Wavelet-based method for reducing respiratory interference in thoracic electrical bioimpedance

The measurements of the thoracic electrical bioimpedance (TEB) are useful for the research on the cardiac functions and in clinical diagnosis. However, TEB is usually contaminated by very heavy respiratory interference. The uses of digital filtering, signal averaging and adaptive processing to remove the respiratory interference have some problems respectively. In this paper, the wavelet-based method for cancellation of respiratory interference is proposed. The continuous wavelet transform (CWT) and the discrete wavelet transform (DWT) are used for the de-respiration. The result of the method of the discrete wavelet transform is satisfactory and the simulated signal is used to prove its accuracy. The de-noising technique based on the discrete wavelet transform is proved to be easy, fast and effective. It can also be applied to other biosignals for denoising.