Cerebrovascular reactivity (CVR), measuring the ability of vessel dilation or constriction, is an important indicator of cerebrovascular health. As a parameter describing the hemodynamic changes, CVR requires a physiological challenge as the stimulus and monitors the response of the brain metabolism. We propose a frequency-based approach, which applies general linear model (GLM) on the magnitude of the stimulus and response spectrum to avoid challenges with signal alignment and improve robustness to noise in CVR estimation.
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