Investigation of the Hemodynamic Response in Near Infrared Spectroscopy Data Analysis

Near infrared spectroscopy (NIRS) is an effective technique for examining functional brain activity during cognitive tasks by enabling the measurement of the concentration changes of oxy-hemoglobin and deoxy-hemoglobin. In NIRS data analysis, accurate estimation of the hemodynamic response function...

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Veröffentlicht in:2010 Second International Conference on Knowledge and Systems Engineering S. 28 - 32
Hauptverfasser: Le Hoa Nguyen, Keum-Shik Hong
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.10.2010
Schlagworte:
Adaptation model
adaptive filter
Adaptive filters
Brain modeling
component
deconvolution algorithm
Frequency estimation
hemodynamic response function
Hemodynamics
NIRS
Noise
noise removal
Spectroscopy
ISBN:1424483344, 9781424483341
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Zusammenfassung:Near infrared spectroscopy (NIRS) is an effective technique for examining functional brain activity during cognitive tasks by enabling the measurement of the concentration changes of oxy-hemoglobin and deoxy-hemoglobin. In NIRS data analysis, accurate estimation of the hemodynamic response function (HRF) is still under investigation. Most existing methods assume that the shape of the HRF to be known. This assumption may not be appropriate when the HRF varies from subject to subject or from region to region. In this paper, a deconvolution algorithm to estimate the HRF is presented. The advantage of this method is no prior hypothesis about the shape of the HRF is required. In addition, in order to increase the sensitivity of NIRS to functional brain activity, an adaptive filter is designed to remove physiological noises from the noisy NIRS data. In order to verify the effectiveness of the proposed methods, numerical simulations were performed, the results of which are provided herein.
ISBN:1424483344
9781424483341
DOI:10.1109/KSE.2010.26