Development of algorithms for hand movements classification based on optical fiber force myography signals
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Palavras-chave

Force myography
Optical fiber sensor
Artificial neural networks

Como Citar

SILVA, Willian da; FUJIWARA, Eric; GOMES, Matheus. Development of algorithms for hand movements classification based on optical fiber force myography signals. Revista dos Trabalhos de Iniciação Científica da UNICAMP, Campinas, SP, n. 27, p. 1–1, 2019. DOI: 10.20396/revpibic2720191807. Disponível em: https://econtents.bc.unicamp.br/eventos/index.php/pibic/article/view/1807. Acesso em: 26 abr. 2024.

Resumo

Force myography (FMG) is the mechanical counterpart of the surface electromyography, providing a low-cost and straightforward alternative for tracking the hand movements in applications related to rehabilitation and robotics. This project proposes the development of a modularized and scalable algorithm for classification of hand postures based on the FMG signals measured by an optical fiber sensor, with artificial neural networks design and implementation in embeeded system.

https://doi.org/10.20396/revpibic2720191807
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Referências

Taşar, B. et. al.; EMG-Controlled Prosthetic Hand with Fuzzy Logic Classification Algorithm, Modern Fuzzy Control Systems and Its Applications, IntechOpen, 2017.

Fujiwara, E.; Suzuki, C. K.; Journal of Sensors, 2018.

Rodriguez, J. D.; Perez, A.; Lozano, J. A.; IEEE Trans. Pattern Anal. Machine Intell., vol. 32, no. 3, pp. 569-575, 2010.

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