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Innovative Formalism for Biological Data Analysis

Innovative Formalism for Biological Data Analysis
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Author(s): Calin Ciufudean (Stefan cel Mare University, Romania)
Copyright: 2019
Pages: 13
Source title: Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7598-6.ch029

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Abstract

Modern medical devices involve information technology (IT) based on electronic structures for data and signals sensing and gathering, data and signals transmission, as well as data and signals processing in order to assist and help the medical staff to diagnose, cure, and to monitor the evolution of patients. By focusing on biological signals processing we may notice that numerical processing of information delivered by sensors has a significant importance for a fair and optimum design and manufacture of modern medical devices. The authors consider for this approach fuzzy set as a formalism of analysis of biological signals processing and they propose to accomplish this goal by developing fuzzy operators for filtering the noise of biological signals measurement. The authors exemplify this approach on neurological measurements performed with an electro-encephalograph (EEG).

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