AIMC Topic: Signal Processing, Computer-Assisted

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Robust EMI elimination for RF shielding-free MRI through deep learning direct MR signal prediction.

Magnetic resonance in medicine Feb 20, 2024
PURPOSE: To develop a new electromagnetic interference (EMI) elimination strategy for RF shielding-free MRI via active EMI sensing and deep learning direct MR signal prediction (Deep-DSP).
Algorithms Brain Image Processing, Computer-Assisted Magnetic Resonance Imaging Deep Learning Humans Electromagnetic Fields Signal Processing, Computer-Assisted Phantoms, Imaging Radio Waves
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Deep learning and predictive modelling for generating normalised muscle function parameters from signal images of mandibular electromyography.

Medical & biological engineering & computing Feb 20, 2024
Challenges arise in accessing archived signal outputs due to proprietary software limitations. There is a notable lack of exploration in open-source mandibular EMG signal conversion for continuous access and analysis, hindering tasks such as pattern ...
Young Adult Mastication Adult Mandible Temporomandibular Joint Humans Signal Processing, Computer-Assisted Masseter Muscle Female Electromyography Male Deep Learning
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A novel deep-learning model based on τ-shaped convolutional network (τNet) with long short-term memory (LSTM) for physiological fatigue detection from EEG and EOG signals.

Medical & biological engineering & computing Feb 20, 2024
In recent years, fatigue driving has become the main cause of traffic accidents, leading to increased attention towards fatigue detection systems. However, the pooling and strided convolutional operations in fatigue detection algorithm based on tradi...
Fatigue Neural Networks, Computer Algorithms Electroencephalography Deep Learning Humans Signal Processing, Computer-Assisted
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A multi-branch convolutional neural network for snoring detection based on audio.

Computer methods in biomechanics and biomedical engineering Feb 19, 2024
Obstructive sleep apnea (OSA) is associated with various health complications, and snoring is a prominent characteristic of this disorder. Therefore, the exploration of a concise and effective method for detecting snoring has consistently been a cruc...
Convolutional Neural Networks Signal Processing, Computer-Assisted Snoring Humans Neural Networks, Computer
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The Impact of Feature Extraction on Classification Accuracy Examined by Employing a Signal Transformer to Classify Hand Gestures Using Surface Electromyography Signals.

Sensors (Basel, Switzerland) Feb 16, 2024
Interest in developing techniques for acquiring and decoding biological signals is on the rise in the research community. This interest spans various applications, with a particular focus on prosthetic control and rehabilitation, where achieving prec...
Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms Electromyography Gestures
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Prediction of treatment response in major depressive disorder using a hybrid of convolutional recurrent deep neural networks and effective connectivity based on EEG signal.

Physical and engineering sciences in medicine Feb 15, 2024
In this study, we have developed a novel method based on deep learning and brain effective connectivity to classify responders and non-responders to selective serotonin reuptake inhibitors (SSRIs) antidepressants in major depressive disorder (MDD) pa...
Signal Processing, Computer-Assisted Selective Serotonin Reuptake Inhibitors Treatment Outcome Electroencephalography Adult Male Depressive Disorder, Major Deep Learning Middle Aged Neural Networks, Computer Female Humans
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A Q-transform-based deep learning model for the classification of atrial fibrillation types.

Physical and engineering sciences in medicine Feb 14, 2024
According to the World Health Organization (WHO), Atrial Fibrillation (AF) is emerging as a global epidemic, which has resulted in a need for techniques to accurately diagnose AF and its various subtypes. While the classification of cardiac arrhythmi...
Humans Electrocardiography Signal Processing, Computer-Assisted Atrial Fibrillation Neural Networks, Computer Deep Learning
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Classification of EMG signals with CNN features and voting ensemble classifier.

Computer methods in biomechanics and biomedical engineering Feb 5, 2024
Electromyography (EMG) signals are primarily used to control prosthetic hands. Classifying hand gestures efficiently with EMG signals presents numerous challenges. In addition to overcoming these challenges, a successful combination of feature extrac...
Hand Electromyography Voting Algorithms Signal Processing, Computer-Assisted Humans Neural Networks, Computer
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Scalar invariant transform based deep learning framework for detecting heart failures using ECG signals.

Scientific reports Feb 1, 2024
Heart diseases are leading to death across the globe. Exact detection and treatment for heart disease in its early stages could potentially save lives. Electrocardiogram (ECG) is one of the tests that take measures of heartbeat fluctuations. The devi...
Signal Processing, Computer-Assisted Heart Failure Arrhythmias, Cardiac Deep Learning Humans Algorithms Electrocardiography
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Exploring Convolutional Neural Network Architectures for EEG Feature Extraction.

Sensors (Basel, Switzerland) Jan 29, 2024
The main purpose of this paper is to provide information on how to create a convolutional neural network (CNN) for extracting features from EEG signals. Our task was to understand the primary aspects of creating and fine-tuning CNNs for various appli...
Signal Processing, Computer-Assisted Interior Design and Furnishings Neural Networks, Computer Electroencephalography
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