Hybrid and fast: A novel in silico approach with reduced computational cost to predict failures of in vivo needle-based implantations

Pier Nicola Sergi*, Winnie Jensen, Ken Yoshida, Silvestro Micera

*Corresponding author

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

Original languageEnglish
Title of host publicationConverging Clinical and Engineering Research on Neurorehabilitation III : Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018)
Number of pages5
PublisherSpringer Publishing Company
Publication date1 Jan 2019
Pages127-131
ISBN (Print)978-3-030-01844-3
ISBN (Electronic)978-3-030-01845-0
DOIs
Publication statusPublished - 1 Jan 2019
Event4th International Conference on NeuroRehabilitation, ICNR2018 - Pisa, Italy
Duration: 16 Oct 2018 → 20 Oct 2018

Conference

Conference4th International Conference on NeuroRehabilitation, ICNR2018
CountryItaly
CityPisa
Period16/10/2018 → 20/10/2018
SeriesBiosystems and Biorobotics
Volume21
ISSN2195-3562

Fingerprint

Computer Simulation
Needles
Costs and Cost Analysis
Tungsten
Robotics
Peripheral Nerves
Punctures
Prostheses and Implants
Cicatrix
Hand
Equipment and Supplies
Wounds and Injuries
In Vitro Techniques

Cite this

Sergi, P. N., Jensen, W., Yoshida, K., & Micera, S. (2019). Hybrid and fast: A novel in silico approach with reduced computational cost to predict failures of in vivo needle-based implantations. In Converging Clinical and Engineering Research on Neurorehabilitation III: Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018) (pp. 127-131). Springer Publishing Company. Biosystems and Biorobotics, Vol.. 21 https://doi.org/10.1007/978-3-030-01845-0_25
Sergi, Pier Nicola ; Jensen, Winnie ; Yoshida, Ken ; Micera, Silvestro. / Hybrid and fast : A novel in silico approach with reduced computational cost to predict failures of in vivo needle-based implantations. Converging Clinical and Engineering Research on Neurorehabilitation III: Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018). Springer Publishing Company, 2019. pp. 127-131 (Biosystems and Biorobotics, Vol. 21).
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Sergi, PN, Jensen, W, Yoshida, K & Micera, S 2019, Hybrid and fast: A novel in silico approach with reduced computational cost to predict failures of in vivo needle-based implantations. in Converging Clinical and Engineering Research on Neurorehabilitation III: Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018). Springer Publishing Company, Biosystems and Biorobotics, vol. 21, pp. 127-131, Pisa, Italy, 16/10/2018. https://doi.org/10.1007/978-3-030-01845-0_25

Hybrid and fast : A novel in silico approach with reduced computational cost to predict failures of in vivo needle-based implantations. / Sergi, Pier Nicola; Jensen, Winnie; Yoshida, Ken; Micera, Silvestro.

Converging Clinical and Engineering Research on Neurorehabilitation III: Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018). Springer Publishing Company, 2019. p. 127-131 (Biosystems and Biorobotics, Vol. 21).

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

TY - GEN

T1 - Hybrid and fast

T2 - A novel in silico approach with reduced computational cost to predict failures of in vivo needle-based implantations

AU - Sergi, Pier Nicola

AU - Jensen, Winnie

AU - Yoshida, Ken

AU - Micera, Silvestro

PY - 2019/1/1

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M3 - Article in proceeding

SN - 978-3-030-01844-3

T3 - Biosystems and Biorobotics

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EP - 131

BT - Converging Clinical and Engineering Research on Neurorehabilitation III

PB - Springer Publishing Company

ER -

Sergi PN, Jensen W, Yoshida K, Micera S. Hybrid and fast: A novel in silico approach with reduced computational cost to predict failures of in vivo needle-based implantations. In Converging Clinical and Engineering Research on Neurorehabilitation III: Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018). Springer Publishing Company. 2019. p. 127-131. (Biosystems and Biorobotics, Vol. 21). https://doi.org/10.1007/978-3-030-01845-0_25

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