Abstract: The ballistocardiogram least mean square adaptive de-noising method based on orthogonal wavelet transform was researched. The principal of least mean sctuare adaptive de-noising method based on orthogonal wavelet transform was analyzed. The decomposition scale was confirmed by central frequency of ballistocardiogram gained from joint time frequency analysis based on adaptive radial gauss kernel function, and the level confirmed approach for adaptive filter was proposed by choosing and choosing the wavclet base and the length of input signal. I}hc realization approach was described from the view of matrix, and the reason why orthogonal wavelet transform could improve convergence speed of least mean square algorithm was explained. The experiment results show that, by using least mean square adaptive de-noising method based on orthogonal wavelet transform, the adaptive denoised ballistocardiogram becomes steady more ctuickly and its wave changing along with cardiac cycle is clearer. Compared with power spectrum density of before and after denoised signal, least mean square adaptive dcnoising method based on orthogonal wavelet transform holds the characters of ballistocardiogram while denoising time variable noise, and gains better denoising results.

Key words: Ballistocardiogram, Orthogonal wavclet transform, Joint timcfrequcncy analysis, Least mean square, Adaptivc dcnoising