DocumentCode :
2993874
Title :
Symbolic Dynamics Analysis of Pathological Signals
Author :
Wang, Jun ; Wu, Jun
Author_Institution :
Image Process. & Image Commun. Key Lab., Nanjing Univ. of Posts & Telecomm., Nanjing, China
fYear :
2011
fDate :
24-28 Sept. 2011
Firstpage :
129
Lastpage :
132
Abstract :
Paper uses symbolic dynamics to study heartbeat time series from the normal subjects, patients with congestive heart failure and cardiac arrest patients. The results show that entropy value of normal people´s heart beat signals is the maximum. Information entropy value of congestive heart failure patient is decreasing. Cardiac arrest patients´ information entropy is the smallest. It is corresponding that patients have entered into dangerous stage in clinical. Clinical treatment of patients at this time is a critical period. The results are of great significance on the clinical automatically diagnosis. It can play a role in timely warning especially in the long ambulatory ECG monitoring to save the patient´s life.
Keywords :
cardiology; electrocardiography; entropy; medical signal processing; symbol manipulation; time series; ambulatory ECG monitoring; cardiac arrest patients; clinical treatment; congestive heart failure; heartbeat time series; information entropy value; pathological signals; symbolic dynamics analysis; Complexity theory; Databases; Electrocardiography; Entropy; Heart; Information entropy; Time series analysis; Cardiac arrest patients; congestive heart failure; symbolic dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Complexity and Data Mining (IWCDM), 2011 First International Workshop on
Conference_Location :
Nanjing, Jiangsu
Print_ISBN :
978-1-4577-2007-9
Type :
conf
DOI :
10.1109/IWCDM.2011.37
Filename :
6128448
Link To Document :
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