The neuromuscular disorders are diagnosed using electromyographic (EMG) signals.
Machine learning algorithms are employed as a decision support system to diagnose …

Electromyographic (EMG) signals are utilized to analyze the neuromuscular disorders.
Machine learning algorithms have been employed as a decision support system to detect …

Amyotrophic lateral sclerosis (ALS) is a disease, affects the nerve cells in brain and spinal
cord that controls the voluntary action of muscles, which identification can be possible by …

Automated diagnosis of neuromuscular disorders such as myopathy and neuropathy can be
done by measuring and analyzing the nonlinear and non-stationary trends in …

Biomedical signals are collected from a body that can be at the organ level, cell level, or
molecular level. There are different biomedical signals including the electroencephalogram …

This article presents an automatic diagnostic system to classify intramuscular
electromyography (iEMG) signals, thereby detecting neuromuscular disorders. To this end …

Machine learning methods can be used to diagnose neuromuscular illnesses using
electromyographic (EMG) signals. This research examines the tunable-Q factor wavelet …

Surface Electromyography (SEMG) signal measurement technique in which an electrode
connects to the surface of human muscle skin was produced from the mechanics of human …

This work reviews the recent techniques used to analyze the EMG signals to extract and
classify features. The discussed techniques are used in medical applications for the …

This study is devoted to the classification of neuromuscular diseases (NMDs) including ALS
and myopathy by using Electromyography (EMG) signals and a machine learning approach …