Analysis of normal and abnormal electromyograms using fractional calculus andcomputational intelligence

Abstract

Electromyography is a diagnostic technique of recording the electrical signals generated by the neuromuscular system. Such electrical signals produced from the muscular and nervous systems are referred as Electromyograms (EMG). The examination of electromyograms is a challenging task, which requires experts to investigate and diagnose neuromuscular disorders. Hence, the development of efficient and automated procedures is required for the analysis of electromyograms, for mass screening of disorders in the neuromuscular system. newlineIn this work, the experimental measurements of dielectric relative permittivity as well as conductivity at two frequencies (120 Hz and 1 KHz) were utilized for the development of a mathematical modelling of the variations in the frequency dependent dielectric properties of the biceps brachial region in vivo and in contact with surface electrodes as well as electromyogram measurement systems. The dielectric properties were measured in clinical environments from healthy individuals and the ethical clearance was obtained from Gleneagles Global Health city, Chennai (HR/2019/MS/0011). The parameters of the Debye equation was estimated using the least squares optimization procedure.The information content and the degree of chaos in the electromyograms recorded using Concentric Needle Electrodes (CEN) Monopolar Needle Electrodes (MNE) and Surface Electrodes (SE), were examined using entropy metrics (Tsallis entropy and Rényi entropy) and Lyapunov Exponents (LE). Further, the normal, Amyotrophic Lateral Sclerosis (ALS) and myopathy EMG signals (N=150) recorded from biceps brachial muscles, using concentric needle electrodes, were considered for the development of EMG classification systems. newline newline