. sleep staging is essential for diagnosing sleep disorders and managing sleep health. Traditional methods require time-consuming manual scoring. Recent photoplethysmography (PPG)-based deep learning models perform well on local datasets but struggle...
Electrocardiogram (ECG) reconstruction involves synthesizing leads from a reduced or alternative lead set. While ECG leads are generally considered linearly related, recording distortions and individual differences make perfect replication difficult,...
In recent years, progress in artificial intelligence, particularly in the realm of deep learning, has resulted in substantial enhancements in the diagnosis of various medical conditions. This study introduces a framework that leverages multiple light...
Biomedical physics & engineering express
Nov 26, 2025
Auscultations are commonly used to analyze lung conditions through signal processing and classification techniques. However, the efficiency of these models is often limited by factors like signal quality, sensor performance, and dataset size. Current...
Biomedical physics & engineering express
Nov 25, 2025
As physiological artifacts commonly overlap with EEG signals in both time and frequency domains, developing an effective end-to-end EEG artifact removal method is essential for a brain-computer interface (BCI) system. An end-to-end artifact removal m...
Brain-computer interfaces (BCIs) hold significant promise for restoring communication in individuals with severe motor or speech impairments. Imagined handwriting, as a form of motor imagery, offers an intuitive paradigm for character-level neural de...
Partial discharge (PD) detection in power transformers is critical for preventing insulation failures in modern power grids, yet remains challenging due to signal complexity and environmental noise. Existing methods struggle with accurate PD classifi...
International journal of neural systems
Nov 19, 2025
This research looks at the use of long-short-term memory (LSTM) networks to predict psychosis, in patients within the schizophrenia spectrum, based on Heart Rate Variability (HRV) data acquired from wearable devices. Our primary objective is to test ...
Neonatal respiratory monitoring is crucial for assessing breathing patterns, but the lack of real-time clinical data limits the development of machine learning (ML) models. This study provides a synthetic signal generation framework to replicate infa...
Biomedical physics & engineering express
Nov 14, 2025
Electrocardiogram (ECG) and phonocardiogram (PCG) have emerged as crucial non-invasive and portable diagnostic modalities for early cardiovascular disease (CVD) screening. Despite the individual merits of these signal modalities in CVD detection, sig...
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