Online simultaneous myoelectric finger control

Sigrid S.G. Dupan; Ivan Vujaklija; Martyna K. Stachaczyk; Janne M. Hahne; Dick F. Stegeman; Strahinja S. Dosen; Dario Farina

doi:10.1007/978-3-030-01845-0_14

Online simultaneous myoelectric finger control

Sigrid S.G. Dupan^*, Ivan Vujaklija, Martyna K. Stachaczyk, Janne M. Hahne, Dick F. Stegeman, Strahinja S. Dosen, Dario Farina

^*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

Abstract

State-of-the-art prosthetic hands allow separate control of all digits. Restoring natural hand use with these systems requires simultaneous and proportional control of all fingers. Regression algorithms might be able to predict any combination of degrees of freedom after training them separately. However, to the best of our knowledge, this has yet to be shown online. Twelve able-bodied participants were instructed to reach predefined target forces representing either single or combined finger presses, following a system training session consisting of only individual finger presses. Myoelectric control was implemented using linear ridge regression. The results demonstrated that myoelectric control allowed participants to reach both single finger, and combination targets, with hit rates of 88% and 54% respectively. These findings suggest that simultaneous control of multiple fingers is possible, even when these movements are not included in the training set.

Original language	English
Title of host publication	Proceedings of the 4th International Conference on NeuroRehabilitation : ICNR2018
Editors	Lorenzo Masia, Silvestro Micera, Metin Akay, José L. Pons
Number of pages	5
Publisher	Springer Publishing Company
Publication date	1 Jan 2019
Pages	72-76
ISBN (Print)	978-3-030-01844-3
ISBN (Electronic)	978-3-030-01845-0
DOIs	https://doi.org/10.1007/978-3-030-01845-0_14
Publication status	Published - 1 Jan 2019
Event	International Conference on Neurorehabilitation - Pisa, Italy Duration: 16 Oct 2018 → 20 Oct 2018 http://www.icnr2018.org

Conference

Conference	International Conference on Neurorehabilitation
Country/Territory	Italy
City	Pisa
Period	16/10/2018 → 20/10/2018
Internet address	http://www.icnr2018.org

Series	Biosystems and Biorobotics
Volume	21
ISSN	2195-3562

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10.1007/978-3-030-01845-0_14

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Dupan, S. S. G., Vujaklija, I., Stachaczyk, M. K., Hahne, J. M., Stegeman, D. F., Dosen, S. S., & Farina, D. (2019). Online simultaneous myoelectric finger control. In L. Masia, S. Micera, M. Akay, & J. L. Pons (Eds.), Proceedings of the 4th International Conference on NeuroRehabilitation : ICNR2018 (pp. 72-76). Springer Publishing Company. https://doi.org/10.1007/978-3-030-01845-0_14

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title = "Online simultaneous myoelectric finger control",

abstract = "State-of-the-art prosthetic hands allow separate control of all digits. Restoring natural hand use with these systems requires simultaneous and proportional control of all fingers. Regression algorithms might be able to predict any combination of degrees of freedom after training them separately. However, to the best of our knowledge, this has yet to be shown online. Twelve able-bodied participants were instructed to reach predefined target forces representing either single or combined finger presses, following a system training session consisting of only individual finger presses. Myoelectric control was implemented using linear ridge regression. The results demonstrated that myoelectric control allowed participants to reach both single finger, and combination targets, with hit rates of 88% and 54% respectively. These findings suggest that simultaneous control of multiple fingers is possible, even when these movements are not included in the training set.",

author = "Dupan, {Sigrid S.G.} and Ivan Vujaklija and Stachaczyk, {Martyna K.} and Hahne, {Janne M.} and Stegeman, {Dick F.} and Dosen, {Strahinja S.} and Dario Farina",

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doi = "10.1007/978-3-030-01845-0_14",

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booktitle = "Proceedings of the 4th International Conference on NeuroRehabilitation",

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note = "International Conference on Neurorehabilitation, ICNR ; Conference date: 16-10-2018 Through 20-10-2018",

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Dupan, SSG, Vujaklija, I, Stachaczyk, MK, Hahne, JM, Stegeman, DF, Dosen, SS & Farina, D 2019, Online simultaneous myoelectric finger control. in L Masia, S Micera, M Akay & JL Pons (eds), Proceedings of the 4th International Conference on NeuroRehabilitation : ICNR2018. Springer Publishing Company, Biosystems and Biorobotics, vol. 21, pp. 72-76, International Conference on Neurorehabilitation, Pisa, Italy, 16/10/2018. https://doi.org/10.1007/978-3-030-01845-0_14

Online simultaneous myoelectric finger control. / Dupan, Sigrid S.G.; Vujaklija, Ivan; Stachaczyk, Martyna K. et al.
Proceedings of the 4th International Conference on NeuroRehabilitation : ICNR2018. ed. / Lorenzo Masia; Silvestro Micera; Metin Akay; José L. Pons. Springer Publishing Company, 2019. p. 72-76 (Biosystems and Biorobotics, Vol. 21).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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AU - Dupan, Sigrid S.G.

AU - Vujaklija, Ivan

AU - Stachaczyk, Martyna K.

AU - Hahne, Janne M.

AU - Stegeman, Dick F.

AU - Dosen, Strahinja S.

AU - Farina, Dario

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Y1 - 2019/1/1

N2 - State-of-the-art prosthetic hands allow separate control of all digits. Restoring natural hand use with these systems requires simultaneous and proportional control of all fingers. Regression algorithms might be able to predict any combination of degrees of freedom after training them separately. However, to the best of our knowledge, this has yet to be shown online. Twelve able-bodied participants were instructed to reach predefined target forces representing either single or combined finger presses, following a system training session consisting of only individual finger presses. Myoelectric control was implemented using linear ridge regression. The results demonstrated that myoelectric control allowed participants to reach both single finger, and combination targets, with hit rates of 88% and 54% respectively. These findings suggest that simultaneous control of multiple fingers is possible, even when these movements are not included in the training set.

AB - State-of-the-art prosthetic hands allow separate control of all digits. Restoring natural hand use with these systems requires simultaneous and proportional control of all fingers. Regression algorithms might be able to predict any combination of degrees of freedom after training them separately. However, to the best of our knowledge, this has yet to be shown online. Twelve able-bodied participants were instructed to reach predefined target forces representing either single or combined finger presses, following a system training session consisting of only individual finger presses. Myoelectric control was implemented using linear ridge regression. The results demonstrated that myoelectric control allowed participants to reach both single finger, and combination targets, with hit rates of 88% and 54% respectively. These findings suggest that simultaneous control of multiple fingers is possible, even when these movements are not included in the training set.

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Dupan SSG, Vujaklija I, Stachaczyk MK, Hahne JM, Stegeman DF, Dosen SS et al. Online simultaneous myoelectric finger control. In Masia L, Micera S, Akay M, Pons JL, editors, Proceedings of the 4th International Conference on NeuroRehabilitation : ICNR2018. Springer Publishing Company. 2019. p. 72-76. (Biosystems and Biorobotics, Vol. 21). doi: 10.1007/978-3-030-01845-0_14

Online simultaneous myoelectric finger control

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