Optimal Parameters of Adaptive Segmentation for Epileptic Graphoelements Recognition

Manual review of EEG records, as it is per¬formed in common medical practice, is very time-consuming. There is an effort to make this analysis easier and faster for neurologists by using systems for automatic EEG graphoelements recognition. Such a system is composed of three steps: (1) segmentation, which is a subject of this article, (2) features extraction and (3) classification. Precision of classification, and thereby the whole recognition, is strongly affected by the quality of preceding segmentation procedure, which depends on the method of segmentation and its parameters. In this paper, Varri’s method for segmentation of real epileptic EEG signals is used. Effect of input parameters on segmentation outcome is discussed and parameters values are proposed to achieve optimal outcome suitable for the following classification and graphoelements recognition. Only the results of segmentation are presented in this paper

Information Technology in Bio- and Medical Informatics, ITBAM 2010

Non e' previsto abstract per una curatel

Evaluation of ECG: comparison of decision tree and fuzzy rules induction

This paper compares two different approaches to computer-aided analysis of ECG signals. ECG records are preprocessed by the wavelet transform, and the machine learning method of decision trees and fuzzy rules induction are used for classification. The wavelet transform allows good localisation of QRS complexes, P and T waves in time and amplitude. The average accuracy of detection of all events is above 87 per cent. For learning and further classification we use Quinlan's See5 application and FURL (FUzzy Rule Learner). We used the MIT-BIH database for experiments. Diverse settings of the parameters for decision tree generation (tree pruning, attribute selection, class sets) were examined. Two datasets and diverse settings of fuzzysets were examined as well

Proceedings of Information Technology in Bio- and Medical Informatics

Non e' previsto abstract per una curatel

Non-technical issues in design and development of personal portable devices

Mobile technologies are constantly evolving and with the development of Internet of Things we can expect continuous increase of various applications. Mobile technologies have undeniable opportunities to play an important role in health services. Concerning purely technical aspects, almost every problem can be solved. However, there are still many unsolved and unclear issues related with ethics and governance mechanisms for mobile phone applications. These issues are even more critical in medical and health care applications of mobile technologies. This paper tries to analyse ethical, and privacy-related challenges that may occur when introducing Personal Portable Devices (PPD) to collect and record personal health data in health care and welfare environment

Evolving Artificial Neural Networks by Means of Evolutionary Algorithms with L-Systems Based Enconding.

Available from STL Prague, CZ / NTK - National Technical LibrarySIGLECZCzech Republi

Intelligent Methods for Quality Improvement in Industrial Practice.

Available from STL Prague, CZ / NTK - National Technical LibrarySIGLECZCzech Republi