Biomedical Signal Processing

The presentation of the material in the book follows the flow of events of the general signal processing system. After the signal has been acquired, some manipulations are applied in order to enhance the relevant information present in the signal. Simple, Optimal, and adaptive filtering are examples of such manipulations. The detection of wavelets is of importance in biomedical signals; they can be detected from the enhanced signal by several methods. The signal very often contains redundancies. When effective storing, transmission, or automatic classification are required, these redundancies have to be extracted. The signal is then subjected to data reduction algorithms that allow the effective representation in terms of features. Methods for data reduction and features extraction are discussed. Finally, the topic of automatic classification is dealt with, in both the decision theoretic and the syntactic approaches.