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Previous issue date: 2016-04-26 / This study proposes a new methodology for automatic detection of muscle activation in electromyographic (EMG) signals. Which uses the local variance of EMG signal to determine the onset and offset times of muscle activation events. Were implemented two existing and consolidated methods (Teager-Kaiser Energy Operator and Sample Entropy) in order to carry the activation detection by another way and enable a comparative analysis of different methodologies. The evaluation of results was separated into two stages: performance analysis and convergence analysis. The performance analysis was established by quantifiable and objective parameters: accuracy, tolerance to noise and computational cost. It was developed also a generator of synthetic EMG signals whose muscle activation times and signal to noise ratio (SNR) were previously known. Considering the parameters established and the data analyzed, the proposed methodology demonstrated a better precision and tolerance to noise when compared to the others methods. The convergence analysis used the real EMG data from ten subjects, of which was collected signals from eight different muscles. Through this set of data, it was possible to demonstrate the high correlation between the results from the analyzed methods. / Este trabalho prop?e uma nova metodologia para detec??o autom?tica da ativa??o muscular em sinais de Eletromiografia (EMG). A qual utiliza a vari?ncia local do sinal para determinar os instantes de tempo que correspondem a eventos de ativa??o muscular. Duas t?cnicas existentes e consolidadas na literatura (Operador de Energia de Teager-Kaiser e Sample Entropy) foram implementadas com objetivo de realizar a detec??o da ativa??o e viabilizar uma an?lise comparativa entre as diferentes metodologias. A avalia??o dos resultados foram separadas em duas etapas: analise de performance e an?lise de converg?ncia. Para realiza??o da an?lise de performance foram estabelecidos crit?rios quantific?veis e objetivos: precis?o, toler?ncia a ru?dos e custo computacional. Foi desenvolvido tamb?m, um gerador de sinais de EMG sint?ticos, cujos tempos de ativa??o muscular e a rela??o sinal ru?do (SNR) eram previamente conhecidos. Considerando os crit?rios estabelecidos e o conjunto de dados analisados, a metodologia proposta demonstrou-se superior nos quesitos performance e toler?ncia a ru?dos. A an?lise de converg?ncia utilizou dados reais provenientes dez sujeitos, dos quais foram coletados sinais de oito m?sculos. Atrav?s desse
conjunto de dados foi poss?vel demonstrar a forte correla??o entre os resultados obtidos pelos m?todos analisados.
| Identifer | oai:union.ndltd.org:IBICT/oai:tede2.pucrs.br:tede/6901 |
| Date | 26 April 2016 |
| Creators | Moraes, Rodrigo Belagamba de |
| Contributors | Salton, Aur?lio Tergolina, Baptista, Rafael Reimann |
| Publisher | Pontif?cia Universidade Cat?lica do Rio Grande do Sul, Programa de P?s-Gradua??o em Engenharia El?trica, PUCRS, Brasil, Faculdade de Engenharia |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Format | application/pdf |
| Source | reponame:Biblioteca Digital de Teses e Dissertações da PUC_RS, instname:Pontifícia Universidade Católica do Rio Grande do Sul, instacron:PUC_RS |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 207662918905964549, 600, 600, 600, -655770572761439785, 4518971056484826825 |
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