Biomedical physics & engineering express
Feb 21, 2025
Early Diagnosis of Cardiovascular disease (CVD) is essential to prevent a person from death in case of a cardiac arrhythmia. Automated ECG classification is required because manual classification by cardiologists is laborious, time-consuming, and pro...
IEEE transactions on bio-medical engineering
Feb 20, 2025
OBJECTIVE: Ventricular arrhythmias are the primary arrhythmias that cause sudden cardiac death. We address the problem of classification between ventricular tachycardia (VT), ventricular fibrillation (VF) and non-ventricular rhythms (NVR).
IEEE transactions on bio-medical engineering
Feb 20, 2025
Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offer promising solutions, they of...
Accurate prediction of Parkinson's disease tremor (PDT) is crucial for developing assistive technologies; however, this is challenging due to the nonlinear, stochastic, and nonstationary characteristics of PDT, which substantially vary among patients...
The limited availability of labeled ECG data restricts the application of supervised deep learning methods in ECG detection. Although existing self-supervised learning approaches have been applied to ECG analysis, they are predominantly image-based, ...
Alcoholism, a progressive loss of control over alcohol consumption, deteriorates mental and physical health over time. Automatic alcoholism detection can aid in early interventions and timely corrective actions. For this purpose, electroencephalogram...
In order to detect epileptic spikes, this paper suggests a deep learning architecture that blends 1D residual convolutional neural networks (1D-ResCNN) with a hybrid optimization strategy. The Layer-wise Adaptive Moments (LAMB) and AdamW algorithms h...
Journal of medical engineering & technology
Feb 14, 2025
Developing a robust and effective technique is crucial for interpreting a user's brainwave signals accurately in the realm of biomedical signal processing. The variability and uncertainty present in EEG patterns over time, compounded by noise, pose n...
Journal of medical engineering & technology
Feb 14, 2025
The work proposes a methodology for five different classes of ECG signals. The methodology utilises moving average filter and discrete wavelet transformation for the remove of baseline wandering and powerline interference. The preprocessed signals ar...
Wearable technology has expanded the applications of photoplethysmography (PPG) in remote health monitoring, enabling real-time measurement of various physiological parameters, such as heart rate (HR), heart rate variability (HRV), and respiration ra...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.