AIMC Topic: Signal Processing, Computer-Assisted
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Dual-pathway EEG model with channel attention for virtual reality motion sickness detection.
Journal of neuroscience methods
Mar 12, 2025
BACKGROUND: Motion sickness has been a key factor affecting user experience in Virtual Reality (VR) and limiting the development of the VR industry. Accurate detection of Virtual Reality Motion Sickness (VRMS) is a prerequisite for solving the proble...
Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease.
Scientific reports
Mar 12, 2025
Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the coronary arteries, responsible for supplying oxygenated blood to the heart, get occluded due to plaque deposits on their inner walls. The most critic...
Reconstruction of ECG from ballistocardiogram using generative adversarial networks with attention.
Biomedical physics & engineering express
Mar 12, 2025
Electrocardiogram (ECG) is widely used to provide early warning signals for cardiovascular diseases. However, traditional twelve-lead ECG monitoring methods and smartwatch-based home solutions are unable to achieve daily long-term monitoring. Therefo...
Identification of People in a Household Using Ballistocardiography Signals Through Deep Learning.
Sensors (Basel, Switzerland)
Mar 11, 2025
BACKGROUND: Various sensor technologies have been developed to monitor the health of older adults; however, most of them require attachment to the skin. This study aimed to develop a health monitoring system, using a non-adhesive, non-invasive polyvi...
Deep learning-based prediction of atrial fibrillation from polar transformed time-frequency electrocardiogram.
PloS one
Mar 10, 2025
Portable and wearable electrocardiogram (ECG) devices are increasingly utilized in healthcare for monitoring heart rhythms and detecting cardiac arrhythmias or other heart conditions. The integration of ECG signal visualization with AI-based abnormal...
Integrated fusion approach for multi-class heart disease classification through ECG and PCG signals with deep hybrid neural networks.
Scientific reports
Mar 8, 2025
Detection and classification of cardiovascular diseases are crucial for early diagnosis and prediction of heart-related conditions. Existing methods rely on either electrocardiogram or phonocardiogram signals, resulting in higher false positive rates...
Advance signal processing and machine learning approach for analysis and classification of knee osteoarthritis vibroarthrographic signals.
Medical engineering & physics
Mar 7, 2025
Osteoarthritis is a common cause of disability among elderly significantly affecting their quality of life due to pain and functional limitations. This study proposes a novel, non-invasive, and cost-effective diagnostic technique using vibroarthrogra...
The More, the Better? Evaluating the Role of EEG Preprocessing for Deep Learning Applications.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 7, 2025
The last decade has witnessed a notable surge in deep learning applications for electroencephalography (EEG) data analysis, showing promising improvements over conventional statistical techniques. However, deep learning models can underperform if tra...
LAST-PAIN: Learning Adaptive Spike Thresholds for Low Back Pain Biosignals Classification.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mar 7, 2025
Spiking neural networks (SNNs) present the potential for ultra-low-power computation, especially when implemented on dedicated neuromorphic hardware. However, a significant challenge is the efficient conversion of continuous real-world data into the ...
GLEAM: A multimodal deep learning framework for chronic lower back pain detection using EEG and sEMG signals.
Computers in biology and medicine
Mar 6, 2025
Low Back Pain (LBP) is the most prevalent musculoskeletal condition worldwide and a leading cause of disability, significantly affecting mobility, work productivity, and overall quality of life. Due to its high prevalence and substantial economic bur...
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