Algorithm Establishment with Model Experiment for Continuous-Wave Functional Near-Infrared Spectroscopy

2011 ◽  
Vol 138-139 ◽  
pp. 553-559
Author(s):  
Ting Li ◽  
Zhi Li Zhang ◽  
Yi Zheng
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Model Experiment ◽  
Near Infrared ◽  
Continuous Wave ◽  
Valsalva Maneuver ◽  
Hemoglobin Concentration ◽  
Functional Near Infrared Spectroscopy ◽  
Concentration Changes

Although functional near-infrared spectroscopy (fNIRS) has been developing as a useful tool for monitoring functional brain activity since the early 1990s, the quantification of hemoglobin concentration changes is still controversial and there are few detailed reports especially for continuous-wave (CW) instruments. By means of a two-layer model experiment mimicking hemodynamic changes in brain and mathematical analysis based on the modified Beer-Lambert law, we established an algorithm for a CW functional near-infrared spectroscopy (CW-fNIRS). The accuracy of this algorithm was validated both in comparison with direct measurements on brain tissue model and in vivo measurement upon human valsalva maneuver. This described method can also be utilized for other CW-fNIRS instruments to establish measuring algorithm.

scholarly journals Measuring speaker-listener neural coupling with functional near infrared spectroscopy

2016 ◽  
Author(s):  
Yichuan Liu ◽  
Elise A. Piazza ◽  
Erez Simony ◽  
Patricia A. Shewokis ◽  
Banu Onaral ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Brain Activity ◽  
Hemoglobin Concentration ◽  
Verbal Communication ◽  
Story Comprehension ◽  
Speech Comprehension ◽  
Functional Near Infrared Spectroscopy ◽  
Concentration Changes

AbstractThe present study investigates brain-to-brain coupling, defined as inter-subject correlations in the hemodynamic response, during natural verbal communication. We used functional near-infrared spectroscopy (fNIRS) to record brain activity of speakers telling stories and listeners comprehending audio recordings of these stories. Listeners’ brain activity was correlated with speakers’ with a delay. This between-brain correlation disappeared when verbal communication failed. We further compared the fNIRS and functional Magnetic Resonance Imaging (fMRI) recordings of listeners comprehending the same story and found a relationship between the fNIRS oxygenated-hemoglobin concentration changes and the fMRI BOLD in brain areas associated with speech comprehension. This correlation between fNIRS and fMRI was only present when data from the same story were compared between the two modalities and vanished when data from different stories were compared; this cross-modality consistency further highlights the reliability of the spatiotemporal brain activation pattern as a measure of story comprehension. Our findings suggest that fNIRS is a powerful tool for investigating brain-to-brain coupling during verbal communication. As fNIRS sensors are relatively low-cost and can even be built into wireless, portable, battery-operated systems, these results highlight the potential of broad utilization of this approach in everyday settings for augmenting communication and interaction.

scholarly journals A DAQ-Device-Based Continuous Wave Near-Infrared Spectroscopy System for Measuring Human Functional Brain Activity

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Gang Xu ◽  
Xiaoli Li ◽  
Duan Li ◽  
Xiaomin Liu
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Continuous Wave ◽  
Mental Arithmetic ◽  
Valsalva Maneuver ◽  
Light Sources ◽  
Functional Near Infrared Spectroscopy ◽  
Quadrature Demodulation ◽  
Custom Made

In the last two decades, functional near-infrared spectroscopy (fNIRS) is getting more and more popular as a neuroimaging technique. The fNIRS instrument can be used to measure local hemodynamic response, which indirectly reflects the functional neural activities in human brain. In this study, an easily implemented way to establish DAQ-device-based fNIRS system was proposed. Basic instrumentation components (light sources driving, signal conditioning, sensors, and optical fiber) of the fNIRS system were described. The digital in-phase and quadrature demodulation method was applied in LabVIEW software to distinguish light sources from different emitters. The effectiveness of the custom-made system was verified by simultaneous measurement with a commercial instrument ETG-4000 during Valsalva maneuver experiment. The light intensity data acquired from two systems were highly correlated for lower wavelength (Pearson’s correlation coefficientr= 0.92,P< 0.01) and higher wavelength (r= 0.84,P< 0.01). Further, another mental arithmetic experiment was implemented to detect neural activation in the prefrontal cortex. For 9 participants, significant cerebral activation was detected in 6 subjects (P< 0.05) for oxyhemoglobin and in 8 subjects (P< 0.01) for deoxyhemoglobin.

scholarly journals A Versatile Setup for Time-Resolved Functional Near Infrared Spectroscopy Based on Fast-Gated Single-Photon Avalanche Diode and on Four-Wave Mixing Laser

2019 ◽  
Vol 9 (11) ◽  
pp. 2366 ◽  
Author(s):  
Laura Di Sieno ◽  
Alberto Dalla Mora ◽  
Alessandro Torricelli ◽  
Lorenzo Spinelli ◽  
Rebecca Re ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Single Photon ◽  
Wave Mixing ◽  
Functional Near Infrared Spectroscopy ◽  
Time Resolved ◽  
Diffusive Medium ◽  
Spectroscopy System

