Adaptive exercise electrocardiographic signal enhancer with manual neural network anticipate filtering .
- Author:
Hailong LIU
1
;
Jiling TANG
Author Information
1. The Key Laboratory of Biomedical Photonics, Ministry of Education, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Electrocardiography;
Humans;
Neural Networks (Computer);
Nonlinear Dynamics;
Signal Processing, Computer-Assisted;
instrumentation
- From:
Journal of Biomedical Engineering
2006;23(5):1118-1122
- CountryChina
- Language:Chinese
-
Abstract:
Exercise electrocardiogram is to detect ECG signals when one is in exercise state. Its characteristics are that the exercise will result in serious excursion of the baseline ,the distinct increase of the muscle voltage interfere and the fall signal-to-noise. This article introduces a adaptive exercise ECG signal enhancer with manual neural network. It is designed by combining non-linearity of manual neural network and the tracking characteristics of adaptive processing. It can reduce the noise, increase signal-to-noise and effectively abstract exercise
