TY - JOUR
T1 - Classification of ECG Signals Based on Functional Data Analysis
AU - Zhangxiao Miao and Chunzheng Cao
JO - Journal of Information and Computing Science
VL - 1
SP - 075
EP - 080
PY - 2024
DA - 2024/01
SN - 17
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22364.html
KW - functional classification, generalized functional linear model, functional linear discriminant analysis.
AB - <p style="text-align: justify;">Electrocardiogram (ECG) signals are the impulses generated by the heart which are used to
analyze the proper functioning of heart. This paper applies a functional data analysis method to classify ECG
signals. The classification of functional data can be divided into regression model-based classification methods
and density-based classification methods. In this paper, Generalized Functional Linear Models (GFLM) and
Functional Linear Discriminant Analysis (FLDA) are introduced. Finally, we apply GFLM, FLDA and SVM,
neural network, KNN in the actual data, and find that the functional data classification method performs better
in the classification of ECG signals.</p>