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Wyniki wyszukiwania dla: surface electromyography
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Basic Hand Gestures Classification Based on Surface Electromyography
PublikacjaThis 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...
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Could thermal imaging supplement surface electromyography measurements for skeletal muscles?
PublikacjaAbstract—(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,...
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SIMPLY AND LOW COAST ELECTROMYOGRAPHY SIGNAL AMPLIFIER
PublikacjaRecently, 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)....
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Basic evaluation of limb exercises based on electromyography and classification methods
PublikacjaSymptoms caused by cerebral palsy or stroke deprive a person partially or even completely of his ability to move. Nowadays we can observe more technologically advanced rehabilitation devices which incorporate biofeedback into the process of rehabilitation of such people. However, there is still a lack of devices that would analyse, assess, and control (independently or with limited support) specialised movement exercises. Here...
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Leveraging Training Strategies of Artificial Neural Network for Classification of Multiday Electromyography Signals
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Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
PublikacjaThe temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs)...
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Jaw biomechanics: Estimation of activity of muscles acting at the temporomandibular joint
PublikacjaThe aim of this study was to elaborate a method of estimation of activity of surface muscles acting at the temporomandibular joint of the healthy subjects by using a surface electromyography (EMG). The scope of this study involved testing chosen jaw motions (open, close, lateral deviation) and process of mastication occurring during eating food with different toughness (chewing gum, cereal and carrot) by using mixed sides, right...
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Komputerowo wspomagana klasyfikacja wybranych sygnałów elektromiografii powierzchniowej
PublikacjaWykorzystywanie sygnałów elektromiografii powierzchniowej (ang. Surface Electromyography, SEMG) w procesach sterowania systemami rehabilitacyjnymi stanowi obecnie standardową procedurę. Popularność SEMG wynika z nieinwazyjności metody oraz możliwości szybkiej i precyzyjnej identyfikacji funkcji mięśniowej. W przypadku osób małoletnich proces klasyfikacji sygnałów jest utrudniony ze względu na mniejsze rozmiary i wyższą dynamikę...
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Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps
PublikacjaThe study considers the need for an effective method of classification of patients with a temporomandibular joint disorder (TMD). The self-organising map method (SOM) was applied to group patients and used together with the cross-correlation approach to interpret the processed (rectified and smoothed by using root mean square (RMS) algorithm) surface electromyography signal (sEMG) obtained from testing the muscles (two temporal...
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Unsupervised Learning for Biomechanical Data Using Self-organising Maps, an Approach for Temporomandibular Joint Analysis
PublikacjaWe 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...