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Feature Extraction and Classification of Neuromuscular Diseases Using Scanning EMG
(IEEE, 2014)
In this study a new dataset are prepared for neuromuscular diseases using scanning EMG method and four new features are extracted. These features are maximum amplitude, phase duration at the maximum amplitude, maximum ...
New features for scanned bioelectrical activity of motor unit in health and disease
(Elsevier, 2018-03)
The present study aims to find new features that support the differential diagnosis of neuromuscular diseases. Scanning EMG is an experimental method developed for understanding the motor unit organization and for observing ...
Classification of Neuromuscular Junction and Tendon Recordings of Neuromuscular Diseases by Their Spectrogram
(IEEE, 2017)
In this study, the effect of spectrograms from neuromuscular junction and tendon records for normal, neurogenic and myopathic motor units being constructed via EMG Simulator v3.6 on the differential diagnosis were investigated. ...
The effect of recording site on extracted features of motor unit action potential
(Elsevier, 2016)
Motor unit action potential (MUAP), which consists of individual muscle fiber action potentials (MFAPs), represents the electrical activity of the motor unit. The values of the MUAP features are changed by denervation and ...
Classification of Neuromuscular Diseases in Neuromuscular Junction and Tendon Recordings with Needle EMG by Using Welch's Method
(IEEE, 2017)
In this study, the power spectral density of simulated data which contain neuromuscular diseases and normal motor unit (i.e. control group) scenarios was calculated using Welch's method. Furthermore, the effect of Welch's ...
Determining Phase Duration of Scanning EMG Signals
(IEEE, 2015)
There are more than one motor unit activities recorded simultaneously during scanning EMG recordings. It is not possible to determine the phase duration correctly by inspecting only one sweep. The other motor unit activities, ...
Classification of juvenile myoclonic epilepsy data acquired through scanning electromyography with machine learning algorithms
(Springer, 2012)
In this paper, classification of Juvenile Myoclonic Epilepsy (JME) patients and healthy volunteers included into Normal Control (NC) groups was established using Feed-Forward Neural Networks (NN), Support Vector Machines ...
