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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2020
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2020
Data sources: ZENODO
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2020
Data sources: Datacite
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EMG database - EMG Pattern Recognition For Prosthesis Control

Authors: Andrade, Adriano De Oliveira;

EMG database - EMG Pattern Recognition For Prosthesis Control

Abstract

This database is one of the results of the MSc dissertation of Adriano de Oliveira Andrade (http://orcid.org/0000-0002-5689-6606) The experimental protocol is fully described in the MSc dissertation (Chapter 5 - pp. 56-60). The avaliable program in R (Import_EMG_Files.R) can be used to import and visualize the EMG data available (EMG-DATA-MSc-AOA.zip). The EMG data are in in the folders "Isometricos" and "Isotonicos". MSc dissertation avaiable @ [1] Andrade A de O. Metodologia para classificação de sinais EMG no controle de membros artificiais. [manuscrito]. 2000. Uberlândia: Universidade Federal de Uberlândia. doi: https://doi.org/10.13140/RG.2.2.17314.02242. [2] http://search.ebscohost.com/login.aspx?direct=true&db=cat08055a&AN=sapere.000058379&lang=pt-br&site=eds-live Abstract - EMG Pattern Recognition For Prosthesis Control One of the major challenges for prosthesis development is to produce devices which mimic their natural counterparts. In general, articial limbs don't have proper feedback by which the user can assess the status of the prosthesis and the control is very unnatural. Preferably, a subconscious control is desired. Myoelectric control has been widely used as an alternative strategy designed for easier control. However, there is still a lot do be done in order to achieve articial limbs as dextrous as human limbs. In an attempt to contribute to the researches towards better artical limbs, it has been developed an EMG processing system, capable of generate input control to a four degrees of freedom prosthesis. Two major muscle groups (biceps and triceps) were used as source of electromyograc signals, which were discriminated into four different classes: elbow exion, elbow extension, wrist pronation and wrist supination. Those patterns were classied by an articial neural network, which received as inputs the EMG signal features extracted by an autoregressive model. The minimum number of pairs of electrodes and their best positioning for detection, processing and classication were also investigated. To do so, five pairs of electrodes (two on the biceps - long head (B1) and short head (B2) - and three on the triceps - long head (T1), medium head (T2) and lateral head(T3) and one pair of electrodes (on plexo brachial) configuration were considered. Isometric and isotonic contractions were analyzed for each one of those two configurations. The EMG signals were studied in several combinations for each type of contraction. The results show that the configurations using two pairs of electrodes (positioned on B2 and T1) and three pairs of electrodes (positioned on B2, T1 and T2 or B2, T1 and T3), provided accuracy as good as 100%, for the EMG pattern recognition process. Resumo em Português - Metodologia para Classicação de Sinais EMG no Controle de Membros Artificiais Um dos grandes desafios atuais das pesquisas envolvendo o aperfeiçoamento de membros artificiais, é que esses possam ser controlados de maneira mais natural possível pelos pacientes. Neste sentido, os processos envolvendo a aquisição e a manipulação das informações de controle provenientes do paciente, têm merecido especial atenção. Dentre as diversas técnicas de controle possíveis, uma das que tem alcançado melhores resultados utiliza a atividade eletromiográfica resultante de contrações voluntárias de determinados grupos musculares. Numa tentativa de contribuir para aquelas pesquisas, foi desenvolvido um sistema de processamento de sinais eletromiográficos (EMG), capaz de fornecer entradas de controle para uma prótese com quatro graus de liberdade. Para tal, sinais EMG provenientes dos grupos musculares tríceps e bíceps foram classificados em quatro padrões distintos: flexão e extensão do cotovelo, pronação e supinação do punho. A classificação dos padrões foi feita através de uma rede neural artifical que recebe como entrada as características dos sinais eletromiográficos, extraídas através de um modelo autoregressivo. Outro objetivo desta pesquisa foi buscar o número mínimo de pares de eletrodos e os sítios mais adequados para a detecção, processamento e classificação satisfatória dos movimentos executados. Foram feitas análises considerando 5 pares de eletrodos, sendo dois sobre o bíceps - na cabeça longa (B1) e na cabeça curta (B2) - e três sobre o tríceps - na cabeça longa (T1), na cabeça medial (T2) e na cabeça lateral (T3); e um par de eletrodos sobre o plexo braquial. Os experimentos foram realizados considerando-se contrações isométricas e isotônicas. Aqueles sinais foram analisados em diversas combinações, para cada tipo de contração, numa tentativa de se encontrar aquela que apresentasse melhores resultados. Os resultados mostraram que as combinações envolvendo o uso de dois pares de eletrodos posicionados sobre os sítios B2 e T1; e três pares de eletrodos posicionados sobre os sítios B2, T1 e T2 ou B2, T1 e T3 apresentaram melhores performances, com taxas de acerto de até 100%.

{"references": ["https://doi.org/10.13140/RG.2.2.17314.02242"]}

Related Organizations
Keywords

autoregressive model, prosthesis, Eletromiography, neural networks

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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