A novel hybrid energy fraction and entropy-based approach for systolic heart murmurs identification. Issue 5 (1st April 2015)

• Record Type: Journal Article
• Authors: Zheng, Yineng; Guo, Xingming; Ding, Xiaorong
• Is Part Of: Expert systems with applications. Volume 42:Issue 5(2015)
• Page Start: 2710
• Page End: 2721
• Publication Date: 2015-04-01
• Subjects: Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2014.10.051
• Languages: English
• ISSNs: 0957-4174

Abstract

<abstract xml:lang="en" abstract-type="author-highlights" id="ab005"> <title id="st090">Highlights</title> <sec> <p id="sp0005"> <list id="l0005"> <list-item id="o0005"> <label></label> <p id="p0180">We proposed a novel feature extraction based on wavelet packet and sample entropy.</p> </list-item> <list-item id="o0010"> <label></label> <p id="p0185">We proposed five novel feature descriptions of heart sounds.</p> </list-item> <list-item id="o0015"> <label></label> <p id="p0190">We discovered the relationship between energy fraction and area of murmurs.</p> </list-item> <list-item id="o0020"> <label></label> <p id="p0195">Optimal kernel function and parameters for murmurs classification were selected.</p> </list-item> <list-item id="o0025"> <label></label> <p id="p0200">This paper reviewed and compared recently reports on heart sound classification.</p> </list-item> </list> </p> </sec> </abstract>