Early diagnosis of carpal tunnel syndrome using electromyogram signals
The present investigation proposes to use electromyographic signals for the diagnosis of carpal tunnel with the aim of helping to reduce the number of false positives and negatives that are obtained with the criteria currently used. For this, the EMG signals were analyzed using the Bitalino kit of a patient with carpal tunnel and a control patient. The signals were filtered and analyzed using the Python language. From this it was obtained that the signals presented slight differences in the electrical activity of both patients, a decrease in the interference pattern was observed, which indicates a reduction in the electrical activity recorded in the muscle during contraction and it is concluded that the carpal tunnel patient has a progressive decrease in nerve conduction velocity compared to a control patient.
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