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This work presents a strategy for the prediction of biosignals' future trend, based on a Haar wavelet transform. The proposed scheme is based on the hypothesis that the future evolution of a given biosignal (template) can be estimated from similar patterns existent in a historic dataset. Thus, the first step consists of a simple and efficient measure to evaluate the similarity between biosignal time...
This work describes a Matlab tool implemented to address the trend prediction of physiological time series. It is composed of two main components: time series similarity analysis and wavelet decomposition prediction modules. This tool permits to adjust a set of parameters and configurations that can be used by users/professionals in an active training process. Moreover, a set of common prediction...
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