An arx model approach to fnirs data acquired from migraine and healthy subjects

Abstract

This study is focused on investigating the cerebrovascular dynamics of migraineby analyzing data acquired from healthy and migraine subjects with a noninvasivemeasuring technique, fNIRS during a breath holding task. Brain hemodynamicresponses of subjects are modeled via a parametric identication technique,Auto-regressive with Exogenous input (ARX) model. Analysis of modeled signals forhealthy and migraine subjects is performed both in frequency and time domains. Infrequency domain analysis, frequency intervals in which power spectrum estimates ofmigraineurs signicantly dier from healthy ones, are obtained as 0.01-0.03Hz, around0.13 Hz and higher than 0.2 Hz (p<0.05). The energy of the estimated signals ofmigraineurs in 0.01-0.03 Hz is approximately ve folds smaller than the healthy ones,whereas in 0.13 Hz and 0.25 Hz this dierence is approximately 1.5 folds. Time domainanalysis has shown that the amplitude of peak response of migraineurs is ve foldssmaller than the healthy ones during all breath holding procedure (p<0.05). Requiredmodel orders to fulll the dynamics of response are found higher in migraine case.Results obtained show that response of cerebrovascular system of migraine subjects tobreath holding task is considerably dierent with respect to normal subjects.Keywords: Migraine, Cerebrovascular Dynamics, Functional Near Infrared Spectroscopy(fNIRS), Linear Parametric Identication, Autoregressive Exogenous Input(ARX) Model.