Abstract:

The intelligent care system can collect physiological data such as ECG in real-time through human body appreciable smart clothes. But it inevitably mixes ECG signals with motion artifacts, causing a loss of morphological characteristics of signals. By using the getting intrinsic mode functions, the empirical mode decomposition (EMD) algorithm can remove non-static and nonlinear signals, as well as the motion artifacts from ECG signals. However, the computation cost of the traditional EMD algorithm is great so it is not applicable to low-power embedded mobile devices. We propose a fast-EMD algorithm, which adopts different motion states to control the number of iterations rather than calculate the complex boundary value SD. Experimental results show that the proposed algorithm can simplify the algorithm implementation process and improve the accuracy of capturing R points. Meanwhile, it can effectively enhance the filtering processing performance of embedded devices.

Key words: smart clothes, ECG, empirical mode decomposition algorithm, motion artifacts