DocumentCode
674490
Title
Fractal behaviour of heart rate variability reflects abnormal respiration patterns in OSAS patients
Author
D´Addio, G. ; Accardo, Agostino ; Fornasa, E. ; Cesarelli, M. ; De Felice, Alberto
Author_Institution
S Maugeri Found., Telese Terme, Italy
fYear
2013
fDate
22-25 Sept. 2013
Firstpage
445
Lastpage
448
Abstract
Although heart rate variability (HRV) decreasing has been usually described in obstructive sleep apnea syndrome (OSAS), some studies have recently questioned the validity of spectral HRV analysis in presence of respiratory and arrhythmic disorders. Fractal analysis of HRV is an emerging nonlinear technique overcoming these limitations and allowing short term HRV assessment during hypo/apnea phases. The aim of this study is to analyse the Fractal features in sleep apnea in order to find as these characteristics could change during abnormal respiration patterns in OSAS. We studied 30 polysomnographic recordings of severe OSAS (AHI≥30) pts. (age 55±9) and 10 PR of normal subjects (age 46±4). Hypo/apnea phases and related beat-to-beat time series have been detected and classified by automated algorithms and manually verified by expert technicians. Fractal analysis was performed by the Higuchi algorithm (FD). Results showed that while FD does not significantly differ between Normals (1.61±0.09) and normal breath epochs in OSAS, it significantly (p<;0.005) tends to a less fractal structure from normal breath (1.60±0.15) to hypopneas (1.52±0.13), obstructive (1.50±0.12) and mixed apneas (1.48±0.11) epochs, with a significant Dunn´s multiple comparisons post test only between normal breath vs. obstructive and mixed apneas.
Keywords
bioelectric potentials; electrocardiography; fractals; medical disorders; medical signal detection; medical signal processing; neurophysiology; pattern classification; pneumodynamics; signal classification; sleep; statistical analysis; time series; Dunn multiple comparisons post test; Higuchi algorithm; OSAS patients; abnormal respiration patterns; arrhythmic disorders; beat-to-beat time series; fractal feature analysis; heart rate variability assessment; hypopneas; nonlinear technique; normal breath epochs; obstructive sleep apnea syndrome; polysomnographic recordings; respiratory disorders; spectral HRV analysis; Abstracts; Biomedical monitoring; Fractals; Heart rate variability; Lead; Monitoring; Niobium;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing in Cardiology Conference (CinC), 2013
Conference_Location
Zaragoza
ISSN
2325-8861
Print_ISBN
978-1-4799-0884-4
Type
conf
Filename
6713409
Link To Document