Evaluation of neural information content from the phase component of a 32-channel frequency-domain fNIRS system

Scholl, Clara A.; Wathen, Jeremiah J.; Fitch, Michael J.; Milsap, Griffin; Thompson, Margaret C.; Villafane-Delgado, Marisel; Odoemene, Kachi; Eggebrecht, Adam T.; Markow, Zachary E.; Richter, Edward J.; Trobaugh, Jason W.; Culver, Joseph P.; Blodgett, David W.; Hendrickson, S. M.

doi:10.1117/12.2581851

Cited by 3 publications

(8 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(c) The Dual Wavelength FD-fNIRS system described by Scholl et al, providing 1024 theoretical channels. This figure is taken with permission from [ 35 ].…”

Section: State-of-the-art Fd-nirs Technologiesmentioning

confidence: 99%

“…In the same year, Scholl et al [ 35 ] presented a second-generation version of their dual-wavelength FD-fNIRS system. On the source side, 64 TO-can laser diodes were implemented with 32 operating at 690 nm (HL6738MG, Thorlabs, US) and 32 operating at 852 nm (L852P50, Thorlabs, US).…”

Section: State-of-the-art Fd-nirs Technologiesmentioning

confidence: 99%

“…In many existing FD-NIRS systems [ 19 – 21 , 23 , 25 , 27 , 29 , 30 , 32 , 34 , 35 , 39 – 41 , 44 – 48 , 51 , 52 , 54 , 56 – 58 , 60 – 62 , 65 ], Edge-Emitting Lasers (EELs) have been widely applied as light sources. In an EEL, light is emitted from the edge of the substrate, and an EEL offers relatively high power density and wall-plug efficiency, and good beam uniformity [ 78 ].…”

Section: Light Sources and Detectors And Phase Measurement Schemesmentioning

confidence: 99%

“…Of note, the source powers in all the discussed devices [ 19 – 21 , 23 , 25 , 27 , 29 , 30 , 32 , 34 , 35 , 39 – 48 , 50 – 52 , 54 , 56 – 58 , 60 – 62 , 65 ] are expected to meet the skin safety limits (i.e. maximum permissible exposure) suggested by IEC 60825 standard [ 80 , 81 ].…”

Section: Light Sources and Detectors And Phase Measurement Schemesmentioning

confidence: 99%

See 3 more Smart Citations

Review of recent advances in frequency-domain near-infrared spectroscopy technologies [Invited]

Zhou¹,

Xia

Uchitel

et al. 2023

Biomed. Opt. Express

View full text Add to dashboard Cite

Over the past several decades, near-infrared spectroscopy (NIRS) has become a popular research and clinical tool for non-invasively measuring the oxygenation of biological tissues, with particular emphasis on applications to the human brain. In most cases, NIRS studies are performed using continuous-wave NIRS (CW-NIRS), which can only provide information on relative changes in chromophore concentrations, such as oxygenated and deoxygenated hemoglobin, as well as estimates of tissue oxygen saturation. Another type of NIRS known as frequency-domain NIRS (FD-NIRS) has significant advantages: it can directly measure optical pathlength and thus quantify the scattering and absorption coefficients of sampled tissues and provide direct measurements of absolute chromophore concentrations. This review describes the current status of FD-NIRS technologies, their performance, their advantages, and their limitations as compared to other NIRS methods. Significant landmarks of technological progress include the development of both benchtop and portable/wearable FD-NIRS technologies, sensitive front-end photonic components, and high-frequency phase measurements. Clinical applications of FD-NIRS technologies are discussed to provide context on current applications and needed areas of improvement. The review concludes by providing a roadmap toward the next generation of fully wearable, low-cost FD-NIRS systems.

show abstract

“…(c) The Dual Wavelength FD-fNIRS system described by Scholl et al, providing 1024 theoretical channels. This figure is taken with permission from [ 35 ].…”

Section: State-of-the-art Fd-nirs Technologiesmentioning

confidence: 99%

Section: State-of-the-art Fd-nirs Technologiesmentioning

confidence: 99%

Section: Light Sources and Detectors And Phase Measurement Schemesmentioning

confidence: 99%

Section: Light Sources and Detectors And Phase Measurement Schemesmentioning

confidence: 99%

See 2 more Smart Citations

Review of recent advances in frequency-domain near-infrared spectroscopy technologies [Invited]

Zhou¹,

Xia

Uchitel

et al. 2023

Biomed. Opt. Express

View full text Add to dashboard Cite

show abstract

“…The benefits of FD-DOS for both image reconstruction and functional classification are well documented. Scholl et al performed PCA on FD-data collected from the visual cortices of subjects watching movie scenes, and found that the combined intensity and phase signal captured more orthogonal signal dimensions over training and hold-out data than either intensity or phase alone [16] . Thompson et al found that the inclusion of the phase measurement along with intensity significantly improved the accuracy of a regression-based classifier in a two-class finger-opposition task, achieving higher accuracy for each of twelve subjects and significantly higher accuracy at the group level [17] .…”

Section: Introductionmentioning

confidence: 99%

System Derived Spatial-Temporal CNN for High-Density fNIRS BCI

Dale

O’Sullivan

Howard

et al. 2023

IEEE Open J. Eng. Med. Biol.

View full text Add to dashboard Cite

An intuitive and generalisable approach to spatial-temporal feature extraction for high-density (HD) functional Near-Infrared Spectroscopy (fNIRS) brain-computer interface (BCI) is proposed, demonstrated here using Frequency-Domain (FD) fNIRS for motor-task classification. Enabled by the HD probe design, layered topographical maps of Oxy/deOxy Haemoglobin changes are used to train a 3D convolutional neural network (CNN), enabling simultaneous extraction of spatial and temporal features. The proposed spatial-temporal CNN is shown to effectively exploit the spatial relationships in HD fNIRS measurements to improve the classification of the functional haemodynamic response, achieving an average F1 score of 0.69 across seven subjects in a mixed subjects training scheme, and improving subject-independent classification as compared to a standard temporal CNN.INDEX TERMS fNIRS, brain-computer interface, neural network, machine learning, CNN IMPACT STATEMENT The unique and often overlooked interdependence between fNIRS probe design and neural network architecture is demonstrated. A novel and effective BCI model is presented, which can be generalised to multi-wavelength, broadband, and hybrid fNIRS data.

show abstract

Optical Phantoms for Calibrating a Novel Neuroimaging System Targeting Central Nervous System Fluid Flow Dynamics

Angelo

Coon

Nagle

et al. 2023

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)

View full text Add to dashboard Cite

Evaluation of neural information content from the phase component of a 32-channel frequency-domain fNIRS system

Cited by 3 publications

References 0 publications

Review of recent advances in frequency-domain near-infrared spectroscopy technologies [Invited]

Review of recent advances in frequency-domain near-infrared spectroscopy technologies [Invited]

System Derived Spatial-Temporal CNN for High-Density fNIRS BCI

Optical Phantoms for Calibrating a Novel Neuroimaging System Targeting Central Nervous System Fluid Flow Dynamics

Contact Info

Product

Resources

About