Assessment of Instantaneous Heartbeat Dynamics in amnestic Mild Cognitive Impairment
In this study, we employ a time-varying, probabilistic model of linear and nonlinear heartbeat dynamics to investigate the possibility of detecting subtle autonomic alterations in subjects suffering from amnestic mild cognitive impairment (aMCI) by exploi
- PDF / 1,232,245 Bytes
- 4 Pages / 595.276 x 790.866 pts Page_size
- 80 Downloads / 226 Views
Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy 2 Massachusetts General Hospital-Harvard Medical School, Boston, USA 3 Department of Information Engineering, and Research Centre “E. Piaggio”, University of Pisa, Pisa, Italy 4 School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK 5 Department of Electrical, Electronic, and Information Engineering “Guglielmo Marconi”, University of Bologna, Cesena, Italy 6 Versilia Hospital, Viareggio, Italy 7 Department of Electronics, Informatics and Bioengineering, Politecnico di Milano, Milano. Italy #These authors contributed equally to this publication
Abstract—In this study, we employ a time-varying, probabilistic model of linear and nonlinear heartbeat dynamics to investigate the possibility of detecting subtle autonomic alterations in subjects suffering from amnestic mild cognitive impairment (aMCI) by exploiting heartbeat information alone. aMCI is a frequent form of cognitive dysfunction which increases the risk of culminating in Alzheimer's disease (AD)-related dementia, and previous studies have demonstrated that AD is accompanied by alterations in autonomic function, which in turn have been linked to cognitive performance in non-demented subjects. We compare 13 MCI patients without ouvert dysautonomia to 13 age- and gender-matched healthy controls by feeding an autonomic nervous system-related linear and nonlinear feature set into a classification framework. Our results show a satisfactory classification performance (73% balanced accuracy), which dropped to 65% when excluding cardiovascular nonlinear/complex features. This outcome confirms the presence of subtle autonomic dysfunction in aMCI (a possible prodromal condition to AD), which can only be detected through to the use of our comprehensive modeling strategy which comprises timevarying, nonlinear/complex estimates of heartbeat dynamics.
be associated with cardiac autonomic dysfunction [5], is affected even in the preclinical stages of AD. Accordingly, a number of previous studies have investigated the cardiac branch of the autonomic nervous system in AD using techniques like orthostatic reflexes, modulation through breathing and Valsalva's maneuver. Alterations of sympathovagal balance in AD have been reported [6]. Additionally, a number of studies have investigated possible relationships between heart rate variability (HRV) - related estimates of autonomic nervous system (ANS) outflow and cognition in non-demented subjects. Most of these studies show an association between varying degrees of cognitive impairment and cardiac autonomic dysfunction [7-10]. The aim of this study is to investigate if, using cardiac signals only, autonomic alterations can be detected in patients suffering from aMCI, hence providing additional clues about possible future patient trajectories within the AD spectrum.
Keywords— Heart Rate Variability, Autonomic Nervous System, Support Vector Machine, Autonomic dysfunction, Mild Cognitive Impairment.
A. Experim
Data Loading...
