Identification of hand postures by force myography using an optical fiber specklegram sensor

Eric Fujiwara; Yu Tzu Wu; Murilo F. M. Santos; Egont A. Schenkel; Carlos K. Suzuki

doi:10.1117/12.2194605

28 September 2015 Identification of hand postures by force myography using an optical fiber specklegram sensor

Eric Fujiwara, Yu Tzu Wu, Murilo F. M. Santos, Egont A. Schenkel, Carlos K. Suzuki

Proceedings Volume 9634, 24th International Conference on Optical Fibre Sensors; 96343Z (2015) https://doi.org/10.1117/12.2194605
Event: International Conference on Optical Fibre Sensors (OFS24), 2015, Curitiba, Brazil

Abstract

The identification of hand postures based on force myography (FMG) measurements using a fiber specklegram sensor is reported. The microbending transducers were attached to the user forearm in order to detect the radial forces due to hand movements, and the normalized intensity inner products of output specklegrams were computed with reference to calibration positions. The correlation between measured specklegrams and postures was carried out by artificial neural networks, resulting in an overall accuracy of 91.3% on the retrieval of hand configuration.

Citation Download Citation

Eric Fujiwara, Yu Tzu Wu, Murilo F. M. Santos, Egont A. Schenkel, and Carlos K. Suzuki "Identification of hand postures by force myography using an optical fiber specklegram sensor", Proc. SPIE 9634, 24th International Conference on Optical Fibre Sensors, 96343Z (28 September 2015); https://doi.org/10.1117/12.2194605

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