Automatic risk evaluation in elderly patients based on Autonomic Nervous System assessment

Melillo, Paolo (2015) Automatic risk evaluation in elderly patients based on Autonomic Nervous System assessment , [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Bioingegneria, 27 Ciclo. DOI 10.6092/unibo/amsdottorato/6844.
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Abstract

Dysfunction of Autonomic Nervous System (ANS) is a typical feature of chronic heart failure and other cardiovascular disease. As a simple non-invasive technology, heart rate variability (HRV) analysis provides reliable information on autonomic modulation of heart rate. The aim of this thesis was to research and develop automatic methods based on ANS assessment for evaluation of risk in cardiac patients. Several features selection and machine learning algorithms have been combined to achieve the goals. Automatic assessment of disease severity in Congestive Heart Failure (CHF) patients: a completely automatic method, based on long-term HRV was proposed in order to automatically assess the severity of CHF, achieving a sensitivity rate of 93% and a specificity rate of 64% in discriminating severe versus mild patients. Automatic identification of hypertensive patients at high risk of vascular events: a completely automatic system was proposed in order to identify hypertensive patients at higher risk to develop vascular events in the 12 months following the electrocardiographic recordings, achieving a sensitivity rate of 71% and a specificity rate of 86% in identifying high-risk subjects among hypertensive patients. Automatic identification of hypertensive patients with history of fall: it was explored whether an automatic identification of fallers among hypertensive patients based on HRV was feasible. The results obtained in this thesis could have implications both in clinical practice and in clinical research. The system has been designed and developed in order to be clinically feasible. Moreover, since 5-minute ECG recording is inexpensive, easy to assess, and non-invasive, future research will focus on the clinical applicability of the system as a screening tool in non-specialized ambulatories, in order to identify high-risk patients to be shortlisted for more complex investigations.

Abstract
Tipologia del documento
Tesi di dottorato
Autore
Melillo, Paolo
Supervisore
Co-supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze e ingegneria dell'informazione
Ciclo
27
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Data-mining Heart Rate Variability Autonomic Nervous System Hypertension Congestive Heart Failure Vascular event Fall identification Cardiovascular risk
URN:NBN
DOI
10.6092/unibo/amsdottorato/6844
Data di discussione
8 Maggio 2015
URI

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