Title :
The BCG signal feature extraction and recognition based on the cumulative residual entropy
Author :
Zhixin Ma ; Taishan Chu
Author_Institution :
Nat. Eng. Res. Center for Broadband Networks & Applic., Shanghai, China
Abstract :
In this paper, we use cumulative residual entropy to get the features of Ballistocardiogram (BCG). The data after feature recognition are classified by Support Vector Machine (SVM) algorithm to compare the accuracy. Experimental results indicate that high classification accuracy can be obtained. The method can be used in some disease identification.
Keywords :
cardiology; feature extraction; image classification; medical signal processing; support vector machines; BCG signal feature extraction; SVM algorithm; ballistocardiogram; classification accuracy; cumulative residual entropy; disease identification; feature recognition; support vector machine algorithm; Accuracy; Diseases; Entropy; Feature extraction; Heart; Sleep apnea; Support vector machines; Arrhythmia; Ballistocardiogram (BCG); Disease Identification; Support Vector Machine (SVM); cumulative residual entropy; obstructive sleep apnea-hypopnea syndrome (OSAHS);
Conference_Titel :
Instrumentation and Measurement, Sensor Network and Automation (IMSNA), 2013 2nd International Symposium on
Conference_Location :
Toronto, ON
DOI :
10.1109/IMSNA.2013.6743330
