Functional Near-Infrared Spectroscopy (fNIRS) in Neuroergonomics

Thomas, Liya; Nam, Chang S.

doi:10.1007/978-3-030-34784-0_4

Cited by 3 publications

(3 citation statements)

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“…In recent years, functional near-infrared spectroscopy (fNIRS) has emerged as a promising neuroimaging technique, offering a non-invasive and portable approach to monitoring cerebral hemodynamics. By optically measuring changes in oxygenated and deoxygenated hemoglobin concentrations (Kim et al, 2017), fNIRS provides valuable insights into the neural correlates of cognitive and motor functions (Bauernfeind et al, 2016; Thomas and Nam, 2020). Its versatility and relatively low cost have facilitated the expansion of neuroimaging research beyond traditional laboratory settings, enabling studies in more ecologically valid environments.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Validity and Reliability of HD-DOT TD-fNIRS Resting-State Measurements in Rapid Succession Data Collection Settings

Oveisi,

Momi,

Morshedzadeh

et al. 2024

Preprint

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Functional magnetic resonance imaging (fMRI) has long been a cornerstone in the study of brain activity, but its high operational costs, limited availability, and restricted practical applicability have led researchers to seek alternative neuroimaging technologies. Recent advancements in high-density diffuse optical tomography (HD-DOT) and Time-Domain (TD) functional near-infrared spectroscopy (fNIRS) have emerged as promising solutions, offering the ability to generate detailed tomographic maps of hemodynamic fluctuations associated with neural activity. In this study, using the Kernel Flow device, we assess the performance of HD-DOT TD-fNIRS in terms of signal validity and reliability, particularly in rapid succession data collection settings. We conducted a multiple test-retest experiment involving fNIRS recordings from three participants across 20 ten-minute sessions of eyes-open resting-state brain activity over six days. Our findings indicate that HD-DOT TD-fNIRS systems like the Kernel Flow can reproduce hemodynamic patterns identified by fMRI, albeit with less spatial detail, and can detect resting state networks overall, though some individual network detections are not significant. The system performs consistently over days, with more variability within the time of day, and can capture subject-specific patterns with high accuracy as identified through FC fingerprinting analysis. We conclude that the new generation of HD-DOT TD-fNIRS systems holds significant promise for enhancing and expanding the measurement of functional brain data in both clinical and more naturalistic research settings. This study represents an important step towards a comprehensive understanding of the data quality and consistency achievable with these innovative neuroimaging devices.

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Section: Introductionmentioning

confidence: 99%

Assessing the Validity and Reliability of HD-DOT TD-fNIRS Resting-State Measurements in Rapid Succession Data Collection Settings

Oveisi,

Momi,

Morshedzadeh

et al. 2024

Preprint

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“…The light weight and robust nature of the components required for fNIRS (which has been and will likely continue to increase, given the ubiquity of LEDs and photo diodes in many common electronic devices) make it well-suited to neuroergonomic use cases where spatially-specific cortical information is of interest (Ferrari and Quaresima, 2012;Ayaz and Dehais, 2021). Indeed, the use of fNIRS in the field of neuroergonomics has and by all measures will continue to grow in popularity (Naseer and Hong, 2015;Thomas and Nam, 2020). The suitability of fNIRS to such tasks is best considered in reference to all other options (Pinti et al, 2020): compared with fMRI and wet EEG, fNIRS offers a measurement method and form factor that are quicker to deploy; while compared with dry EEG, fNIRS' ability to take spatially-specific cortical measurements (given its use of the hemodynamic response as opposed to the measurement of electrical potentials at the scalpwhich sufferings a smearing effect rendering spatially-specific information challenging to obtain in the absence of many low-impedance measurement locations), make it well-suited where spatially-specific cortical signals are to be captured in a scenario requiring an easy to deploy and ergonomic measurement method.…”

Section: Introductionmentioning

confidence: 99%

Home-based portable fNIRS-derived cortical laterality correlates with impairment and function in chronic stroke

Friesen

Lawrence²,

Ingram³

et al. 2022

Front. Hum. Neurosci.

