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Cited by 332

The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.

Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans

Open access
Oddo, Calogero Maria, Raspopovic, Stanisa, Artoni, Fiorenzo, Mazzoni, Alberto, Spigler, Giacomo, Petrini, Francesco, Giambattistelli, Federica, Vecchio, Fabrizio, Miraglia, Francesca, Zollo, Loredana, Di Pino, Giovanni, Camboni, Domenico, Carrozza, Maria Chiara, Guglielmelli, Eugenio, Rossini, Paolo Maria, Faraguna, Ugo, Micera, Silvestro·2016·eLife

Abstract

Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in the next generation of neuro-prosthetic hands.

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Crossref · 10.7554/elife.09148

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Research works printed but not linked: 3

  1. Oddo, 2011, Roughness encoding for discrimination of surfaces in artificial active-touch, IEEE Transactions on Robotics, 27, 522, 10.1109/TRO.2011.2116930 · DOI
  2. Perez, 2010, A critical experimental study of the classical tactile threshold theory, BMC Neuroscience, 11, 76, 10.1186/1471-2202-11-76 · doi:10.1186/1471-2202-11-76
  3. Spigler G, Oddo CM, Carrozza MC. 2012. 4th IEEE RAS & EMBS international conference on biomedical robotics and biomechatronics (BioRob).

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Metadata

Authors
Oddo, C. M., Raspopovic, S., Artoni, F., Mazzoni, A., Spigler, G., Petrini, F., Giambattistelli, F., Vecchio, F., Miraglia, F., Zollo, L., Di Pino, G., Camboni, D., Carrozza, M. C., Guglielmelli, E., Rossini, P. M., Faraguna, U., & Micera, S.
Venue
eLife
Published
2016-03-08
Volume
5
Pages
e09148-e09148
ISSN
2050-084X (ISSN-L)
OpenAlex
W2296426322
Cited by
332
References
71
FWCI
24.68
Type
journal article
Language
en
Open access
gold
Funders
  • Directorate-General for Communications Networks, Content and Technology (EU Grant CP-FP-INFSO 224012 TIME project, EU Grant FET 611687 NEBIAS Project, EU Grant FP7-NMP 228844 NANOBIOTOUCH project)
  • Ministero della Salute (Italian NEMESIS (Neurocontrolled mechatronic hand prosthesis))
  • Ministero dell’Istruzione, dell’Università e della Ricerca (Italian project PRIN/HandBot)
  • Italian National Institute for Insturance against Industrial Injuries (National project PPR2 (Control of hand prosthesis by invasive neural interfaces))
  • Swiss National Competence Center in Research in Robotics (NCCR Robotics)
  • Wyss Center for Bio and Neuroengineering (ENABLE Project)

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CoChat. (2026). Citation check: Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans. https://app.cochat.ai/papers/10.7554/elife.09148
The paper
Oddo, C. M., Raspopovic, S., Artoni, F., Mazzoni, A., Spigler, G., Petrini, F., Giambattistelli, F., Vecchio, F., Miraglia, F., Zollo, L., Di Pino, G., Camboni, D., Carrozza, M. C., Guglielmelli, E., Rossini, P. M., Faraguna, U., & Micera, S. (2016). Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans. eLife. https://doi.org/10.7554/elife.09148

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.