ニューロリハビリテーションの国際ジャーナル

Novel Method for Assessment of Autonomic Function in Health and Disease: An Application to Epilepsy

Abstract

Ahmed K Kamal

Objective: Impaired autonomic function has been associated with an increased risk of mortality in patients with epilepsy. Autonomic dysfunction involving both sympathetic and parasympathetic systems has also been demonstrated in Epileptic disease using cardiovascular reflex tests based on heart rate to various stimuli. The aim of this study is to propose novel approach using Volterra kernel for system identification of nonlinear relationship between input stimulus (lowering and raising leg) and the output (HRV signals) using entrainment method based on lowering and raising leg of patients to assess in qualitative and quantitative methods the autonomic function of healthy subjects and patients with epilepsy disease and provide medical indices for assessment and neurorehabilitation of autonomic system in Epilepsy
Methods: Forty eight patients with Epilepsy and forty eight of healthy subjects age matched controls participated in this study from July to September 2010 at Johns Hopkins Hospital, Baltimore, Maryland, and the Medical Center, Cookeville, Tennessee, United States of America. All subjects signed consent to participate in the research prior to their inclusion in the study and the consent of ethical committee was obtained and approved the study protocol. The study design was to carry out experimental procedure of lowering and raising a leg at different frequency rate whiles the subject in supine. By applying an algorithm and considering the process of lowering and raising a leg as stimulus input and the Heart Rate Variability signal (HRV) as output for system identification, a mathematical model is expressed as integral equations, whose input-output behavior is nearly identical to that of the system in both healthy subjects and epilepsy disease patients. The model for each group contains the linear part (first order kernel) and nonlinear part (second order kernel).
Results: A difference equation model was employed to represent the system for both control subjects and patients with Epilepsy disease .The results show significant difference in first and second kernel for both groups. Both the first kernel and second kernel of epileptic patients show low variation with respect to healthy subjects. Introducing Normalized Mean Square Errors (NMSE) of first order and second order kernel prediction of both groups may be considered as medical index for to assess the autonomic nervous system in health and disease.
Conclusion: Using first order kernel and second order kernel, it is possible noninvasively to differentiate and assess autonomic function qualitatively and quantitatively in both groups. Future studies are needed to investigate model quantitative indices using this methodology to assess the autonomic nervous system in health and disease.