Abstract
Characterization of Electromyogram (EMG) signals is important for identifying neuromuscular diseases. Although various techniques were implemented for classification, none of them were implemented in the complexity domain. In this study, characterization of EMG signals recorded from healthy, neuropathic and myopathic subjects has been performed in complexity domain based on Multiscale Entropy (MSE) method. To do this, the multiscale entropy method has been applied to an EMG database publicly available in PhysioNet. The complexity profile curves obtained with the MSE approach have shown promising classification among healthy subject, neuropathic and myopathic patients in terms of complexity. One way ANOVA test has shown statistically significant differences (p<0.01) among these three classes. Moreover, Support Vector Machine (SVM) has demonstrated a classification accuracy of 86.1% for characterizing EMG signals of neuromuscular disorders. Furthermore, myopathic and neuropathic patients have been recognized with 66.7% sensitivity at 95.8% specificity and 100% sensitivity at 100% specificity respectively.
Highlights
Neuromuscular diseases are disorders that affect nerve or muscle, neuromuscular junctions, and muscle tissue
As the sample entropy values of EMG signals recorded from patients suffering from neuromuscular diseases do not intersect one another in the complexity domain for the majority of the scale factors, these neuromuscular diseases can be detected by the Multiscale Entropy (MSE) approach in complexity domain
Healthy subject and patients affected by neuromuscular diseases can be identified with the MSE technique in the complexity domain due to the nonconvergent behavior of one another
Summary
Neuromuscular diseases are disorders that affect nerve or muscle, neuromuscular junctions, and muscle tissue. Neuropathy and myopathy are two types of neuromuscular diseases. When motoneuron cells involved in muscular control or sensation (Brown et al, 2002; Basmajian and De Luca, 1985; Kandel et al, 2000) die, patients suffer from neuropathy. Patients suffer from myopathy when the muscle fibers die (Kocer, 2010). The electromyography test is used for the diagnosis of neuromuscular disorders, this technique is subjective (Subasi, 2013). Because the signals acquired in this type of test are analyzed using a visual and audible way by an adroit electrophysiologist (Kimura, 2013), this subjectivity test should be replaced with automatic classification techniques to help the diagnosis (Subasi, 2013)
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