AIMC Topic: Signal Processing, Computer-Assisted

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A New ECG Denoising Framework Using Generative Adversarial Network.

IEEE/ACM transactions on computational biology and bioinformatics Apr 6, 2021
This paper presents a novel Electrocardiogram (ECG) denoising approach based on the generative adversarial network (GAN). Noise is often associated with the ECG signal recording process. Denoising is central to most of the ECG signal processing tasks...
Machine Learning Electrocardiography Algorithms Humans Signal Processing, Computer-Assisted Neural Networks, Computer Databases, Factual Arrhythmias, Cardiac
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Deep ANC: A deep learning approach to active noise control.

Neural networks : the official journal of the International Neural Network Society Apr 1, 2021
Traditional active noise control (ANC) methods are based on adaptive signal processing with the least mean square algorithm as the foundation. They are linear systems and do not perform satisfactorily in the presence of nonlinear distortions. In this...
Noise Least-Squares Analysis Signal Processing, Computer-Assisted Humans Deep Learning Speech
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Ensemble deep model for continuous estimation of Unified Parkinson's Disease Rating Scale III.

Biomedical engineering online Mar 31, 2021
BACKGROUND: Unified Parkinson Disease Rating Scale-part III (UPDRS III) is part of the standard clinical examination performed to track the severity of Parkinson's disease (PD) motor complications. Wearable technologies could be used to reduce the ne...
Humans Neural Networks, Computer Algorithms Middle Aged Severity of Illness Index Deep Learning Female Aged Male Signal Processing, Computer-Assisted Wearable Electronic Devices Parkinson Disease
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Multitask Feature Learning Meets Robust Tensor Decomposition for EEG Classification.

IEEE transactions on cybernetics Mar 17, 2021
In this article, we study a tensor-based multitask learning (MTL) method for classification. Taking into account the fact that in many real-world applications, the given training samples are limited and can be inherently arranged into multidimensiona...
Algorithms Electroencephalography Signal Processing, Computer-Assisted Humans Machine Learning
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Hybrid Prediction Method for ECG Signals Based on VMD, PSR, and RBF Neural Network.

BioMed research international Mar 15, 2021
To explore a method to predict ECG signals in body area networks (BANs), we propose a hybrid prediction method for ECG signals in this paper. The proposed method combines variational mode decomposition (VMD), phase space reconstruction (PSR), and a r...
Arrhythmias, Cardiac Databases, Factual Electrocardiography Signal Processing, Computer-Assisted Humans Neural Networks, Computer
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Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison.

Journal of neuroengineering and rehabilitation Feb 25, 2021
BACKGROUND: Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculatur...
Bionics Arm Movement Humans Machine Learning Young Adult Electromyography Artificial Limbs Activities of Daily Living Male Quality of Life Signal Processing, Computer-Assisted
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A Machine Learning Processing Pipeline for Reliable Hand Gesture Classification of FMG Signals with Stochastic Variance.

Sensors (Basel, Switzerland) Feb 22, 2021
ForceMyography (FMG) is an emerging competitor to surface ElectroMyography (sEMG) for hand gesture recognition. Most of the state-of-the-art research in this area explores different machine learning algorithms or feature engineering to improve hand g...
Hand Electromyography Humans Machine Learning Algorithms Gestures Signal Processing, Computer-Assisted
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Reduced Adaptive Fuzzy Decoupling Control for Lower Limb Exoskeleton.

IEEE transactions on cybernetics Feb 17, 2021
This article reports our study on a reduced adaptive fuzzy decoupling control for our lower limb exoskeleton system which typically is a multi-input-multi-output (MIMO) uncertain nonlinear system. To show the applicability and generality of the propo...
Nonlinear Dynamics Exoskeleton Device Fuzzy Logic Lower Extremity Equipment Design Signal Processing, Computer-Assisted Walking Gait Machine Learning Algorithms Biomechanical Phenomena Humans
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SpikeDeep-classifier: a deep-learning based fully automatic offline spike sorting algorithm.

Journal of neural engineering Feb 5, 2021
Advancements in electrode design have resulted in micro-electrode arrays with hundreds of channels for single cell recordings. In the resulting electrophysiological recordings, each implanted electrode can record spike activity (SA) of one or more ne...
Animals Deep Learning Action Potentials Signal Processing, Computer-Assisted Neurons Electrodes, Implanted Humans Algorithms
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Deep Representation-Based Domain Adaptation for Nonstationary EEG Classification.

IEEE transactions on neural networks and learning systems Feb 4, 2021
In the context of motor imagery, electroencephalography (EEG) data vary from subject to subject such that the performance of a classifier trained on data of multiple subjects from a specific domain typically degrades when applied to a different subje...
Movement Image Processing, Computer-Assisted Brain Mapping Electroencephalography Signal Processing, Computer-Assisted Algorithms Neuroimaging Reproducibility of Results Brain-Computer Interfaces Deep Learning Humans Neural Networks, Computer
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