Title :
Support Vector Machine Based Error Filtering for Holter Electrocardiogram Analysis
Author :
Kigawa, Yasushi ; Oguri, Koji
Author_Institution :
Graduate Sch. of Inf. Sci. & Technol., Aichi Prefectural Univ.
Abstract :
Holter electrocardiogram data is analyzed by a computer, however, there is a detection of non-heartbeat as a heartbeat. This study dealt with reduction of the incorrect detection using support vector machine (SVM). By exploiting the power of SVM and human like information processing, the data was classified to heartbeat class or non-heartbeat class. The performance of the proposed method was verified in several experiments and comparing with SVM and neural network, and 96% of accuracy was achieved
Keywords :
electrocardiography; medical signal processing; neural nets; support vector machines; Holter electrocardiogram analysis; data classification; error filtering; heartbeat; human like information processing; neural network; nonheartbeat; support vector machine; Costs; Electrocardiography; Filtering; Heart beat; Humans; Information analysis; Information processing; Neural networks; Support vector machine classification; Support vector machines;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1615306
