The DOI matches its Crossref record; 168 of the 168 references it cites were found in a registry or an index.
Restoration of sensory information via bionic hands
Open accessAbstract
This Review discusses non-invasive and invasive technologies for conveying artificial sensory feedback through bionic hands. Individuals who have lost the use of their hands because of amputation or spinal cord injury can use prosthetic hands to restore their independence. A dexterous prosthesis requires the acquisition of control signals that drive the movements of the robotic hand, and the transmission of sensory signals to convey information to the user about the consequences of these movements. In this Review, we describe non-invasive and invasive technologies for conveying artificial sensory feedback through bionic hands, and evaluate the technologies’ long-term prospects.
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Cites
The co-ordination and regulation of movements
(1969) · Brain Research · doi:10.1016/0006-8993(69)90278-9 · Cited by 5,043
Rubber hands ‘feel’ touch that eyes see
Botvinick, M., & Cohen, J. (1998) · Nature · doi:10.1038/35784 · Cited by 4,410
PENFIELD, W., & BOLDREY, E. (1937) · Brain · doi:10.1093/brain/60.4.389 · Cited by 4,188
Proske, U., & Gandevia, S. C. (2012) · Physiological Reviews · doi:10.1152/physrev.00048.2011 · Cited by 2,223
Fully integrated silicon probes for high-density recording of neural activity
Jun, J. J., Steinmetz, N. A., Siegle, J. H., Denman, D. J., Bauza, M., Barbarits, B., Lee, A. K., Anastassiou, C. A., Andrei, A., Aydın, Ç., et al. (2017) · Nature · doi:10.1038/nature24636 · Cited by 2,190
Coding and use of tactile signals from the fingertips in object manipulation tasks
Johansson, R. S., & Flanagan, J. R. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2621 · Cited by 2,063
A bioinspired flexible organic artificial afferent nerve
Kim, Y., Chortos, A., Xu, W., Liu, Y., Oh, J. Y., Son, D., Kang, J., Foudeh, A. M., Zhu, C., Lee, Y., et al. (2018) · Science · doi:10.1126/science.aao0098 · Cited by 1,466
Biomedical applications of soft robotics
Cianchetti, M., Laschi, C., Menciassi, A., & Dario, P. (2018) · Nature Reviews Materials · doi:10.1038/s41578-018-0022-y · Cited by 1,435
Johansson, R. S., & Vallbo, A. B. (1979) · The Journal of Physiology · doi:10.1113/jphysiol.1979.sp012619 · Cited by 1,291
Wyndaele, M., & Wyndaele, J.-J. (2006) · Spinal Cord · doi:10.1038/sj.sc.3101893 · Cited by 1,116
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Toward higher-performance bionic limbs for wider clinical use
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Self-citationToward an AI Era: Advances in Electronic Skins
Fu, X., Cheng, W., Wan, G., Yang, Z., & Tee, B. C. K. (2024) · Chemical Reviews · doi:10.1021/acs.chemrev.4c00049 · Cited by 172
Human brain mapping with multithousand-channel PtNRGrids resolves spatiotemporal dynamics
Tchoe, Y., Bourhis, A. M., Cleary, D. R., Stedelin, B., Lee, J., Tonsfeldt, K. J., Brown, E. C., Siler, D. A., Paulk, A. C., Yang, J. C., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abj1441 · Cited by 135
An actor-model framework for visual sensory encoding
Leong, F., Rahmani, B., Psaltis, D., Moser, C., & Ghezzi, D. (2024) · Nature Communications · doi:10.1038/s41467-024-45105-5 · Cited by 8
Metadata
- Authors
- Bensmaia, S. J., Tyler, D. J., & Micera, S.
- Venue
- Nature Biomedical Engineering
- Published
- 2020-11-23
- Volume
- 7
- Issue
- 4
- Pages
- 443-455
- ISSN
- 2157-846X (ISSN-L)
- OpenAlex
- W3108506906
- Cited by
- 257
- References
- 168
- FWCI
- 8.48
- Type
- journal article
- Language
- en
- Open access
- green
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