DCT domain feature extraction scheme based on motor unit action potential of EMG signal for neuromuscular disease classification
نویسندگان
چکیده
منابع مشابه
Comparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition
Background: Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impac...
متن کاملcomparative analysis of wavelet-based feature extraction for intramuscular emg signal decomposition
background: electromyographic (emg) signal decomposition is the process by which an emg signal is decomposed into its constituent motor unit potential trains (mupts). a major step in emg decomposition is feature extraction in which each detected motor unit potential (mup) is represented by a feature vector. as with any other pattern recognition system, feature extraction has a significant impac...
متن کاملA Multiclassifier Approach to Motor Unit Potential Classification for EMG Signal Decomposition
EMG signal decomposition is the process of resolving a composite EMG signal into its constituent motor unit potential trains (classes) and it can be configured as a classification problem. An EMG signal detected by the tip of an inserted needle electrode is the superposition of the individual electrical contributions of the different motor units that are active, during a muscle contraction, and...
متن کاملTechniques for Feature Extraction from EMG Signal
The myoelectric signal (MES) is one of the biosignals utilized in helping humans to control equipments. For this we required to recognize the hand movement. In this direction the first step is feature extraction. The optimal feature is important for the achievement in EMG analysis and control. By this extracted feature we reduce the computational cost of a multifunction myoelectric control syst...
متن کاملA Hybrid Classifier for Characterizing Motor Unit Action Potentials in Diagnosing Neuromuscular Disorders
Background: The time and frequency features of motor unit action potentials (MUAPs) extracted from electromyographic (EMG) signal provide discriminative information for diagnosis and treatment of neuromuscular disorders. However, the results of conventional automatic diagnosis methods using MUAP features is not convincing yet.Objective: The main goal in designing a MUAP characterization system ...
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ژورنال
عنوان ژورنال: Healthcare Technology Letters
سال: 2014
ISSN: 2053-3713,2053-3713
DOI: 10.1049/htl.2013.0036