fNIRS-based brain-computer interfaces: a review

Frontiers in Human Neuroscience, Journal Year: 2015, Volume and Issue: 9

Published: Jan. 28, 2015

A brain-computer interface (BCI) is a communication system that allows the use of brain activity to control computers or other external devices. It can, by bypassing peripheral nervous system, provide means for people suffering from severe motor disabilities in persistent vegetative state. In this paper, brain-signal generation tasks, noise removal methods, feature extraction/selection schemes, and classification techniques fNIRS-based BCI are reviewed. The most common areas fNIRS primary cortex prefrontal cortex. relation cortex, imagery tasks were preferred execution since possible proprioceptive feedback could be avoided. showed significant advantage due no hair detecting cognitive like mental arithmetic, music imagery, emotion induction, etc. removing physiological data, band-pass filtering was mostly used. However, more advanced adaptive filtering, independent component analysis, multi optodes arrangement, being pursued overcome problem filter cannot used when both signals occur within close band. extracting features related desired signal, mean, variance, peak value, slope, skewness, kurtosis noised-removed hemodynamic response For classification, linear discriminant analysis method provided simple but good performance among others: support vector machine, hidden Markov model, artificial neural network, will widely monitor occurrence neuro-plasticity after neuro-rehabilitation neuro-stimulation. Technical breakthroughs future expected via bundled-type probes, hybrid EEG-fNIRS BCI, through detection initial dips.

Language: Английский

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State of science: mental workload in ergonomics

Ergonomics, Journal Year: 2014, Volume and Issue: 58(1), P. 1 - 17

Published: Dec. 2, 2014

Mental workload (MWL) is one of the most widely used concepts in ergonomics and human factors represents a topic increasing importance. Since modern technology many working environments imposes ever more cognitive demands upon operators while physical diminish, understanding how MWL impinges on performance increasingly critical. Yet, also nebulous concepts, with numerous definitions dimensions associated it. Moreover, research has had tendency to focus complex, often safety-critical systems (e.g. transport, process control). Here we provide general overview current state affairs regarding understanding, measurement application design complex over last three decades. We conclude by discussing contemporary challenges for applied research, such as interaction between workload, quantification 'redlines' which specify when are approaching or exceeding their tolerances.

Language: Английский

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Automaticity of walking: functional significance, mechanisms, measurement and rehabilitation strategies

Frontiers in Human Neuroscience, Journal Year: 2015, Volume and Issue: 9

Published: May 5, 2015

Automaticity is a hallmark feature of walking in adults who are healthy and well-functioning. In the context walking, "automaticity" refers to ability nervous system successfully control typical steady state with minimal use attention-demanding executive resources. Converging lines evidence indicate that deficits disorders characterized part by shift locomotor strategy from automaticity compensatory control. This potentially detrimental performance, as an not optimized for Furthermore, it places excessive demands on limited pool reserves. The result compromised perform basic complex tasks heightened risk adverse mobility outcomes including falls. Strategies rehabilitation well defined, which due both lack systematic research into causes impaired robust neurophysiological assessments gauge automaticity. These gaps knowledge concerning given serious functional implications Therefore, objective this article advance science consolidating identifying regarding: (a) significance automaticity; (b) neurophysiology

Language: Английский

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Mental workload and neural efficiency quantified in the prefrontal cortex using fNIRS

Scientific Reports, Journal Year: 2017, Volume and Issue: 7(1)

Published: July 6, 2017

Abstract An improved understanding of how the brain allocates mental resources as a function task difficulty is critical for enhancing human performance. Functional near infrared spectroscopy (fNIRS) field-deployable optical monitoring technology that provides direct measure cerebral blood flow in response to cognitive activity. We found fNIRS was sensitive variations both real-life (flight simulator) and laboratory settings (tests measuring executive functions), showing increased concentration oxygenated hemoglobin (HbO2) decreased deoxygenated (HHb) prefrontal cortex tasks became more complex. Intensity activation (HbO2 concentration) not clearly correlated Rather, intensity shed insight on level effort, i.e., hard an individual working accomplish task. When combined with performance, provided estimate participants’ neural efficiency, this efficiency consistent across levels same Overall, our data support suitability assess effort related operations represents promising tool measurement other contexts such training programs or clinical setting.

