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Electrocardiograms are bioelectrical signals that provide information regarding the normal and abnormal physiology of the heart. Early detection of cardiac irregularities in cardiac patients prevents strokes and sudden deaths. The effective functioning ...

This study investigates the mitigation of cognitive flexibility decrements during long-endurance Uncrewed Aerial Systems (UAS) missions through visual alerts. UAS mishaps are likely partially attributable to decreased cognitive flexibility caused by ...

A new 4:2 approximate compressor is designed based on gate diffusion input (GDI), which has 14 transistors and only 6 errors in its outputs. The integration of the GDI with the dynamic threshold (DT) overcomes the body effect by the selection of ...

With a rapid advance of the technology, side-channel attacks are gaining more attention in the security evaluation of electronic devices. The impact of the attacks on medical devices can be very dangerous: from retrieving private health data to ...

Cardiovascular diseases, including all types of arrhythmias, are the leading cause of death. Deep learning (DL)-based electrocardiography (ECG) diagnosis systems have attracted considerable attention in recent years. However, training DL-based ...

• This paper presents a novel self-supervised residual convolution neural network for actual arrhythmia classification.
• Convolution layers, and Residual blocks are integrated to improve model diagnostic performance.
• The novel pre-...

Electrocardiogram (ECG) signals are of great clinical value for the diagnosis and detection of heart disease. However, current ECG signal recognition research has problems such as large signal morphological differences, unbalanced data distribution, and ...

Detecting repetitive and periodic temporal patterns is essential for accurate predictions and informed decision-making in various domains of sequence learning. In RNN-based approaches to sequence learning, gated RNNs, such as long short-term ...

Heart related diseases have created a major loss in human lives. Healthy heart ensures good standard of living from infant to aged people for a long period. Predicting heart related diseases prior to serious cause would mostly reduce death and ...

ECG classification is a typical and practical multivariate time series classification task. Recently, ECG classification with deep networks has been widely researched and achieved promising results. However, most of existing works focus on multi-...${}_{\mathrm{}}$

The malfunctioning of cardiac autonomic control in epileptic patients develops ventricular tachyarrhythmia and causes sudden unexpected death in epilepsy patients (SUDEP). Various clinical studies investigated the effect of epilepsy on cardiac ...

Arousal detection is of great importance to measure sleep quality. Traditional diagnosis of arousal that relies on polysomnography (PSG) signals is cumbersome and costly, requiring an overnight stay in a sleep laboratory with multiple sensors ...

Myocardial infarction (MI) is a critical cardiovascular disease that requires a timely and accurate diagnosis to prevent severe outcomes. Clinically, MI is located according to the diagnostic criteria of the 12-lead electrocardiogram (ECG). ...

In this paper, a novel approach of Electrocardiogram (<Formula format="inline"><TexMath><?TeX $ECG$ ?></TexMath><File name="a00--inline1" type="gif"/></Formula>) denoising, is proposed and is based on Transformation Matrix for Non-Decimated Wavelet ...

Recent progress in deep learning has sparked widespread interest in their development and adoption of diverse applications. The effectiveness of deep neural networks, particularly in extracting meaningful patterns from multimedia data, has ...

As the popularity of wearables continues to scale, a substantial portion of the population has now access to (self-)monitorization of cardiovascular activity. In particular, the use of ECG wearables is growing in the realm of occupational health ...

This work introduces an enhanced methodology in the domain of eXplainable Artificial Intelligence (XAI) for visualizing local explanations of black-box, feature-based models, such as LIME and SHAP, enabling both domain experts and non-specialists ...

Electrocardiogram is the most essential diagnostic test for heart disease detection in this era, where it has low frequency and small amplitude, making it vulnerable to a variety of stimuli, including high/low-frequency noises resulting in ...

This study investigates whether the electrocardiogram (ECG) signal of pilots shows responsiveness towards unexpected events in highly dynamic environments. These event-related heart rate (HR) responses are manifestations of arousal and might ...

The purpose of this study is to quantify the fear during walking in VR space. We conduct an experiment where subjects walk up and down steps in real and VR spaces. A path with steps of 10cm high was placed in the real and VR spaces. Subjects wore ...

Sleep apnea (SA) is a sleep-related breathing disorder characterized by breathing pauses during sleep. A person’s sleep schedule is significantly influenced by that person’s hectic lifestyle, which may include unhealthy eating habits and their ...