In this paper, a time-domain fast gated near-infrared spectroscopy system is presented. The system is composed of a fiber-based laser providing two pulsed sources and two fast gated detectors. The system is characterized on phantoms and was tested in vivo, showing how the gating approach can improve the contrast and contrast-to-noise-ratio for detection of absorption perturbation inside a diffusive medium, regardless of source-detector separation.

scholarly journals Analysis of Different Classification Techniques for Two-Class Functional Near-Infrared Spectroscopy-Based Brain-Computer Interface

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Noman Naseer ◽  
Nauman Khalid Qureshi ◽  
Farzan Majeed Noori ◽  
Keum-Shik Hong
Keyword(s):  
Infrared Spectroscopy ◽  
Discriminant Analysis ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Continuous Wave ◽  
Mental Arithmetic ◽  
Statistical Significance ◽  
Support Vector ◽  
Functional Near Infrared Spectroscopy ◽  
Linear Discriminant

We analyse and compare the classification accuracies of six different classifiers for a two-class mental task (mental arithmetic and rest) using functional near-infrared spectroscopy (fNIRS) signals. The signals of the mental arithmetic and rest tasks from the prefrontal cortex region of the brain for seven healthy subjects were acquired using a multichannel continuous-wave imaging system. After removal of the physiological noises, six features were extracted from the oxygenated hemoglobin (HbO) signals. Two- and three-dimensional combinations of those features were used for classification of mental tasks. In the classification, six different modalities, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA),k-nearest neighbour (kNN), the Naïve Bayes approach, support vector machine (SVM), and artificial neural networks (ANN), were utilized. With these classifiers, the average classification accuracies among the seven subjects for the 2- and 3-dimensional combinations of features were 71.6, 90.0, 69.7, 89.8, 89.5, and 91.4% and 79.6, 95.2, 64.5, 94.8, 95.2, and 96.3%, respectively. ANN showed the maximum classification accuracies: 91.4 and 96.3%. In order to validate the results, a statistical significance test was performed, which confirmed that thepvalues were statistically significant relative to all of the other classifiers (p< 0.005) using HbO signals.

scholarly journals Evoked Hemodynamic Response Estimation to Auditory Stimulus Using Recursive Least Squares Adaptive Filtering with Multidistance Measurement of Near-Infrared Spectroscopy

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yan Zhang ◽  
Xin Liu ◽  
Dan Liu ◽  
Chunling Yang ◽  
Qisong Wang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Auditory Stimulus ◽  
Near Infrared Spectroscopy ◽  
Adaptive Filtering ◽  
Near Infrared ◽  
Continuous Wave ◽  
Hemodynamic Response ◽  
Recursive Least Squares ◽  
Functional Near Infrared Spectroscopy

The performance of functional near-infrared spectroscopy (fNIRS) is sometimes degraded by the interference caused by the physical or the systemic physiological activities. Several interferences presented during fNIRS recordings are mainly induced by cardiac pulse, breathing, and spontaneous physiological low-frequency oscillations. In previous work, we introduced a multidistance measurement to reduce physiological interference based on recursive least squares (RLS) adaptive filtering. Monte Carlo simulations have been implemented to evaluate the performance of RLS adaptive filtering. However, its suitability and performance on human data still remain to be evaluated. Here, we address the issue of how to detect evoked hemodynamic response to auditory stimulus using RLS adaptive filtering method. A multidistance probe based on continuous wave fNIRS is devised to achieve the fNIRS measurement and further study the brain functional activation. This study verifies our previous findings that RLS adaptive filtering is an effective method to suppress global interference and also provides a practical way for real-time detecting brain activity based on multidistance measurement.

scholarly journals Deconvolution of hemodynamic responses along the cortical surface using personalized functional near infrared spectroscopy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A Machado ◽  
Z Cai ◽  
T Vincent ◽  
G Pellegrino ◽  
J-M Lina ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Temporal Dynamics ◽  
Optical Tomography ◽  
Cortical Surface ◽  
Functional Near Infrared Spectroscopy ◽  
Large Variability ◽  
Deconvolution Analysis ◽  
Concentration Changes

AbstractIn functional near infrared spectroscopy (fNIRS), deconvolution analysis of oxy and deoxy-hemoglobin concentration changes allows estimating specific hemodynamic response functions (HRF) elicited by neuronal activity, taking advantage of the fNIRS excellent temporal resolution. Diffuse optical tomography (DOT) is also becoming the new standard reconstruction procedure as it is more accurate than the modified Beer Lambert law approach at the sensor level. The objective of this study was to assess the relevance of HRF deconvolution after DOT constrained along the cortical surface. We used local personalized fNIRS montages which consists in optimizing the position of fNIRS optodes to ensure maximal sensitivity to subject specific target brain regions. We carefully evaluated the accuracy of deconvolution when applied after DOT, using realistic simulations involving several HRF models at different signal to noise ratio (SNR) levels and on real data related to motor and visual tasks in healthy subjects and from spontaneous pathological activity in one patient with epilepsy. We demonstrated that DOT followed by deconvolution was able to accurately recover a large variability of HRFs over a large range of SNRs. We found good performances of deconvolution analysis for SNR levels usually encountered in our applications and we were able to reconstruct accurately the temporal dynamics of HRFs in real conditions.

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