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IntroductionImproved understanding of the relationship between post-stroke rehabilitation interventions and functional motor outcomes could result in improvements in the efficacy of post-stroke physical rehabilitation. The laterality of motor cortex activity (M1-LAT) during paretic upper-extremity movement has been documented as a useful biomarker of post-stroke motor recovery. However, the expensive, labor intensive, and laboratory-based equipment required to take measurements of M1-LAT limit its potential clinical utility in improving post-stroke physical rehabilitation. The present study tested the ability of a mobile functional near-infrared spectroscopy (fNIRS) system (designed to enable independent measurement by stroke survivors) to measure cerebral hemodynamics at the motor cortex in the homes of chronic stroke survivors.MethodsEleven chronic stroke survivors, ranging widely in their level of upper-extremity motor deficit, used their stroke-affected upper-extremity to perform a simple unilateral movement protocol in their homes while a wireless prototype fNIRS headband took measurements at the motor cortex. Measures of participants' upper-extremity impairment and function were taken.ResultsParticipants demonstrated either a typically lateralized response, with an increase in contralateral relative oxyhemoglobin (ΔHbO), or response showing a bilateral pattern of increase in ΔHbO during the motor task. During the simple unilateral task, M1-LAT correlated significantly with measures of both upper-extremity impairment and function, indicating that participants with more severe motor deficits had more a more atypical (i.e., bilateral) pattern of lateralization.DiscussionThese results indicate it is feasible to gain M1-LAT measures from stroke survivors in their homes using fNIRS. These findings represent a preliminary step toward the goals of using ergonomic functional neuroimaging to improve post-stroke rehabilitative care, via the capture of neural biomarkers of post-stroke motor recovery, and/or via use as part of an accessible rehabilitation brain-computer-interface.

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“…fNIRS is a non-invasive optical methodology able to measure cortical oscillation of oxygenated (O 2 Hb) and deoxygenated (HHb) hemoglobin related to neuronal activity through the blood oxygen level dependent (BOLD) effect [ 1 , 2 , 3 ]. This technique is portable, relatively cheap, lightweight and quite resilient to motion artifacts with a mechanical structure resembling electroencephalography (EEG) [ 4 , 5 ], thus being suitable for ecological measurements, such as the clinical practice and outdoor applications [ 6 , 7 , 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

A Motion Artifact Correction Procedure for fNIRS Signals Based on Wavelet Transform and Infrared Thermography Video Tracking

Perpetuini

Cardone

Filippini

et al. 2021

Sensors

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Functional near infrared spectroscopy (fNIRS) is a neuroimaging technique that allows to monitor the functional hemoglobin oscillations related to cortical activity. One of the main issues related to fNIRS applications is the motion artefact removal, since a corrupted physiological signal is not correctly indicative of the underlying biological process. A novel procedure for motion artifact correction for fNIRS signals based on wavelet transform and video tracking developed for infrared thermography (IRT) is presented. In detail, fNIRS and IRT were concurrently recorded and the optodes’ movement was estimated employing a video tracking procedure developed for IRT recordings. The wavelet transform of the fNIRS signal and of the optodes’ movement, together with their wavelet coherence, were computed. Then, the inverse wavelet transform was evaluated for the fNIRS signal excluding the frequency content corresponding to the optdes’ movement and to the coherence in the epochs where they were higher with respect to an established threshold. The method was tested using simulated functional hemodynamic responses added to real resting-state fNIRS recordings corrupted by movement artifacts. The results demonstrated the effectiveness of the procedure in eliminating noise, producing results with higher signal to noise ratio with respect to another validated method.

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Functional Near-Infrared Spectroscopy (fNIRS) in Neuroergonomics

Cited by 3 publications

References 56 publications

Assessing the Validity and Reliability of HD-DOT TD-fNIRS Resting-State Measurements in Rapid Succession Data Collection Settings

Assessing the Validity and Reliability of HD-DOT TD-fNIRS Resting-State Measurements in Rapid Succession Data Collection Settings

Home-based portable fNIRS-derived cortical laterality correlates with impairment and function in chronic stroke

A Motion Artifact Correction Procedure for fNIRS Signals Based on Wavelet Transform and Infrared Thermography Video Tracking

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