Provides an introduction into wavelets and illustrates their application with two examples. The wavelet transform provides the analyst with a scaleable time-frequency representation of the signal, which may uncover details not evidenced by conventional signal processing techniques. The signals used in this paper are Doppler ultrasound recordings of blood flow velocity taken from the internal carotid artery and the femoral artery. Shows how wavelets can be used as an alternative signal processing tool to the short time Fourier transform for the extraction of the time-frequency distribution of Doppler ultrasound signals. Implements wavelet-based adaptive filtering for the extraction of maximum blood velocity envelopes in the post processing of Doppler signals.