Comparação entre famílias de Wavelets na avaliação de fadiga muscular usando sinais de eletromiografia
Methods of processing signals have several applications in the most different areas such as prevention of electric motors failures, medicine, monitoring of bioelectric activities in the brain and others. Electromyography signs (EMG) are coming from a non-invasive collection of biological signals. Th...
| Autor principal: | Oliveira, Luís Paulo Nallin de |
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| Formato: | Trabalho de Conclusão de Curso (Graduação) |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2022
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| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/27262 |
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| Resumo: |
Methods of processing signals have several applications in the most different areas such as prevention of electric motors failures, medicine, monitoring of bioelectric activities in the brain and others. Electromyography signs (EMG) are coming from a non-invasive collection of biological signals. This paper is focused in EMG signals analysis in dynamic exercises, based on a non-invasive method to collect the EMG signals, to contribute to the efficiency of training athletes. EMG analysis of signals will be done based on the tool called Wavelet Transform. This study aims to improve the analysis of EMG signals from the Wavelet Transform, this tool is composed by many base functions (mother wavelets). To conclude, the purpose of this sutdy will be achieved by the definition of the best mother wavelet (function basis of this transform) to EMG signals from dynamic exercises. |
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