AIMC Topic: Signal Processing, Computer-Assisted

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Optimized FFNN with multichannel CSP-ICA framework of EEG signal for BCI.

Computer methods in biomechanics and biomedical engineering Feb 26, 2024
The electroencephalogram (EEG) of the patient is used to identify their motor intention, which is then converted into a control signal through a brain-computer interface (BCI) based on motor imagery. Whenever gathering features from EEG signals, maki...
Signal Processing, Computer-Assisted Algorithms Humans Brain-Computer Interfaces Electroencephalography Neural Networks, Computer
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Person identification with arrhythmic ECG signals using deep convolution neural network.

Scientific reports Feb 23, 2024
Over the past decade, the use of biometrics in security systems and other applications has grown in popularity. ECG signals in particular are attracting increased attention due to their characteristics, which are required for a trustworthy identifica...
Humans Arrhythmias, Cardiac Neural Networks, Computer Electrocardiography Algorithms Signal Processing, Computer-Assisted Heart Rate Biometry
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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).
Electromagnetic Fields Radio Waves Deep Learning Image Processing, Computer-Assisted Signal Processing, Computer-Assisted Phantoms, Imaging Magnetic Resonance Imaging Algorithms Humans Brain
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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 ...
Deep Learning Mandible Electromyography Temporomandibular Joint Signal Processing, Computer-Assisted Young Adult Adult Male Humans Female Masseter Muscle Mastication
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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...
Algorithms Deep Learning Signal Processing, Computer-Assisted Fatigue Electroencephalography Humans Neural Networks, Computer
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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...
Algorithms Signal Processing, Computer-Assisted Neural Networks, Computer Gestures Electromyography
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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...
Female Adult Male Humans Neural Networks, Computer Deep Learning Treatment Outcome Electroencephalography Middle Aged Depressive Disorder, Major Signal Processing, Computer-Assisted Selective Serotonin Reuptake Inhibitors
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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...
Electrocardiography Signal Processing, Computer-Assisted Humans 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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