Wavelet minimum description length detrending for near-infrared spectroscopy

Jang, Kwang Eun; Tak, Sungho; Jung, Jinwook; Jang, Jaeduck; Jeong, Yong Hoon; Ye, Jong Chul

doi:10.1117/1.3127204

Cited by 238 publications

(173 citation statements)

References 44 publications

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“…NIRS-SPM is an SPM [28] and MATLAB-based software package used for statistical analysis of NIRS signals, developed at the Bio Imaging Signal Processing laboratory, KAIST, Korea [18,19]. Noise was removed from the measurement data by wavelet minimum description length detrending [29], and SPM was performed using a generalized linear model. The level of significance was set at a p value of <5%.…”

Section: Discussionmentioning

confidence: 99%

Brain Activity during the Observation, Imagery, and Execution of Tool Use: An fNIRS/EEG Study

Nakano¹

2012

J Nov Physiother

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Section: Discussionmentioning

confidence: 99%

Brain Activity during the Observation, Imagery, and Execution of Tool Use: An fNIRS/EEG Study

Nakano¹

2012

J Nov Physiother

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“…The fNIRS data was processed with a Matlab (MathWorks, USA) toolbox developed in-house, called nirs10 (available upon request), based on SPM8 (Friston et al, 2007) and NIRS-SPM Jang et al, 2009). Channels with source-detector separation greater than 6 cm or with standard deviation greater than 10% of the mean were removed right away and were not included in channel counts presented later on, following .…”

Section: Data Processingmentioning

confidence: 99%

fNIRS-EEG study of focal interictal epileptiform discharges

et al. 2014

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Functional near-infrared spectroscopy (fNIRS) acquired with electroencephalography (EEG) is a relatively new non-invasive neuroimaging technique with potential for long term monitoring of the epileptic brain. Simultaneous EEG-fNIRS recording allows the spatio-temporal reconstruction of the hemodynamic response in terms of the concentration changes in oxyhemoglobin (HbO) and deoxy-hemoglobin (HbR) associated with recorded epileptic events such as interictal epileptic discharges (IEDs) or seizures. While most previous studies investigating fNIRS in epilepsy had limitations due to restricted spatial coverage and small sample sizes, this work includes a sufficiently large number of channels to provide an extensive bilateral coverage of the surface of the brain for a sample size of 40 patients with focal epilepsies. Topographic maps of significant activations due to each IED type were generated in four different views (dorsal, frontal, left and right) and were compared with the epileptic focus previously identified by an epileptologist.After excluding 5 patients due to the absence of IEDs and 6 more with mesial temporal foci too deep for fNIRS, we report that significant HbR (respectively HbO) concentration changes corresponding to IEDs were observed in 62% (resp. 38%) of patients with neocortical epilepsies. This HbR/HbO response was most significant in the epileptic focus region among all the activations in 28%/21% of patients. Keywords:Focal epilepsy, fNIRS, NIRS-SPM, EEG, interictal epileptic discharges

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“…And then, the detrending process is selectively performed depending on a BD threshold, and it is determined by abrupt increase changing point on sorted channel. If an index (BI) of some channels have high values, the detrending process of the fNIRS signals of the channels are selectively performed using wavelet-MDL (minimum description length) [10].…”

Section: Proposed Selective Detrending Methodsmentioning

confidence: 99%

“…where βi denotes an unknown strength of response, and xi(t) is an explanatory variable from a model of hemodynamic responses [10]. Let y and ε denote the vector of the time series of the hemodynamic signal and noise at the location r:…”

Section: General Linear Model For Fnirsmentioning

confidence: 99%

Selective Detrending using Baseline Drift Detection Index for Task-dependant fNIRS Signal

An¹,

Lee²,

Lee³

et al. 2017

Adv. sci. technol. eng. syst. j.

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A functional near-infrared spectroscopy (fNIRS) can be employed to investigate brain activation by measuring the absorption of near-infrared light through the intact skull. The general linear model (GLM) as a standard model for fMRI analysis has been applied to functional near-infrared spectroscopic (fNIRS) imaging analysis as well. The GLM has drawback of failure in fNIRS signals, when they have drift globally. Wavelet based detrending technique is very popular to correct the baseline drift (BD) in fNIRS. However, this method globally distorted the total multi-channel signals even if just one channel's signal was locally drifted. This paper suggests the selective detrending method using BD detection index to indicate BD as an objective index. The experiments show the performance of the proposed method as graphic results and objective evaluation index with current detrending algorithms.

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Wavelet minimum description length detrending for near-infrared spectroscopy

Cited by 238 publications

References 44 publications

Brain Activity during the Observation, Imagery, and Execution of Tool Use: An fNIRS/EEG Study

Brain Activity during the Observation, Imagery, and Execution of Tool Use: An fNIRS/EEG Study

fNIRS-EEG study of focal interictal epileptiform discharges

Selective Detrending using Baseline Drift Detection Index for Task-dependant fNIRS Signal

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