Automatic Detection of Arrhythmia Based on Multi-Resolution Representation of ECG Signal.

ABSTRACT: Automatic detection of arrhythmia is of great significance for early prevention and diagnosis of cardiovascular disease. Traditional feature engineering methods based on expert knowledge lack multidimensional and multi-view information abstraction and data representation ability, so the traditional research on pattern recognition of arrhythmia detection cannot achieve satisfactory results. Recently, with the increase of deep learning technology, automatic feature extraction of ECG data based on deep neural networks has been widely discussed. In order to utilize the complementary strength between different schemes, in this paper, we propose an arrhythmia detection method based on the multi-resolution representation (MRR) of ECG signals. This method utilizes four different up to date deep ne

SUBMITTER: Wang D 

PROVIDER: S-EPMC7175329 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature