There is a growing body of research focusing on automatic detection of ischemia and
myocardial infarction (MI) using computer algorithms. In clinical settings, ischemia and MI …

OBJECTIVE: In the current work we propose a methodology for the automated creation of
fuzzy expert systems, applied in ischaemic and arrhythmic beat classification. METHODS …

Cardiac beat classification is a key process in the detection of myocardial ischemic episodes
in the electrocardiographic signal. In the present study, we propose a multicriteria sorting …

An automated technique was developed for the detection of ischemic episodes in long
duration electrocardiographic (ECG) recordings that employs an artificial neural network. In …

Currently, an automated methodology based on association rules is presented for the
detection of ischemic beats in long duration electrocardiographic (ECG) recordings. The …

Noise can compromise the extraction of some fundamental and important features from
biomedical signals and hence prohibit accurate analysis of these signals. Baseline wander …

Over the past few years, various devices and techniques have been developed for electronic
fetal monitoring (EFM), which is performed during pregnancy or continuously during labor to …

A methodology for the automated development of fuzzy expert systems is presented. The
idea is to start with a crisp model described by crisp rules and then transform them into a set …

We present a compact approach to joint modeling of powerline interference (PLI) and
baseline wonder (BW) for denoising of biopotential signals. Both PLI and BW are modeled …

The accurate detection of burned forest area is essential for post-fire management and
assessment, and for quantifying carbon budgets. Therefore, it is imperative to map burned …