This paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average...

Abstract—(1) Background: The aim of this study is to present the results of experiments in which surface electromyography (sEMG) and thermal imaging were used to assess muscle activation during gait and to verify the hypothesis that there is a relationship in the case of low fatigue level between sEMG measured muscle activation, assessed in the frequency domain, and thermal factors calculated as minimum, maximum, kurtosis, mean,...

Recently, there has been a noticeable increase in interest in solu tions utilizing electrical signals accompanying muscle activity. Electromyography (EMG) is a technique for recording, analysis and evaluating the electrical activity produced by striated muscle. Its great popularity is due, among other, to the ability to measure with non-invasive electrodes (calle d as sEMG surface electromyography)....

We proposed to apply a specific machine learning technique called Self-Organising Maps (SOM) to identify similarities in the performance of muscles around human temporomandibular joint (TMJ). The performance was assessed by measuring muscle activation with the use of surface electromyography (sEMG). SOM algorithm used in the study was able to find clusters of data in sEMG test results. The SOM analysis was based on processed sEMG...