AIMC Topic: Signal Processing, Computer-Assisted

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sEMG-Based Gesture Recognition via Multi-Feature Fusion Network.

IEEE journal of biomedical and health informatics Apr 4, 2025
The sparse surface electromyography-based gesture recognition suffers from the problems of feature information not richness and poor generalization to small sample data. Therefore, a multi-feature fusion network (MFF-Net) model is proposed in this pa...
Algorithms Female Young Adult Adult Male Gestures Signal Processing, Computer-Assisted Humans Electromyography Neural Networks, Computer Pattern Recognition, Automated
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Decoding SSVEP Via Calibration-Free TFA-Net: A Novel Network Using Time-Frequency Features.

IEEE journal of biomedical and health informatics Apr 4, 2025
Brain-computer interfaces (BCIs) based on steady-state visual evoked potential (SSVEP) signals offer high information transfer rates and non-invasive brain-to-device connectivity, making them highly practical. In recent years, deep learning technique...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Evoked Potentials, Visual Female Young Adult Adult Male Humans Deep Learning Neural Networks, Computer Electroencephalography Algorithms
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Ankle Kinematics Estimation Using Artificial Neural Network and Multimodal IMU Data.

IEEE journal of biomedical and health informatics Apr 4, 2025
Inertial measurement units (IMUs) have become attractive for monitoring joint kinematics due to their portability and versatility. However, their limited accuracy, inability to analyze data in real-time, and complex data fusion algorithms requiring p...
Accelerometry Ankle Joint Ankle Female Young Adult Adult Biomechanical Phenomena Male Signal Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
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A Hybrid Artificial Intelligence System for Automated EEG Background Analysis and Report Generation.

IEEE journal of biomedical and health informatics Apr 4, 2025
Electroencephalography (EEG) plays a crucial role in the diagnosis of various neurological disorders. However, small hospitals and clinics often lack advanced EEG signal analysis systems and are prone to misinterpretation in manual EEG reading. This ...
Humans Deep Learning Electroencephalography Signal Processing, Computer-Assisted Young Adult Adult Male Artificial Intelligence Algorithms Female
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TrustEMG-Net: Using Representation-Masking Transformer With U-Net for Surface Electromyography Enhancement.

IEEE journal of biomedical and health informatics Apr 4, 2025
Surface electromyography (sEMG) is a widely employed bio-signal that captures human muscle activity via electrodes placed on the skin. Several studies have proposed methods to remove sEMG contaminants, as non-invasive measurements render sEMG suscept...
Signal-To-Noise Ratio Muscle, Skeletal Signal Processing, Computer-Assisted Electromyography Humans Neural Networks, Computer Algorithms
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DC-ASTGCN: EEG Emotion Recognition Based on Fusion Deep Convolutional and Adaptive Spatio-Temporal Graph Convolutional Networks.

IEEE journal of biomedical and health informatics Apr 4, 2025
Thanks to advancements in artificial intelligence and brain-computer interface (BCI) research, there has been increasing attention towards emotion recognition techniques based on electroencephalogram (EEG) recently. The complexity of EEG data poses a...
Humans Neural Networks, Computer Brain Emotions Signal Processing, Computer-Assisted Adult Electroencephalography Brain-Computer Interfaces Deep Learning
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Prediction of IUGR condition at birth by means of CTG recordings and a ResNet model.

Computers in biology and medicine Apr 3, 2025
OBJECTIVE: Sub-optimal uterine-placental perfusion and fetal nutrition can lead to intrauterine growth restriction (IUGR), also called fetal growth restriction (FGR). Antenatal cardiotocography (CTG) can aid in the early detection of IUGR. Reliably d...
Pregnancy Female Infant, Newborn Humans Neural Networks, Computer Fetal Growth Retardation Deep Learning Cardiotocography Signal Processing, Computer-Assisted
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An Energy-Efficient Configurable 1-D CNN-Based Multi-Lead ECG Classification Coprocessor for Wearable Cardiac Monitoring Devices.

IEEE transactions on biomedical circuits and systems Apr 3, 2025
Many electrocardiogram (ECG) processors have been widely used for cardiac monitoring. However, most of them have relatively low energy efficiency, and lack configurability in classification leads number and inference algorithm models. A multi-lead EC...
Signal Processing, Computer-Assisted Algorithms Wearable Electronic Devices Humans Electrocardiography Neural Networks, Computer
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Hardware Optimization and Implementation of a 16-Channel Neural Tree Classifier for On-Chip Closed-Loop Neuromodulation.

IEEE transactions on biomedical circuits and systems Apr 2, 2025
This work presents the development of on-chip machine learning (ML) classifiers for implantable neuromodulation system-on-chips (SoCs), aimed at detecting epileptic seizures for closed-loop neuromodulation applications. Tree-based classifiers have ga...
Humans Neural Networks, Computer Machine Learning Seizures Signal Processing, Computer-Assisted Algorithms Electroencephalography Epilepsy
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Parallel convolutional neural networks for non-invasive cardiac hemodynamic estimation: integrating uncalibrated PPG signals with nonlinear feature analysis.

Physiological measurement Mar 31, 2025
Understanding cardiac hemodynamic status (CHS) is essential for accurate cardiovascular health assessment, as it is governed by key parameters such as cardiac output (CO), systemic vascular resistance (SVR), and arterial compliance (AC). This study a...
Hemodynamics Nonlinear Dynamics Adult Deep Learning Photoplethysmography Male Convolutional Neural Networks Humans Signal Processing, Computer-Assisted Middle Aged Neural Networks, Computer Heart Female
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