The DOI matches its Crossref record; 117 of the 121 references it cites were found in a registry or an index.
Sensors and Decoding for Intracortical Brain Computer Interfaces
Open accessAbstract
Intracortical brain computer interfaces (iBCIs) are being developed to enable people to drive an output device, such as a computer cursor, directly from their neural activity. One goal of the technology is to help people with severe paralysis or limb loss. Key elements of an iBCI are the implanted sensor that records the neural signals and the software that decodes the user's intended movement from those signals. Here, we focus on recent advances in these two areas, placing special attention on contributions that are or may soon be adopted by the iBCI research community. We discuss how these innovations increase the technology's capability, accuracy, and longevity, all important steps that are expanding the range of possible future clinical applications.
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Cites
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
Discrete-Time Signal Processing
Oppenheim, A. V., & Schafer, R. W. (1989) · Cited by 11,808
The origin of extracellular fields and currents — EEG, ECoG, LFP and spikes
Buzsáki, G., Anastassiou, C. A., & Koch, C. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3241 · Cited by 4,225
Neuronal ensemble control of prosthetic devices by a human with tetraplegia
Hochberg, L. R., Serruya, M. D., Friehs, G. M., Mukand, J. A., Saleh, M., Caplan, A. H., Branner, A., Chen, D., Penn, R. D., & Donoghue, J. P. (2006) · Nature · doi:10.1038/nature04970 · Cited by 3,295
Self-citationNeuronal Population Coding of Movement Direction
Georgopoulos, A. P., Schwartz, A. B., & Kettner, R. E. (1986) · Science · doi:10.1126/science.3749885 · Cited by 3,219
Estimating the Prevalence of Limb Loss in the United States: 2005 to 2050
Ziegler‐Graham, K., MacKenzie, E. J., Ephraim, P. L., Travison, T. G., & Brookmeyer, R. (2008) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/j.apmr.2007.11.005 · Cited by 2,951
Reach and grasp by people with tetraplegia using a neurally controlled robotic arm
Hochberg, L. R., Bacher, D., Jarosiewicz, B., Masse, N. Y., Simeral, J. D., Vogel, J., Haddadin, S., Liu, J., Cash, S. S., van der Smagt, P., et al. (2012) · Nature · doi:10.1038/nature11076 · Cited by 2,719
Self-citationTargeting Recovery: Priorities of the Spinal Cord-Injured Population
Anderson, K. D. (2004) · Journal of Neurotrauma · doi:10.1089/neu.2004.21.1371 · Cited by 2,094
High-performance neuroprosthetic control by an individual with tetraplegia
Collinger, J. L., Wodlinger, B., Downey, J. E., Wang, W., Tyler-Kabara, E. C., Weber, D. J., McMorland, A. J., Velliste, M., Boninger, M. L., & Schwartz, A. B. (2013) · The Lancet · doi:10.1016/s0140-6736(12)61816-9 · Cited by 1,848
Localization of the motor hand area to a knob on the precentral gyrus. A new landmark
Yousry, T. A. (1997) · Brain · doi:10.1093/brain/120.1.141 · Cited by 1,840
Research works printed but not linked: 14
- Christopher & Dana Reeve (CDR) Found, 2009, One Degree of Separation: Paralysis and Spinal Cord Injury in the United States.
- Burrow M, 1997, Proc. Int. Conf. Rehabil. Robot. (ICORR), 83
- Humphrey DR, 1997, Cortical control of neural prosthetic devices.
- Kim SP, 2006, IEEE/RAS-EMBS Int. Conf. Biomed. Robot. Biomechatron., 811
- Shpigelman L, 2009, Adv. Neural Inf. Proc. Syst., 21, 1489
- Malik WQ, 2010, Neurosci. Meet. Plan.
- Feldman JM, 2011, Neurosci. Meet Plan.
- Chao ZC, 2010, Front. Neuroeng., 3, 3
- Fisher J, 2005, Conf. Proc. IEEE Eng. Med. Biol. Soc., 2, 2130
- Gao Y, 2002, Adv. Neural Inf. Proc. Syst., 1, 213
- Wood F, 2005, Conf. Proc. IEEE Eng. Med. Biol. Soc., 1, 149
- Baker J, 2009, Conf. Proc. IEEE Eng. Med. Biol. Soc., 2009, 4573
- Perge JA, 2010, Neurosci. Meet. Plan.
- Li Z, 2010, Neurosci. Meet. Plan.
Cited by
Sorted by citations
Past, present and future of spike sorting techniques
Rey, H. G., Pedreira, C., & Quiroga, R. Q. (2015) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2015.04.007 · Cited by 451
EEG-based brain–computer interfaces
McFarland, D. J., & Wolpaw, J. R. (2017) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2017.11.004 · Cited by 283
A novel and fully automatic spike-sorting implementation with variable number of features
Chaure, F. J., Rey, H. G., & Quiroga, R. Q. (2018) · Journal of Neurophysiology · doi:10.1152/jn.00339.2018 · Cited by 218
Making brain–machine interfaces robust to future neural variability
Sussillo, D., Stavisky, S. D., Kao, J. C., Ryu, S. I., & Shenoy, K. V. (2016) · Nature Communications · doi:10.1038/ncomms13749 · Cited by 228
Hramov, A. E., Александрович, М. В., & Pisarchik, A. N. (2021) · Physics Reports · doi:10.1016/j.physrep.2021.03.002 · Cited by 228
Metadata
- Authors
- Homer, M. L., Nurmikko, A. V., Donoghue, J. P., & Hochberg, L. R.
- Affiliations
- Biomedical Engineering,
- School of Engineering,
- Brown University (US)
- Harvard University (US)
- Venue
- Annual Review of Biomedical Engineering
- Publisher
- Annual Reviews
- Published
- 2013-07-11
- Volume
- 15
- Issue
- 1
- Pages
- 383-405
- ISSN
- 1523-9829 (ISSN-L)
- 1545-4274
- PMC
- PMC3985135
- OpenAlex
- W2165100436
- Cited by
- 121
- References
- 121
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 7 · 2023: 9 · 2022: 10 · 2021: 9 · 2020: 12 · 2019: 7 · 2018: 10 · 2017: 9 · 2016: 16 · 2015: 14 · 2014: 11
- FWCI
- 1.17
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annual Review of Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Deafness and Other Communication Disorders (R01DC009899)
- National Institute of Neurological Disorders and Stroke (R01NS025074)
- National Institute of Biomedical Imaging and Bioengineering (R01EB007401)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- intracortical brain-computer interfaces, neural decoding, motor intention decoding, paralysis, neuroprosthetics, clinical translation
- MeSH terms
- Algorithms, Amputation, Surgical, Brain, Calibration, Electrodes, Implanted, Equipment Design, Humans, Paralysis, Signal Processing, Computer-Assisted, Brain-Computer Interfaces
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