStrait Matthias eScheutz |
spellingShingle |
Megan eStrait Matthias eScheutz What we can and cannot (yet) do with functional near infrared spectroscopy Frontiers in Neuroscience functional near-infrared spectroscopy (NIRS) human-computer interaction Reliability Signal processing brain-computer interface (BCI) |
author_facet |
Megan eStrait Matthias eScheutz |
author_sort |
Megan eStrait |
title |
What we can and cannot (yet) do with functional near infrared spectroscopy |
title_short |
What we can and cannot (yet) do with functional near infrared spectroscopy |
title_full |
What we can and cannot (yet) do with functional near infrared spectroscopy |
title_fullStr |
What we can and cannot (yet) do with functional near infrared spectroscopy |
title_full_unstemmed |
What we can and cannot (yet) do with functional near infrared spectroscopy |
title_sort |
what we can and cannot (yet) do with functional near infrared spectroscopy |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neuroscience |
issn |
1662-453X |
publishDate |
2014-05-01 |
description |
Functional near infrared spectroscopy (NIRS) is a relatively new technique complimentary to EEG for the development of brain-computer interfaces (BCIs). NIRS-based systems for detecting various cognitive and affective states such as mental and emotional stress have already been demonstrated in a range of adaptive human-computer interaction (HCI) applications. However, before NIRS-BCIs can be used reliably in realistic HCI settings, substantial challenges concerning signal processing and modeling must be addressed. Although many of those challenges have been identified previously, the solutions to overcome them remain scant.<br/><br/> In this paper, we first review what can be currently done with NIRS, specifically, NIRS-based approaches to measuring cognitive and affective user states as well as demonstrations of passive NIRS-BCIs. We then discuss some of the primary challenges these systems would face if deployed in more realistic settings, including detection latencies and motion artifacts. Lastly, we investigate the effects of some of these challenges on signal reliability via a quantitative comparison of three NIRS models. The hope is that this paper will actively engage researchers to facilitate the advancement of NIRS as a more robust and useful tool to the BCI community. |
topic |
functional near-infrared spectroscopy (NIRS) human-computer interaction Reliability Signal processing brain-computer interface (BCI) |
url |
http://journal.frontiersin.org/Journal/10.3389/fnins.2014.00117/full |
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