Electrocardiogram Signal Analysis for Physical Motion Based on Wavelet Approach

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 freeliving 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.