Dynamic analysis of heartbeat rate signals of epileptics using multidimensional phase space reconstruction approach
Journal
Physica A: Statistical Mechanics and its Applications
Journal Volume
387
Journal Issue
10
Pages
2293-2305
Date Issued
2008
Author(s)
Abstract
The heartbeat rate signal provides an invaluable means of assessing the sympathetic-parasympathetic balance of the human autonomic nervous system and thus represents an ideal diagnostic mechanism for detecting a variety of disorders such as epilepsy, cardiac disease and so forth. The current study analyses the dynamics of the heartbeat rate signal of known epilepsy sufferers in order to obtain a detailed understanding of the heart rate pattern during a seizure event. In the proposed approach, the ECG signals are converted into heartbeat rate signals and the embedology theorem is then used to construct the corresponding multidimensional phase space. The dynamics of the heartbeat rate signal are then analyzed before, during and after an epileptic seizure by examining the maximum Lyapunov exponent and the correlation dimension of the attractors in the reconstructed phase space. In general, the results reveal that the heartbeat rate signal transits from an aperiodic, highly-complex behaviour before an epileptic seizure to a low dimensional chaotic motion during the seizure event. Following the seizure, the signal trajectories return to a highly-complex state, and the complex signal patterns associated with normal physiological conditions reappear. ? 2008 Elsevier Ltd. All rights reserved.
Subjects
Chaos; Correlation dimension; Epilepsy; Nonlinearity; Phase space reconstruction
SDGs
Other Subjects
Chaos theory; Computer aided diagnosis; Correlation methods; Neurology; Nonlinear analysis; Correlation dimensions; Diagnostic mechanisms; Epilepsy; Phase space reconstruction; Pattern recognition
Type
journal article