Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
The classification algorithms of rhythm and morphology abnormalities in electrocardiogram (ECG) signals have been widely studied. However, the existing study uses ECGs with fixed leads. We propose a neural network-based method to improve the ECG clas...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Abnormal ventricular potentials (AVPs) are fractionated and complex electrograms (EGMs), typically associated with slow conduction areas in the myocardium. As such, in ventricular tachycardia (VT), their identification supports the localization of th...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Common artefacts such as baseline drift, rescaling, and noise critically limit the performance of machine learning-based automated ECG analysis and interpretation. This study proposes Derived Peak (DP) encoding, a non-parametric method that generates...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
While pre-trained neural networks, e.g., for diagnosis from electrocardiograms (ECGs), are already available and show remarkable performance, their lack of transparency prevents translation to clinical practice. Recently, an explainable artificial in...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Atrial Fibrillation (AFib) represents a prevalent cardiac arrhythmia associated with substantial risk for affected individuals. The integration of wearable devices, coupled with advanced predictive models, opens pathways for non-invasive and real-tim...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
This paper presents an innovative approach to recognizing personality traits using deep learning (DL) methods applied to electrocardiogram (ECG) signals. The research explores the potential of ECG-derived spectrograms as informative features in detec...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
This paper presents a novel approach to noninvasive hyperglycemia monitoring utilizing electrocardiograms (ECG) from an extensive database comprising 1119 subjects. Previous research on hyperglycemia or glucose detection using ECG has been constraine...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Atrial fibrillation (AF) is a common cardiac disease that potentially leads to fatal conditions. Machine Learning (ML) classification methods are widely used to distinguish between sinus rhythm and AF for post-ablation rhythms in ECG. However, intrac...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
In practical scenarios involving the measurement of surface electromyography (sEMG) in muscles, particularly those areas near the heart, one of the primary sources of contamination is the presence of electrocardiogram (ECG) signals. To assess the qua...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Electrocardiogram data provide a tremendous opportunity for the detection of various types of cardiac arrhythmia. Recent advancement in ubiquitous wearable devices with incorporated ECG sensors offers an opportunity for a real-time monitoring system ...