  The electromyogram (EMG) in needle detection represents one of the steps of
the electroneuromyogram (ENMG), an examination commonly performed in neurology.
By inserting a needle into a muscle and studying the contraction during effort,
the EMG provides extremely useful information on the functioning of the
neuromuscular system of an individual, but it is an examination that remains
complex to interpret. The objective of this work is to participate in the
design and evaluation of a software allowing an automated analysis of EMG
tracings of patients suspected of neuromuscular diseases, orienting the
diagnosis towards either a neuropathic or myopathic process from recorded
tracings. The software uses a method of signal decomposition according to a
Markovian model, based on the analysis of motor unit potentials obtained by
EMG, then a classification of the tracings. The tracings of 9 patients were
thus analyzed and classified on the basis of the clinical interpretation of the
neurologist, making it possible to initiate a "machine learning" process. The
software will then be submitted to new tracings in order to test it against a
practitioner experienced in EMG analysis.Translated with
www.DeepL.com/Translator (free version)
