Neuromuscular disorders detection through time-frequency analysis and classification of multi-muscular EMG signals using Hilbert-Huang transform

No abstract is available for this paper.

• Publication year

  2022

• Venue

  Biomedical Signal Processing and Control

• Publication date

  2022-01-01

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1016/j.bspc.2021.103037
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• DWT-based electromyogram signal classification using maximum likelihood-estimated features for neurodiagnostic applications

  2020cited by this paper
• Detecting Neuromuscular Disorders Using EMG Signals Based on TQWT Features

  2019cited by this paper
• Features based on variational mode decomposition for identification of neuromuscular disorder using EMG signals

  2018cited by this paper
• Arrhythmia detection using deep convolutional neural network with long duration ECG signals

  2018cited by this paper
• Neuromuscular disease detection by neural networks and fuzzy entropy on time‐frequency analysis of electromyography signals

  2018cited by this paper
• Diagnostic Accuracy of Muscle Biopsy and Electromyography in 123 Patients with Neuromuscular Disorders

  2018cited by this paper
• Classification of amyotrophic lateral sclerosis disease based on convolutional neural network and reinforcement sample learning algorithm

  2017cited by this paper
• DeepEMGNet: An Application for Efficient Discrimination of ALS and Normal EMG Signals

  2017cited by this paper
• An efficient method for analysis of EMG signals using improved empirical mode decomposition

  2017cited by this paper
• Classifying neuromuscular diseases using artificial neural networks with applied Autoregressive and Cepstral analysis

  2016cited by this paper
• Electromyogram Signals for Multiuser Interface- A Review

  2016cited by this paper
• Classification of neuromuscular disorders using features extracted in the wavelet domain of sEMG signals: a case study

  2016cited by this paper
• Single-Channel EMG Classification With Ensemble-Empirical-Mode-Decomposition-Based ICA for Diagnosing Neuromuscular Disorders

  2016cited by this paper
• An EMG-based feature extraction method using a normalized weight vertical visibility algorithm for myopathy and neuropathy detection

  2016cited by this paper
• Electromyography (EMG) based Classification of Neuromuscular Disorders using Multi-Layer Perceptron

  2015cited by this paper
• Comparison of decision tree algorithms for EMG signal classification using DWT

  2015cited by this paper
• Analysis of Extracted Forearm sEMG Signal Using LDA, QDA, K-NN Classification Algorithms

  2014cited by this paper
• An adaptive level dependent wavelet thresholding for ECG denoising

  2014cited by this paper
• Effect of multiscale PCA de-noising on EMG signal classification for diagnosis of neuromuscular disorders

  2014cited by this paper
• Variational Mode Decomposition

  2014cited by this paper
• 21. Neuromuscular Disorders

  2014cited by this paper
• Characterizing EMG data using machine-learning tools

  2014cited by this paper
• Improved complete ensemble EMD: A suitable tool for biomedical signal processing

  2014cited by this paper
• Wavelet Domain Feature Extraction Scheme Based on Dominant Motor Unit Action Potential of EMG Signal for Neuromuscular Disease Classification

  2014cited by this paper
• Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders

  2013cited by this paper
• Empirical Mode Decomposition-Based Time-Frequency Analysis of Multivariate Signals: The Power of Adaptive Data Analysis

  2013cited by this paper
• Empirical Wavelet Transform

  2013cited by this paper
• 16 – Clinical–Electrophysiologic Correlations: Overview and Common Patterns

  2013cited by this paper
• Linear Discriminant Analysis

  2013cited by this paper
• Linear Discriminant Analysis

  2013cited by this paper
• Multiresolution MUAPs decomposition and SVM-based analysis in the classification of neuromuscular disorders

  2012cited by this paper
• Multi-scale AM-FM analysis for the classification of surface electromyographic signals

  2012cited by this paper
• Classification of EMG signals using combined features and soft computing techniques

  2012cited by this paper
• Comparison of Empirical Mode Decomposition and Wavelet Based Classification of Power Quality Events

  2012cited by this paper
• EMGTools, an Adaptive and Versatile Tool for Detailed EMG Analysis

  2011cited by this paper
• Analysis and classification of compressed EMG signals by wavelet transform via alternative neural networks algorithms

  2011cited by this paper
• Probabilistic muscle characterization using QEMG: Application to neuropathic muscle

  2010cited by this paper
• Intramuscular EMG signal decomposition.

