Cardiovascular diseases are the leading cause of mortality, morbidity, and hospitalization
around the world. Recent technological advances have facilitated analyzing, visualizing …

Analysis of biomedical signals is a very challenging task involving implementation of various
advanced signal processing methods. This area is rapidly developing. This paper is a Part III …

Electrocardiogram (ECG) acquisition is easily contaminated by interferences, and denoising
is the most important task in ECG detection. The variational mode decomposition (VMD) …

Current wavelet thresholding methods for cardiogram signals captured by flexible wearable
sensors face a challenge in achieving both accurate thresholding and real-time signal …

As it was mentioned in the previous part of this work (Part I)—the advanced signal
processing methods are one of the quickest and the most dynamically developing scientific …

Biosensor research has long focused on achieving the lowest possible Limits of Detection
(LOD), driving significant advances in sensitivity and opening up new possibilities in …

Surface electromyography (sEMG) is a technique for measuring and analyzing the electrical
signals of muscle activity using electrodes placed on the skin's surface. The aim of this paper …

An efficient processing approach is essential for increasing identification accuracy since the
electroencephalogram (EEG) signals produced by the Brain–Computer Interface (BCI) …

The pace of technological development, including smart factories within Industry 4.0/5.0,
means that the vagaries of supply chains observed previously cannot be repeated. The …

A significant amount of data is gathered by the healthcare sector, but it is not appropriately
mined and utilized. Finding these hidden links and patterns is frequently underutilized. Our …