Research Article | OPEN ACCESS
Electrocardiogram Signal Analysis for Physical Motion Based on Wavelet Approach
Guang Lu
Wuhan Institute of Physical Education, Wuhan, 430079, China
Research Journal of Applied Sciences, Engineering and Technology 2013 8:2545-2550
Received: July 27, 2012 | Accepted: September 12, 2012 | Published: March 15, 2013
Abstract
In this study, a portable, low-cost system, Portable Motion Analyzer (PMA), is introduced to obtain data from daily physical motions, such as ECG, heart rate signals, as well as kinetic information of motion and free-living gait. It can gather, process and analysis the signals from multiple input channels. To process these signals, digital filtering and wavelet analysis is used for quantitative analysis, which can de-noise, de-composite and reconstruct the signals. Similar to the Fast Fourier Transformation (FFT) in the Fourier, Mallat algorithm can realize the decomposition and reconstruction of the signal according to the coefficient. Experiments show that the system can effectively de-noise analysis of the data from MIT-BIH arrhythmia database and analysis the signals of body subjected to the shock of ground. It is proved efficient and stable in the most practical scenarios.
Keywords:
Electrocardiograph (ECG), physical motion, signal analysis, wavelet transform,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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