Heart Rate Variability Classification using Support Vector Machine and Genetic Algorithm
نویسندگان
چکیده
منابع مشابه
Heart Rate Variability Classification and Feature Extraction Using Support Vector Machine and PCA: An Overview
In today’s era Heart Rate Variability becomes an important characteristic to determine the condition of heart. That’s why the calculation of HRV and classification to generate rules is necessary. Human Heart Generates the electrical signal. ECG is used to detect the heart beat. ECG signal contains lots of noise. To classify the signals first to decompose the signals using wavelet transform. Man...
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OBJECTIVE This paper presents an effective cardiac arrhythmia classification algorithm using the heart rate variability (HRV) signal. The proposed algorithm is based on the generalized discriminant analysis (GDA) feature reduction scheme and the support vector machine (SVM) classifier. METHODOLOGY Initially 15 different features are extracted from the input HRV signal by means of linear and n...
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This contribution describes a classification technique that improves the heart rate estimation during hemodialysis treatments. After the heart rate is estimated from the pressure signal of the dialysis machine, a classifier decides if it is correctly identified and rejects it if necessary. As the classifier employs a support vector machine, special interest is put on the automatic selection of ...
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ژورنال
عنوان ژورنال: Journal of Biomedical Physics and Engineering
سال: 2018
ISSN: 2251-7200
DOI: 10.31661/jbpe.v0i0.614