AIMC Topic: Signal Processing, Computer-Assisted

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HiRENet: Novel convolutional neural network architecture using Hilbert-transformed and raw electroencephalogram (EEG) for subject-independent emotion classification.

Computers in biology and medicine Jun 27, 2024
BACKGROUND AND OBJECTIVES: Convolutional neural networks (CNNs) are the most widely used deep-learning framework for decoding electroencephalograms (EEGs) due to their exceptional ability to extract hierarchical features from high-dimensional EEG dat...
Electroencephalography Humans Signal Processing, Computer-Assisted Neural Networks, Computer Deep Learning Brain Emotions
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Higher-Order Spectral Analysis Combined with a Convolution Neural Network for Atrial Fibrillation Detection-Preliminary Study.

Sensors (Basel, Switzerland) Jun 27, 2024
The global burden of atrial fibrillation (AFIB) is constantly increasing, and its early detection is still a challenge for public health and motivates researchers to improve methods for automatic AFIB prediction and management. This work proposes hig...
Neural Networks, Computer Algorithms ROC Curve Electrocardiography Humans Signal Processing, Computer-Assisted Atrial Fibrillation
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Feature evaluation for myoelectric pattern recognition of multiple nearby reaching targets.

Medical engineering & physics Jun 26, 2024
Intention detection of the reaching movement is considerable for myoelectric human and machine collaboration applications. A comprehensive set of handcrafted features was mined from windows of electromyogram (EMG) of the upper-limb muscles while reac...
Movement Young Adult Adult Humans Support Vector Machine Electromyography Male Female Activities of Daily Living Signal Processing, Computer-Assisted Pattern Recognition, Automated
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Clinical knowledge-based ECG abnormalities detection using dual-view CNN-Transformer and external attention mechanism.

Computers in biology and medicine Jun 26, 2024
BACKGROUND: Automatic abnormalities detection based on Electrocardiogram (ECG) contributes greatly to early prevention, computer aided diagnosis, and dynamic analysis of cardiovascular diseases. In order to achieve cardiologist-level performance, dee...
Signal Processing, Computer-Assisted Humans Neural Networks, Computer Diagnosis, Computer-Assisted Deep Learning Electrocardiography
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EMG-based prediction of step direction for a better control of lower limb wearable devices.

Computer methods and programs in biomedicine Jun 24, 2024
BACKGROUND AND OBJECTIVES: Lower-limb wearable devices can significantly improve the quality of life of subjects suffering from debilitating conditions, such as amputations, neurodegenerative disorders, and stroke-related impairments. Current control...
Algorithms Female Young Adult Adult Male Wearable Electronic Devices Humans Walking Muscle, Skeletal Support Vector Machine Signal Processing, Computer-Assisted Lower Extremity Electromyography
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ConvLSNet: A lightweight architecture based on ConvLSTM model for the classification of pulmonary conditions using multichannel lung sound recordings.

Artificial intelligence in medicine Jun 22, 2024
Characterization of lung sounds (LS) is indispensable for diagnosing respiratory pathology. Although conventional neural networks (NNs) have been widely employed for the automatic diagnosis of lung sounds, deep neural networks can potentially be more...
Lung Signal Processing, Computer-Assisted Respiratory Sounds Neural Networks, Computer Pulmonary Disease, Chronic Obstructive Asthma Humans
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Pulse wave signal-driven machine learning for identifying left ventricular enlargement in heart failure patients.

Biomedical engineering online Jun 22, 2024
BACKGROUND: Left ventricular enlargement (LVE) is a common manifestation of cardiac remodeling that is closely associated with cardiac dysfunction, heart failure (HF), and arrhythmias. This study aimed to propose a machine learning (ML)-based strateg...
Male Middle Aged Pulse Wave Analysis Female Aged Signal Processing, Computer-Assisted Heart Failure Hypertrophy, Left Ventricular Humans Machine Learning
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Intelligent deep model based on convolutional neural network's and multi-layer perceptron to classify cardiac abnormality in diabetic patients.

Physical and engineering sciences in medicine Jun 20, 2024
The ECG is a crucial tool in the medical field for recording the heartbeat signal over time, aiding in the identification of various cardiac diseases. Commonly, the interpretation of ECGs necessitates specialized knowledge. However, this paper explor...
Humans Neural Networks, Computer Diabetes Mellitus Signal Processing, Computer-Assisted Heart Diseases Algorithms Deep Learning Electrocardiography
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Multivariate modeling and prediction of cerebral physiology in acute traumatic neural injury: A scoping review.

Computers in biology and medicine Jun 20, 2024
Traumatic brain injury (TBI) poses a significant global public health challenge necessitating a profound understanding of cerebral physiology. The dynamic nature of TBI demands sophisticated methodologies for modeling and predicting cerebral signals ...
Humans Machine Learning Brain Multivariate Analysis Brain Injuries, Traumatic Signal Processing, Computer-Assisted
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EfficientNet-based machine learning architecture for sleep apnea identification in clinical single-lead ECG signal data sets.

Biomedical engineering online Jun 20, 2024
OBJECTIVE: Our objective was to create a machine learning architecture capable of identifying obstructive sleep apnea (OSA) patterns in single-lead electrocardiography (ECG) signals, exhibiting exceptional performance when utilized in clinical data s...
Sleep Apnea, Obstructive Signal Processing, Computer-Assisted Sleep Apnea Syndromes Female Humans Aged Male Machine Learning Adult Middle Aged Electrocardiography
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