Paper Info
Title
An Integrated Framework for Joint HRF and Drift Estimation and HbO/HbR Signal Improvement in fNIRS Data
Abstract
Nonparametric hemodynamic response function (HRF) estimation in functional near-infrared spectroscopy (fNIRS) data plays an important role when investigating the temporal dynamics of a brain region response during activations. Assuming the drift arising from both physical and physiological effects in fNIRS data is Lipschitz continuous; a novel algorithm for joint HRF and drift estimation is derived in this paper. The proposed algorithm estimates the HRF by applying a first-order differencing to the fNIRS time series samples in order to remove the drift effect. An estimate of the drift is then obtained using a wavelet thresholding technique applied to the residuals generated by removing the estimated induced activation response from the fNIRS time-series. It is shown that the proposed HRF estimator is √N consistent whereas the estimator of the drift is asymptotically optimal. The de-drifted fNIRS oxygenated (HbO) and deoxygenated (HbR) hemoglobin responses are then obtained by removing the corresponding estimated drifts from the fNIRS time-series. Its performance is assessed using both simulated and real fNIRS data sets. The application results reveal that the proposed joint HRF and drift estimation method is efficient both computationally and in terms of accuracy. In comparison to traditional model based methods used for HRF estimation, the proposed novel method avoids the selection of a model to remove the drift component. As a result, the proposed method finds an optimal estimate of the fNIRS drift and offers a model-free approach to de-drift the HbO/HbR responses.
Year
DOI
Venue
2014
10.1109/TMI.2014.2331363
Medical Imaging, IEEE Transactions
Keywords
Field
DocType
brain,infrared spectroscopy,medical image processing,oximetry,physiology,proteins,time series,wavelet transforms,HRF estimator,HbO/HbR responses,HbO/HbR signal improvement,Lipschitz continuous,brain region response,de-drifted fNIRS oxygenated hemoglobin responses,deoxygenated hemoglobin responses,drift component removal,drift effect,drift estimation method,drift estimator,estimated induced activation response removal,fNIRS drift,fNIRS time series samples,first-order differencing,functional near-infrared spectroscopy data,integrated framework,joint HRF estimation,model-free approach,nonparametric hemodynamic response function estimation,physical effects,physiological effects,real fNIRS data sets,simulated fNIRS data sets,temporal dynamics,traditional model,wavelet thresholding technique,Contrast-to-noise ratio improvement,HbO/HbR,functional near-infrared spectroscopy,hemodynamic response function,model-free optimal de-drifting
Data set,Computer science,Lipschitz continuity,Artificial intelligence,Asymptotically optimal algorithm,Computer vision,Wavelet thresholding,Signal-to-noise ratio,Algorithm,Nonparametric statistics,Speech recognition,Discrete cosine transforms,Estimator
Journal
Volume
Issue
ISSN
33
11
0278-0062
Citations 
PageRank 
References 
5
0.41
13
Authors
2
Name
Order
Citations
PageRank
Adnan Shah1476.08
Abd-Krim Seghouane27812.27