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

Willian da Silva; Eric Fujiwara; Matheus Gomes

doi:10.20396/revpibic2720191807

No. 27 (2019), Resumos

No. 27 (2019)

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

Resumos

Published 2019-11-30

Willian da Silva⁺⁻
Eric Fujiwara⁺⁻
Matheus Gomes⁺⁻

Willian da Silva

Universidade Estadual de Campinas

Eric Fujiwara

Universidade Estadual de Campinas

https://orcid.org/0000-0001-8169-9738

Matheus Gomes

Universidade Estadual de Campinas

PDF (Portuguese)

Keywords

Force myography
Optical fiber sensor
Artificial neural networks

How to Cite

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.sbu.unicamp.br/eventos/index.php/pibic/article/view/1807. Acesso em: 6 oct. 2026.

Abstract

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.

PDF (Portuguese)

References

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.

This work is licensed under a Creative Commons Attribution 4.0 International License.

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

Keywords

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