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Title: A shape descriptor for EEG analysis.
Author: Tsironis, P.
Awarding Body: University of Sussex
Current Institution: University of Sussex
Date of Award: 1986
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The Shape Descriptor is a tool for shape analysis of EEG data. It combines shape analysis of wave forms with medical knowledge of EEG features (spikes. slow waves and artifacts). Its contribution is that it optimizes human recognition by providing an accurate shape representation (slopes. durations. amplitudes) using mathematical criteria (error norm. randomness of error ete.) and offering valuable information about their structural properties. The Shape Descriptor has been implemented on a Unix system using Pascal language. The description of the EEG data by linear segments is achieved in two stages. Module 1 provides an initial segmentation of the wave form. The original data is approximated by a polynomial of low degree called Uniform Approximation. using as criterion of clO8el1ess the mioimn error norm. The extraction of linear segments is achieved through the use of hed error approximation techniques. These allow the description of data by straight line segments whose pointwise error does not exceed a pre-assigned value (ie the minimn error obtained in the uniform approximation). The function of Module 2 is to obtiJo better ftptesentation of the EEG data by minimizing the error norm. This is achieved by the split-and-merge algorithm which attempts to minimize the error by moving the junction points of the linear segments. Successive segments with similar approximating c:oefIicients are merged while linear segments with great error are split provided that these processes do not yield greater error. The Shape Descriptor is a good candidate for EEG shape analysis. not only for transients but alao for artifacts and moft complicated patterns
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Bioengineering & biomedical engineering Biomedical engineering Biochemical engineering Computer software