Support vector machine based error filtering for holter electrocardiogram analysis.
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.
Kigawa
Yasushi
Y
Graduate Sch. of Inf. Sci. & Technol., Aichi Prefectural Univ.
Oguri
Koji
K