Selective recording of the canine hypoglossal nerve using a multicontact flat interface nerve electrode
Abstract
A flat-interface nerve electrode (FINE) is presented as a potential solution for using multifascicle nerve recordings as part of a closed-loop control system. To investigate the ability of this electrode to achieve selective recordings at physiological signal-to-noise ratio (SNR), a finite-element model (FEM) of a beagle hypoglossal nerve with an implanted FINE was constructed. Action potentials (AP) were generated at various SNR levels and the performance of the electrode was assessed with a selectivity index (0 < or = SI < or = 1; ability of the electrode to distinguish two active sources). Computer simulations yielded a selective range (0.05 < or = SI < or = 0.76) that was 1) related to the interfiber distance and 2) used to predict the minimum interfiber distance (0.23 mm < or = d < or = 1.42 mm) for selective recording at each SNR. The SI was further evaluated using recorded compound APs elicited from electrically activating the branches of the beagle hypoglossal nerve. For all experiments (n = 7), the selectivity (SI = 0.45 +/- 0.16) was within the range predicted by the FEM. This study suggests that the FINE can record the activity from a multifasciculated nerve and, more importantly, distinguish neural signals from pairs of fascicles at physiologic SNR.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
FINE's recording ability and selectivity of the periphery of the stimulated nerve have been demonstrated.
“Its recording ability (Yoo and Durand, 2005) and selectivity of the periphery of the stimulated nerve have been demonstrated (Schiefer et al., 2013; Ortiz-Catalan et al., 2014).”
From Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review. (2017) · cites this paper as Yoo and Durand, 2005
Cites
A spiral nerve cuff electrode for peripheral nerve stimulation
Naples, G. G., Mortimer, J. T., Scheiner, A., & Sweeney, J. D. (1988) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.8670 · Cited by 415 · see citing works
Functionally selective peripheral nerve stimulation with a flat interface nerve electrode
Tyler, D. J., & Durand, D. M. (2002) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2002.806840 · Cited by 398 · cited 1× · see citing works
“The flat-interface nerve electrode (FINE) presents a unique cuff electrode design for selective nerve recording by realigning the fascicles and reshaping the nerve into a more flattened cross section [25].”
Self-citationA multielectrode array for intrafascicular recording and stimulation in sciatic nerve of cats
Branner, A., & Normann, R. A. (2000) · Brain Research Bulletin · doi:10.1016/s0361-9230(99)00231-2 · Cited by 234 · see citing works
Sensory nerve recording for closed‐loop control to restore motor functions
Popovic, D. B., Stein, R. B., Jovanovic, K. L., Dai, R., Kostov, A., & Armstrong, W. W. (1993) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.247801 · Cited by 159 · see citing works
Chronic Response of the Rat Sciatic Nerve to the Flat Interface Nerve Electrode
Tyler, D. J., & Durand, D. M. (2003) · Annals of Biomedical Engineering · doi:10.1114/1.1569263 · Cited by 144 · cited 1× · see citing works
“postimplant changes in nerve histology or physiology [41].”
Self-citationRecruitment characteristics of nerve fascicles stimulated by a multigroove electrode
Koole, P., Holsheimer, J., Struijk, J. J., & Verloop, A. J. (1997) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/86.559348 · Cited by 56 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Implanted Neural Interfaces: Biochallenges and Engineered Solutions
Grill, W. M., Norman, S. E., & Bellamkonda, R. V. (2009) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-061008-124927 · Cited by 488 · see citing works
Implantable neurotechnologies: a review of micro- and nanoelectrodes for neural recording
Patil, A. C., & Thakor, N. V. (2016) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-015-1430-4 · Cited by 175 · see citing works
Fascicular perineurium thickness, size, and position affect model predictions of neural excitation
Grinberg, Y., Schiefer, M. A., Tyler, D. J., & Gustafson, K. J. (2008) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2008.2010348 · Cited by 145 · see citing works
“It has been used as a method of predicting stimulation selectivity of fascicles and nerve fibers [9-15, 17, 31] and neural recording selectivity [18-22] using various electrode configurations.”