  2010cited by this paper
• Biosignal Denoising via Wavelet Thresholds

  2010cited by this paper
• Complementary Ensemble Empirical Mode Decomposition: a Novel Noise Enhanced Data Analysis Method

  2010cited by this paper
• Multiscale entropy-based approach to automated surface EMG classification of neuromuscular disorders

  2010cited by this paper
• Signal feature extraction based on an improved EMD method

  2009cited by this paper
• K-nearest neighbor

  2009cited by this paper
• Surface EMG analysis on normal subjects based on isometric voluntary contraction.

  2009cited by this paper
• Ensemble Empirical Mode Decomposition: a Noise-Assisted Data Analysis Method

  2009cited by this paper
• Use of Surface Electromyography (EMG) in the Diagnosis of Childhood Hypertonia: A Pilot Study

  2008cited by this paper
• Analysis of neuromuscular disorders using statistical and entropy metrics on surface EMG

  2008cited by this paper
• Myoelectric control systems - A survey

  2007cited by this paper
• Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis

  2006cited by this paper
• Mean frequency derived via Hilbert-Huang transform with application to fatigue EMG signal analysis

  2006cited by this paper
• Interrater reliability of the needle examination in lumbosacral radiculopathy

  2006cited by this paper
• Use of Support Vector Machines and Neural Network in Diagnosis of Neuromuscular Disorders

  2005cited by this paper
• Unsupervised pattern recognition for the classification of EMG signals

  1999cited by this paper
• Decomposition of multiunit electromyographic signals

  1999cited by this paper
• The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

  1998cited by this paper
• E. Fix and J.L. Hodges (1951): An Important Contribution to Nonparametric Discriminant Analysis and Density Estimation: Commentary on Fix and Hodges (1951)

  1989cited by this paper
• Induction of Decision Trees

  1986cited by this paper
• Effective use of EMG parameters in the assessment of neuromuscular diseases.

  1982cited by this paper
• Action potential parameters in normal human muscle and their dependence on physical variables.

  1954cited by this paper

• Artificial Intelligence and Neuromuscular Diseases: A Narrative Review

  2026cites this paper
• Motion Pattern Recognition Based on Surface Electromyography Data and Machine Learning Classifiers: Preliminary Study

  2025cites this paper
• Classification of Finger Movement Using EMG Sensor Signal

  2025cites this paper
• iEMG-Based Diagnosis of ALS and Myopathy using 1D-CNN

  2025cites this paper
• Electromyography Signal Classification With Artificial Intelligence for Detection of Neuromuscular Disorders Using a Large Clinically‐Acquired Database

  2025cites this paper
• Iterative eigenvalue decomposition of Hankel matrix: An EMD like tool

  2025cites this paper
• Classical and Quantum SVM for Electromyography-Based Myopathy Detection: A Comparative Exploration

  2025cites this paper
• Differentiating characteristics of EMG signals in pediatric muscle tone disorders in the aspect of evaluating postural control

  2025cites this paper
• Empirical mode decomposition in clinical signal analysis: A systematic review

  2025cites this paper
• Continuous Joint Kinematics Prediction Using GAT-LSTM Framework Based on Muscle Synergy and Sparse sEMG

  2025cites this paper
• Research and Improvement Methods for EMD on the Basis of Statistical Models

  2025cites this paper
• Deep Learning Classification of Simulated Surface EMG Signals across Maximum Voluntary Contraction Levels

  2025influential citation
• MoEMba: A Mamba-based Mixture of Experts for High-Density EMG-based Hand Gesture Recognition

  2025cites this paper
• Revolutionizing ALS Assessment: XGBoost Classification with Progressive Entropy Weighted-based Focal Loss on Gene Sequences

  2025cites this paper
• Detection, identification and removing of artifacts from sEMG signals: Current studies and future challenges

  2025cites this paper
• A machine learning approach for the design optimization of a multiple magnetic and inertial sensors wearable system for the spine mobility assessment

  2024cites this paper
• Artificial intelligence for automatic classification of needle EMG signals: A scoping review.

