Segmentation of biomedical signals using an unsupervised approach

• Autorzy: Przybyła T. , Wróbel J. , Czabański R. , Horoba K. , Pander T. , Momot M.
• Języki publikacji: EN

Abstrakty

EN

The paper presents an unsupervised approach to biomedical signal segmentation. The proposed segmentation process consists of several stages. In the first step, a state-space of the signal is reconstructed. In the next step, the dimension of the reconstructed state-space is reduced by projection into principal axes. The final step involves fuzzy clustering method. The clustering process is applied in the kernel-feature space. In the experimental part, the fetal heart rate (FHR) signal is used. The FHR baseline and the acceleration or deceleration patterns are the main signal nonstationarities but also the most clinically important signal features determined and interpreted in computer-aided analysis.

Słowa kluczowe

EN

embedded space; attractor; PCA; kernel space; fuzzy clustering

PL

atraktor; przestrzeń jądra; grupowanie rozmyte

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2012
• Tom: Vol. 19
• Strony: 125--131
• Opis fizyczny: Bibliogr. 17 poz., rys.

Twórcy

autor

Przybyła T.

• Silesian University of Technology, Institute of Electronics, Akademicka St. 16, 44-100 Gliwice, Poland

autor

Wróbel J.

autor

Czabański R.

autor

Horoba K.

autor

Pander T.

autor

Momot M.

Bibliografia

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