Ortiz-Catalan, M., Brånemark, R., Håkansson, B., & Delbeke, J. (2012) · BioMedical Engineering OnLine · doi:10.1186/1475-925x-11-33 · Cited by 144 · see citing works
Neural interfaces for somatosensory feedback: bringing life to a prosthesis
Tyler, D. J. (2015) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000266 · Cited by 105 · see citing works
Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review.
Ghafoor, U., Kim, S., & Hong, K.-S. (2017) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2017.00059 · Cited by 88 · see citing works
“Its recording ability (Yoo and Durand, 2005) and selectivity of the periphery of the stimulated nerve have been demonstrated (Schiefer et al.”
Update on Peripheral Nerve Electrodes for Closed-Loop Neuroprosthetics
Rijnbeek, E. H., Eleveld, N., & Olthuis, W. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00350 · Cited by 91 · see citing works
“One way to describe the signal quality is the signal-to-noise ratio as has been done by multiple studies (Branner and Normann, 2000; Yoo and Durand, 2005; Citi et al., 2011; Srinivasan et al., 2015; Dweiri et al., 2017; Lee et al., 2017).”
Raspopovic, S., Carpaneto, J., Udina, E., Navarro, X., & Micera, S. (2010) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-7-17 · Cited by 81 · see citing works
Chronic multichannel neural recordings from soft regenerative microchannel electrodes during gait
Musick, K. M., Rigosa, J., Narasimhan, S., Wurth, S., Capogrosso, M., Chew, D. J., Fawcett, J. W., Micera, S., & Lacour, S. P. (2015) · Scientific Reports · doi:10.1038/srep14363 · Cited by 70 · see citing works
Motor-commands decoding using peripheral nerve signals: a review
Hong, K.-S., Aziz, N., & Ghafoor, U. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aab383 · Cited by 63 · see citing works
A Parylene Self-Locking Cuff Electrode for Peripheral Nerve Stimulation and Recording
Yu, H., Xiong, W., Zhang, H., Wang, W., & Li, Z. (2014) · Journal of Microelectromechanical Systems · doi:10.1109/jmems.2014.2333733 · Cited by 56 · see citing works
Stable Detection of Movement Intent From Peripheral Nerves: Chronic Study in Dogs
Dweiri, Y. M., Eggers, T. E., Gonzalez-Reyes, L. E., Drain, J., McCallum, G. A., & Durand, D. M. (2017) · Proceedings of the IEEE · doi:10.1109/jproc.2016.2607520 · Cited by 44 · see citing works
Self-citationNielsen, T. N., Sevcencu, C., & Struijk, J. J. (2014) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2013.2278479 · Cited by 15 · see citing works
- Authors
- Yoo, P. B., & Durand, D. M.
- Affiliations
- Duke University (US)
- Case Western Reserve University (US)
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2005-08
- Volume
- 52
- Issue
- 8
- Pages
- 1461-1469
- ISSN
- 0018-9294 (ISSN-L)
- OpenAlex
- W2152448309
- Cited by
- 106
- References
- 6
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2022: 3 · 2021: 4 · 2020: 3 · 2019: 6 · 2018: 11 · 2017: 9 · 2016: 12 · 2015: 10 · 2014: 6 · 2013: 7 · 2012: 3
- FWCI
- 1.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- National Institutes of Health (5r01hl066267-04)
- National Heart, Lung, and Blood Institute (1 R01 HL66267-01)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Life Sciences › Neuroscience › Neurology › Vagus Nerve Stimulation Research
- Keywords
- hypoglossal nerve, signal-to-noise ratio, finite element analysis, action potential, compound action potential, beagle dogs
- MeSH terms
- Action Potentials, Animals, Computer Simulation, Diagnosis, Computer-Assisted, Dogs, Electrodes, Implanted, Electrodiagnosis, Equipment Design, Hypoglossal Nerve, Microelectrodes, Models, Neurological, Sensitivity and Specificity, Reproducibility of Results, Computer-Aided Design, Equipment Failure Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
