The following information was submitted:
Transactions: Please, select the Journal that you submit to
Transactions ID Number: 19-813
Full Name: Mario Malcangi
Position: Please, select:
Age: ON
Sex: Male
Address: Via Comelico 39
Country: ITALY
Tel:
Tel prefix:
Fax:
E-mail address: malcangi@dico.unimi.it
Other E-mails:
Title of the Paper: Cardiac Sounds Segmentation Algorithm for Arrhythmias Detection by Fuzzy Logic
Authors as they appear in the Paper: M. Fanfulla, M. Malcangi, M. Riva, D. Della Giustina, F. Belloni
Email addresses of all the authors: riva@unimi.it,federico.belloni@unimi.it,davide.dellagiustina@unimi.it,matteo.fanfulla@studenti.unimi.it
Number of paper pages: 8
Abstract: The heart auscultation is the main investigation approach used to evaluate the possibility of a diseases. In order to improve the automatic diagnosis capabilities of auscultations, signal processing algorithms are developed. A basic task for the diseases diagnosis from the phonocardiogram is to detect the exact timing location of the events presents in the cardiac cycle, especially in pathological cases. In this paper is presented a new technique for segmentation and identification of cardiac sounds able to operate even in the case of cardiac anomalies, and without any additional reference signal such as electrocardiogram signal. A framework to arrhythmias detection based on the heart rate variability, is presented. The advantage in term of low computational burden inherited from the characteristics of fuzzy logic has been tested with a set of normal and abnormal heart sounds achieving satisfactory results.
Keywords: Arrhythmia ; Automatic diagnosis ; Cardiac diseases ; Fuzzy classification ; Heart sound segmentation ; Phonocardiogram
EXTENSION of the file: .pdf
Special (Invited) Session: A General End-Point Detection Algorithm for Cardiac Sounds
Organizer of the Session: 638-329
How Did you learn about congress:
IP ADDRESS: 87.15.146.248