  2024cites this paper
• Towards a diagnostic tool for neurological gait disorders in childhood combining 3D gait kinematics and deep learning

  2024cites this paper
• Recognition of Human Lower Limb Motion and Muscle Fatigue Status Using a Wearable FES-sEMG System

  2024cites this paper
• ALS Disease Detection in EMG using a Polynomial Compact Support Kernel-based Time-Frequency Distribution and CNN

  2024cites this paper
• A critical review on system architecture, techniques, trends and challenges in intelligent predictive maintenance

  2024cites this paper
• A clinical decision support system for diagnosis and severity quantification of lumbosacral radiculopathy using intramuscular electromyography signals

  2024cites this paper
• Characterizing the onset of transitional and turbulent flow regimes in pipe flows using instantaneous time-frequency-based analysis

  2024cites this paper
• EEG Graph-Based Disease Analysis: A Novel Approach to Neurological Disorder Diagnosis

  2024cites this paper
• AML-DECODER: Advanced Machine Learning for HD-sEMG Signal Classification—Decoding Lateral Epicondylitis in Forearm Muscles

  2024cites this paper
• Enhancing EMG signal classification using convolution neural network optimized with fractional order bat algorithm

  2024cites this paper
• Comprehensive Review of Feature Extraction Techniques for sEMG Signal Classification: From Handcrafted Features to Deep Learning Approaches

  2024cites this paper
• Intra- and inter-channel deep convolutional neural network with dynamic label smoothing for multichannel biosignal analysis

  2024cites this paper
• Gesture recognition based on Gramian angular difference field and multi-stream fusion methods

  2024cites this paper
• Classification of Myopathy and Normal Electromyogram (EMG) Data with a New Deep Learning Architecture

  2023cites this paper
• Classification of intramuscular EMG signals using a separable compact support kernel-based timefrequency distribution and deep transfer learning

  2023cites this paper
• EMG Signal Classification Using Deep Learning and Time Domain Descriptors-Based Feature Extraction for Hand Grip Movement Recognition

  2023cites this paper
• Stretchable array electromyography sensor with graph neural network for static and dynamic gestures recognition system

  2023cites this paper
• Window length insensitive real-time EMG hand gesture classification using entropy calculated from globally parsed histograms

  2023cites this paper
• A neuro-fuzzy network modeling method for uncovering the dynamic properties of time-varying systems

  2023cites this paper
• Surface Electromyography and Artificial Intelligence for Human Activity Recognition—A Systematic Review on Methods, Emerging Trends Applications, Challenges, and Future Implementation

  2023cites this paper
• Comparison of KNN and Random Forest Algorithms in Classifying EMG Signals

  2023cites this paper
• Hand gesture classification framework leveraging the entropy features from sEMG signals and VMD augmented multi-class SVM

  2023cites this paper
• Signal Acquisition and Time–Frequency Perspective of EMG Signal-based Systems and Applications

  2023cites this paper
• Electromyography based hand movement classification and feature extraction using machine learning algorithms

  2023cites this paper
• Low Complex CORDIC-based Hand Movement Recognition Design Methodology for Rehabilitation and Prosthetic Applications

  2023cites this paper
• The role of artificial intelligence in electrodiagnostic and neuromuscular medicine: Current state and future directions

  2023cites this paper
• Use of Advanced Materials and Artificial Intelligence in Electromyography Signal Detection and Interpretation

  2022cites this paper
• Mobile Music Recognition based on Deep Neural Network

  2022cites this paper
• Prediction and Analysis of Muscular Paralysis Disease Using Daubechies Wavelet Approach

  2022cites this paper
• Classification of Myopathy and Amyotrophic Lateral Sclerosis Electromyograms Using Bat Algorithm and Deep Neural Networks

  2022cites this paper
• A Comprehensive Survey on the Detection, Classification, and Challenges of Neurological Disorders

  2022cites this paper
• A machine learning based frame work for classification of neuromuscular disorders

  2022cites this paper
• Effect of Emg Signals on Gesture Control: A Survey

  2022cites this paper
• Cardiac Abnormalities Detection Through 12-Lead/Reduced-Lead ECG Spectrograms and 2D-CRNN

  2021cites this paper