Pulse waveform plays important role in pulse diagnosis, which is the key technique in Traditional Chinese Medicine. However, its baseline wander introduced in the acquisition process will result in misdiagnosis. Therefore a wavelet based cascade adaptive filter to remove this wander is presented in this paper. This cascade adaptive filter works in two stages. The first stage is a discrete Meyer wavelet filter and the second stage is the cubic spline estimation. Comparing with some traditional methods, such as cubic spline estimation and Linear-phase FIR least-squares error minimization digital filter, the proposed approach has better performance for removing the baseline wander of pulse waveform.