Differential pathlength factor estimation for brain-like tissue from a single-layer Monte Carlo model

Chatterjee, Subhasri; Phillips, Justin P.; Kyriacou, Panayiotis A.

doi:10.1109/embc.2015.7319092

Cited by 4 publications

(3 citation statements)

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“…Thus, accurate quantification of NIRS signal is possible with information regarding nature of light transport through in-homogenous medium. Chatterjee et al ( 2015 ) analyzed a Monte-Carlo based computational model within a single layer of tissue like human brain. Their finding concluded that optical path changes by changing the source-detector separation.…”

Section: Discussionmentioning

confidence: 99%

“…It is assumed that the NIR light emitted by the source and detected by a near-by detector follows a banana-shaped path (Kamran et al, 2016 ). Thus, the actual path traveled by NIR light is much longer than the source-detector separation on the surface of the scalp (Delpy et al, 1988 ; Hiraoka et al, 1993 ; Chatterjee et al, 2015 ; Piao et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

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Differential Path-Length Factor's Effect on the Characterization of Brain's Hemodynamic Response Function: A Functional Near-Infrared Study

Kamran

Mannan

Jeong

2018

Front. Neuroinform.

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Functional near-infrared spectroscopy (fNIRS) has evolved as a neuro-imaging modality over the course of the past two decades. The removal of superfluous information accompanying the optical signal, however, remains a challenge. A comprehensive analysis of each step is necessary to ensure the extraction of actual information from measured fNIRS waveforms. A slight change in shape could alter the features required for fNIRS-BCI applications. In the present study, the effect of the differential path-length factor (DPF) values on the characteristics of the hemodynamic response function (HRF) was investigated. Results were compiled for both simulated data sets and healthy human subjects over a range of DPF values from three to eight. Different sets of activation durations and stimuli were used to generate the simulated signals for further analysis. These signals were split into optical densities under a constrained environment utilizing known values of DPF. Later, different values of DPF were used to analyze the variations of actual HRF. The results, as summarized into four categories, suggest that the DPF can change the main and post-stimuli responses in addition to other interferences. Six healthy subjects participated in this study. Their observed optical brain time-series were fed into an iterative optimization problem in order to estimate the best possible fit of HRF and physiological noises present in the measured signals with free parameters. A series of solutions was derived for different values of DPF in order to analyze the variations of HRF. It was observed that DPF change is responsible for HRF creep from actual values as well as changes in HRF characteristics.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Differential Path-Length Factor's Effect on the Characterization of Brain's Hemodynamic Response Function: A Functional Near-Infrared Study

Kamran

Mannan

Jeong

2018

Front. Neuroinform.

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“…An erroneous DPF can yield an inaccurate estimation of hemodynamic responses (HRs) [33]. Some studies proposed a DPF estimation by an offline Monte-Carlo method [32,34,35], while others proposed approaches based on the analysis of a time-domain contrast function for compensation [36,37]. The Monte-Carlo method assumes that the DPF is identical for all channels, while the latter is only suitable for time-domain fNIRS.…”

Section: Introductionmentioning

confidence: 99%

Multi-Channel-Based Differential Pathlength Factor Estimation for Continuous-Wave fNIRS

Huang

Hong

2021

IEEE Access

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Functional near-infrared spectroscopy (fNIRS) in brain imaging needs to be robust to subjectwise variability. The use of a fixed differential pathlength factor (DPF) per wavelength for the entire brain will degrade the accuracy of hemodynamic responses. Since the tissue composition varies within the brain, correct DPF values should be used for various emitter-detector distances and brain regions. In this paper, a DPF estimation method combining a state-space model of the modified Beer-Lambert law (mBLL), a parameter model for estimating the reduced scattering coefficients, and dual square-root cubature Kalman filters (SCKFs) is proposed. To validate the proposed method, known light intensities (six channels, two wavelengths) and reference DPFs are generated using NIRFAST (a Matlab toolbox) using a presumed paradigm, known tissue properties, a Balloon model, and a finite element head model consisting of 58,818 mesh elements. Then, the DPF values are estimated using a Jacobian matrix from the head model and the mBLL. The results show that the estimated concentration changes correlate well with the reference data. Also, the estimated DPFs showed relative errors less than 1.33% maximum and 0.75% on average. A onetailed t-test revealed that the estimated DPFs matched the reference DPFs with more than 99.9% confidence. The developed method can efficiently access the actual DPFs even if emitter-detector distances vary significantly and the tissue properties are not uniform. With the developed state-space models for dual SCKFs, real-time estimation of the DPFs from one experiment to another has become plausible.INDEX TERMS Differential pathlength factor (DPF), functional near-infrared spectroscopy (fNIRS), Kalman filter, state-space method, finite element method (FEM)

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Wearable Sensor for Multi-wavelength Near-Infrared Spectroscopy of Skin Hemodynamics Along with Underlying Muscle Electromyography

Mujumdar

Cheung

Kadam

et al. 2021

Biosystems &Amp; Biorobotics

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Differential pathlength factor estimation for brain-like tissue from a single-layer Monte Carlo model

Abstract: This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent

Cited by 4 publications

References 15 publications

Differential Path-Length Factor's Effect on the Characterization of Brain's Hemodynamic Response Function: A Functional Near-Infrared Study

Differential Path-Length Factor's Effect on the Characterization of Brain's Hemodynamic Response Function: A Functional Near-Infrared Study

Multi-Channel-Based Differential Pathlength Factor Estimation for Continuous-Wave fNIRS

Wearable Sensor for Multi-wavelength Near-Infrared Spectroscopy of Skin Hemodynamics Along with Underlying Muscle Electromyography

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