Machine-learning-based automatic sleep stage scoring is a promising approach to enhance the time-consuming manual annotation process of polysomnography recordings. Although numerous algorithms have been proposed for this purpose, systematic explorati...
Electrocardiogram (ECG) signals are crucial in diagnosing cardiovascular diseases (CVDs). While wavelet-based feature extraction has demonstrated effectiveness in deep learning (DL)-based ECG diagnosis, selecting the optimal wavelet base poses a sign...
Accurate recognition and classification of motor imagery electroencephalogram (MI-EEG) signals are crucial for the successful implementation of brain-computer interfaces (BCI). However, inherent characteristics in original MI-EEG signals, such as non...
PURPOSE: Despite increased awareness of sleep hygiene, over 80% of sleep apnea cases remain undiagnosed, underscoring the need for accessible screening methods. This study presents a method for detecting sleep apnea using data from the Apple Watch's ...
BACKGROUND: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are both progressive neurological disorders that affect the elderly. Distinguishing between individuals suffering from these two diseases in the early stages can be quite challeng...
EEG signals exhibit spatio-temporal characteristics due to the neural activity dispersion in space over the brain and the dynamic temporal patterns of electrical activity in neurons. This study tries to effectively utilize the spatio-temporal nature ...
Medical & biological engineering & computing
Jan 30, 2025
With the advancement of artificial intelligence technology, more and more effective methods are being used to identify and classify Electroencephalography (EEG) signals to address challenges in healthcare and brain-computer interface fields. The appl...
International journal of medical informatics
Jan 30, 2025
BACKGROUND: Cardiac arrest (CA) is the sudden cessation of heart function, typically resulting in loss of consciousness and cessation of pulse and breathing. The electrocardiogram (ECG) stands as an essential tool extensively utilized by clinicians, ...
Journal of clinical monitoring and computing
Jan 29, 2025
Unobtrusive pulse rate monitoring by continuous video recording, based on remote photoplethysmography (rPPG), might enable early detection of perioperative arrhythmias in general ward patients. However, the accuracy of an rPPG-based machine learning ...
Biomedizinische Technik. Biomedical engineering
Jan 29, 2025
OBJECTIVES: In recent years, significant progress has been made in the research of gesture recognition using surface electromyography (sEMG) signals based on machine learning and deep learning techniques. The main motivation for sEMG gesture recognit...
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