U-Net has gained traction in biomedical signal processing, particularly for segmenting 1D waveforms. Building on this success, we propose a U-Net-inspired architecture that integrates both 2D and 1D CNNs to effectively learn and segment gastroesophag...
PURPOSE: Cyclic alternating patterns (CAP) of sleep can be observed through electroencephalogram (EEG) signals. Analyzing CAP can provide valuable insights into different abnormalities relating to sleep. CAP comprises of two phases: A and B, characte...
. This exploratory study investigates cyclical changes in physiological features across the menstrual cycle in women with epilepsy, focusing on their potential relationship with seizure occurrence.. Nocturnal data during sleep were collected from two...
The burgeoning necessity for copious and diverse electrocardiogram (ECG) datasets for deep learning applications in clinical diagnostics has been impeded by the confidential nature of patient data. Related works have shown the effectiveness of additi...
Sleep is a cyclic physiological process that goes into different stages, and every stage has its' importance in the construction or recovery of physiological function. Sleep scoring is performed from polysomnography recordings which requires signals ...
Surface electromyography (EMG) provides a non-invasive human-machine interaction interface that can promote the coherence of human-machine interaction operations. Decomposing surface electromyographic signals into hand joint angles in real time can b...
Cardiovascular disease (CVD) is the top cause of mortality globally, making it crucial to diagnose arrhythmias promptly and accurately for the early prevention and treatment of CVD. While numerous methods exist for detecting arrhythmias using ECG sig...
Biomedical physics & engineering express
Oct 15, 2025
Electrocardiogram (ECG) is essential for assessing heart function, but manual analysis is time-consuming and error-prone. Automated ECG analysis can improve early detection of cardiovascular diseases by accurately identifying abnormal beats despite s...
Transcranial Electrical Stimulation (tES) is a non-invasive neuromodulation technique that generates artifacts in simultaneous EEG recordings, hindering brain activity analysis. This study analyzes Machine Learning (ML) methods for tES noise artifact...
In response to the limited detection accuracy of traditional orthogonal frequency division multiplexing systems in complex wireless channel environments, this study first uses conditional generative adversarial networks to construct a single input/ou...
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