Language: Английский

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Mental workload during n-back task—quantified in the prefrontal cortex using fNIRS

Frontiers in Human Neuroscience, Journal Year: 2014, Volume and Issue: 7

Published: Jan. 1, 2014

When interacting with technical systems, users experience mental workload. Particularly in multitasking scenarios (e.g. the car navigation system while driving) it is desired to not distract from their primary task. For such purposes, human-machine interfaces (HCIs) are desirable which continuously monitor users' workload and dynamically adapt behavior of interface measured While memory tasks have been shown illicit hemodynamic responses brain when averaging over multiple trials, a robust single trial classification crucial prerequisite for purpose adapting HCIs its user.The prefrontal cortex (PFC) plays an important role processing associated In this study 10 subjects, we used functional Near-Infrared Spectroscopy (fNIRS), non-invasive imaging modality, sample activity PFC. The results show up 78% accuracy single-trial discrimination three levels each other. We use n-back task (n ∈ {1, 2, 3}) induce different workload, forcing subjects remember last one, two or rapidly changing items.Our experimental that measuring PFC fNIRS, can be robustly quantify classify workload.Single analysis still young field suffers general lack standards. To increase comparability fNIRS methods results, data corpus made available online.

Language: Английский

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Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development

Frontiers in Human Neuroscience, Journal Year: 2013, Volume and Issue: 7

Published: Jan. 1, 2013

Functional near infrared spectroscopy (fNIRS) is a noninvasive, safe and portable optical neuroimaging method that can be used to assess brain dynamics during skill acquisition performance of complex work everyday tasks. In this paper we describe neuroergonomic studies illustrate the use fNIRS in examination training-related human assessment. We results investigating cognitive workload air traffic controllers, dual verbal-spatial working memory skill, development expertise piloting unmanned vehicles. These conventional devices which participants were tethered device while seated at workstation. Consistent with aims mobile imaging, also compact battery-operated wireless system performs similar accuracy as other established devices. Our indicate both wired systems allow for function naturalistic settings, thus are suitable reliable monitoring training

Language: Английский

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Sensitivity of fNIRS to cognitive state and load

Frontiers in Human Neuroscience, Journal Year: 2014, Volume and Issue: 8

Published: Jan. 1, 2014

Functional near-infrared spectroscopy (fNIRS) is an emerging low-cost noninvasive neuroimaging technique that measures cortical bloodflow. While fNIRS has gained interest as a potential alternative to fMRI for use with clinical and pediatric populations, it remains unclear whether the necessary sensitivity serve replacement fMRI. The present study set out examine detect linear changes in activation functional connectivity response cognitive load, when transitioning from task-free resting state task. Sixteen young adult subjects were scanned continuous-wave system during 10-min resting-state scan followed by letter n-back task three load conditions. Five optical probes placed over frontal parietal cortices, covering bilateral dorsolateral PFC (dlPFC), ventrolateral (vlPFC), frontopolar cortex (FP), cortex. Activation was found scale linearly working memory prefrontal increased increasing loads fronto-parietal, interhemispheric dlPFC, local connections. differed between scan, fronto-parietal greater n-back, vlPFC rest. These results demonstrate sensitive both state, suggesting well-suited explore full complement of research questions will viable

Language: Английский

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Neuroergonomics: a review of applications to physical and cognitive work

Frontiers in Human Neuroscience, Journal Year: 2013, Volume and Issue: 7

Published: Jan. 1, 2013

Neuroergonomics is an emerging science that defined as the study of human brain in relation to performance at work and everyday settings. This paper provides a critical review neuroergonomic approach evaluating physical cognitive work, particularly mobile research employing immobile imaging techniques are discussed following areas work: (1) parameters; (2) fatigue; (3) vigilance mental (4) training neuroadaptive systems; (5) assessment concurrent work. Finally, integration body measurements investigating workload fatigue, context brain/body ("MoBI"), discussed.

Language: Английский

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Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

Frontiers in Neurorobotics, Journal Year: 2017, Volume and Issue: 11

Published: July 23, 2017

In this article, non-invasive hybrid brain-computer interface (hBCI) technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging prosthesis control. Electroencephalography (EEG), due to its easy use fast temporal resolution, most widely utilized combination with other brain/non-brain signal acquisition modalities, instance, functional near infrared spectroscopy (fNIRS), electromyography (EMG), electrooculography (EOG), eye tracker. Three main purposes hybridization increase control commands, improve reduce detection time. Currently, such combinations EEG + fNIRS EOG commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, features) relevant improvement discussed. case signals, motor imagination/movement tasks combined cognitive active (BCI) accuracy. Active reactive sometimes combined: imagination steady-state evoked visual potentials (SSVEP) P300. tasks, SSVEP P300 commands. Passive BCIs, however, rare. After discussing hardware strategies involved development hBCI, second part examines approaches used enhance The future prospects extension hBCI real-time applications daily life scenarios provided.

Language: Английский

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Using near infrared spectroscopy and heart rate variability to detect mental overload

Behavioural Brain Research, Journal Year: 2013, Volume and Issue: 259, P. 16 - 23

Published: Oct. 31, 2013

Language: Английский

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