Xin Liu1,*, Yujuan Si1,2, Di Wang1
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 341-351, 2020, DOI:10.31209/2019.100000104
Abstract As a biological signal existing in the human living body, the electrocardiogram
(ECG) contains abundantly personal information and fulfils the basic
characteristics of identity recognition. It has been widely used in the field of
individual identification research in recent years. The common process of
identity recognition includes three steps: ECG signals preprocessing, feature
extraction and processing, beat classification recognition. However, the existing
ECG classification models are sensitive to limitations of database type and
extracted features dimension, which makes classification accuracy difficult to
improve and cannot meet the needs of practical applications. To tackle the
problem, this paper proposes to build… More >
Login
Register
