The Discrete Lifting Shapelet Transform for biological pattern recognition

Wavelet transform has been widely used in biological signal processing since last decade. The success in the wavelet results relies on the proper selection of the mother wavelet function. In this document the wavelet function is customized to the application. Mentioned approach is possible by means of the Discrete Lifting Shapelet Transform (DLST), a novel transform introduced here and use to generate mother wavelets that resemble the shape of a match pattern and the time-frequency information within. The DLST is inspired on two works: the Discrete Shapelet Transform and the Signal-Dependent Filter Banks. Comparison results are given ensuring the efficacy of the proposed transform in the framework of hand movement recognition using electromyographic signals.