scholarly journals Optimal hemodynamic response model for functional near-infrared spectroscopy

2015 ◽  
Vol 9 ◽  
Author(s):  
Muhammad A. Kamran ◽  
Myung Yung Jeong ◽  
Malik M. N. Mannan
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Hemodynamic Response ◽  
Response Model ◽  
Functional Near Infrared Spectroscopy

Robust functional near infrared spectroscopy denoising using multiple wavelet shrinkage based on a hemodynamic response model

2018 ◽  
Vol 26 (2) ◽  
pp. 79-86 ◽  
Author(s):  
Gihyoun Lee ◽  
Seung Hyun Lee ◽  
Sang Hyeon Jin ◽  
Jinung An
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
General Linear Model ◽  
Hemodynamic Response ◽  
Response Model ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Wavelet Shrinkage ◽  
Functional Near Infrared Spectroscopy

Functional near infrared spectroscopy can measure hemodynamic signals, and the results are similar to functional magnetic resonance imaging of blood-oxygen-level-dependent signals. Thus, functional near infrared spectroscopy can be employed to investigate brain activity by measuring the absorption of near infrared light through an intact skull. Recently, a general linear model, which is a standard method for functional magnetic resonance imaging, was applied to functional near infrared spectroscopy imaging analysis. However, the general linear model fails when functional near infrared spectroscopy signals retain noise, such as that caused by the subject's movement during measurement. Although wavelet-based denoising and hemodynamic response function smoothing are popular denoising methods for functional near infrared spectroscopy signals, these methods do not exhibit impressive performances for very noisy environments and a specific class of noise. Thus, this paper proposes a new denoising algorithm that uses multiple wavelet shrinkage and a multiple threshold function based on a hemodynamic response model. Through the experiments, the performance of the proposed algorithm is verified using graphic results and objective indexes, and it is compared with existing denoising algorithms.

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.

Hemodynamic Response to Repeated Noxious Cold Pressor Tests Measured by Functional Near Infrared Spectroscopy on Forehead

2012 ◽  
Vol 41 (2) ◽  
pp. 223-237 ◽  
Author(s):  
Zeinab Barati ◽  
Patricia A. Shewokis ◽  
Meltem Izzetoglu ◽  
Robi Polikar ◽  
George Mychaskiw ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Cold Pressor ◽  
Hemodynamic Response ◽  
Functional Near Infrared Spectroscopy ◽  
Noxious Cold

Relationship Between Age and Cerebral Hemodynamic Response to Breath Holding: A Functional Near-Infrared Spectroscopy Study

2021 ◽  
Vol 34 (2) ◽  
pp. 154-166
Author(s):  
Keerthana Deepti Karunakaran ◽  
Katherine Ji ◽  
Donna Y. Chen ◽  
Nancy D. Chiaravalloti ◽  
Haijing Niu ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Hemodynamic Response ◽  
Breath Holding ◽  
Spectroscopy Study ◽  
Functional Near Infrared Spectroscopy ◽  
Cerebral Hemodynamic

scholarly journals Classification of Tactile and Motor Velocity-Evoked Hemodynamic Response in Primary Somatosensory and Motor Cortices as Measured by Functional Near-Infrared Spectroscopy

2020 ◽  
Vol 10 (10) ◽  
pp. 3381
Author(s):  
Mohsen Hozan ◽  
Jacob Greenwood ◽  
Michaela Sullivan ◽  
Steven Barlow
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Hemodynamic Response ◽  
Dominant Hand ◽  
Common Spatial Pattern ◽  
Functional Near Infrared Spectroscopy ◽  
Stimulus Velocity ◽  
Motor Velocity

Functional near-infrared spectroscopy (fNIRS) is an emerging technique in studying cerebral hemodynamics; however, consensus on the analysis methods and the clinical applications has yet to be established. In this study, we demonstrate the results of a pilot fNIRS study of cerebral hemodynamic response (HR) evoked by pneumotactile and sensorimotor stimuli on the dominant hand. Our goal is to find the optimal stimulus parameters to maximally evoke HR in the primary somatosensory and motor cortices. We use a pulsatile pneumatic array of 14 tactile cells that were attached to the glabrous surface of the dominant hand, with a patterned stimulus that resembles saltation at three distinct traverse velocities [10, 25, and 45 cm/s]. NIRS optodes (16 sources; 20 detectors) are bilaterally and symmetrically placed over the pre-and post-central gyri (M1 and S1). Our objective is to identify the extent to which cerebral HR can encode the velocity of the somatosensory and/or motor stimuli. We use common spatial pattern for feature extraction and regularized-discriminant analysis for classifying the fNIRS time series into velocity classes. The classification results demonstrate discriminatory features of the fNIRS signal from each distinct stimulus velocity. The results are inconclusive regarding the velocity which evokes the highest intensity of hemodynamic response.

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