Analysis of the capacitance of minimally insulated parallel wires implanted in biological tissue

Biology; Cabling; Capacitance; Finite-element method; Implants; Mathematical model; Cable sheathing; Dental prostheses; Electrodes; Finite element method; Insulating materials; Insulation; Mathematical models; Voltage regulators; Electrical stimulations; Electrode-tissue interface; Electrostatic solver; Porcine muscle tissue; Relative permittivity; Simulations and measurements; Stimulating electrodes; Tissue; Article

Abstract :

[en] State of the art bioelectronic implants are using thin cables for therapeutic electrical stimulation. If cable insulation is thin, biological tissue surrounding cables can be unintentionally stimulated. The capacitance of the cable must be much less than the stimulating electrodes to ensure stimulating currents are delivered to the electrode-tissue interface. This work derives and experimentally validates a model to determine the capacitance of parallel cables implanted in biological tissue. Biological tissue has a high relative permittivity, so the capacitance of cabling implanted in the human body depends on cable insulation thickness. Simulations and measurements demonstrate that insulation thickness influences the capacitance of implanted parallel cables across almost two orders of magnitude: from 20 pF/m to 700 pF/m. The results are verified using four different methods: solving the Laplacian numerically from first principles, using a commercially available electrostatic solver, and measuring twelve different parallel pairs of wires using two different potentiostats. Cable capacitance simulations and measurements are performed in air, a porcine blood pool and porcine muscle tissue. The results do not differ by more than 30% for a given cable across simulation and measurement methodologies. The modelling in this work can be used to design cabling for minimally-invasive biomedical implants. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Disciplines :

Electrical & electronics engineering

Author, co-author :

Tsai, Rong-Jhen; Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, Australia

Aldaoud, Ammar; School of Physics, University of Melbourne, Parkville, Australia

Redouté, Jean-Michel ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes microélectroniques intégrés

Garrett, David J.; School of Physics, University of Melbourne, Parkville, Australia

Prawer, Steven; School of Physics, University of Melbourne, Parkville, Australia

Grayden, David B.; Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia

Language :

English

Title :

Analysis of the capacitance of minimally insulated parallel wires implanted in biological tissue

Publication date :

2020

Journal title :

Biomedical Microdevices

ISSN :

1387-2176

eISSN :

1572-8781

Publisher :

Springer

Volume :

Issue :

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 31 March 2020

Statistics

Number of views

51 (3 by ULiège)

Number of downloads

5 (4 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

OpenAlex citations

Bibliography

J. Timperley. Pacemakers and ICDs. [electronic resource]., ser. Oxford Specialist Handbooks in Cardiology (Oxford University Press, Oxford, 2008)
D. Grayden, G. Clark, Implant design and development. Wiley - John Wiley & Sons (2006)
K.L. Chou, S. Grube, P.G. Patil. Deep Brain Stimulation: a New Life for People with Parkinson’s, Dystonia and Essential Tremor (Demos Health, New York, 2012)
D. Ashworth. I Spy with my Bionic Eye (Dorrance Publishing Co., Pittsburgh, 2014)
Y.H.-L. Luo, E. Fukushige, L. Da Cruz, The potential of the second sight system bionic eye implant for partial sight restoration. Expert Rev. Med. Devices. 13(7), 673–681 (2016)
K. Hu, M. Jamali, Z.B. Moses, G.N. Friedman, Z.M. Williams, W. Xu, C.A. Ortega, Decoding unconstrained arm movements in primates using high-density electrocorticography signals for brain-machine interface use. Sci. Rep. 8, 10583 (2018). 10.1038/s41598-018-28940-7
A. Ma, A.S.Y. Poon, Midfield wireless power transfer for bioelectronics. IEEE Circuits Syst. Mag. 15(2), 54 (2015)
G. Chitnis, T. Maleki, B. Samuels, L.B. Cantor, B. Ziaie, A minimally invasive implantable wireless pressure sensor for continuous iop monitoring. IEEE Trans. Biomed. Eng. 60(1), 250–256 (2013)
A. Aldaoud, A. Soto-Breceda, W. Tong, G. Conductier, M.A. Tonta, H.A. Coleman, H.C. Parkington, I. Clarke, J. -M. Redoute, D.J. Garrett, S. Prawer, Wireless multichannel optogenetic stimulators enabled by narrow bandwidth resonant tank circuits. Sens. Actuators A Phys. 271, 201–211 (2018)
A. Aldaoud, J. -M. Redoute, K. Ganesan, G.S. Rind, S.E. John, S.M. Ronayne, N.L. Opie, D.J. Garrett, S. Prawer, Near-field wireless power transfer to stent-based biomedical implants. IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology. 2(3), 193–200 (2018)
H. Lee, H. Park, M. Ghovanloo, A power-efficient wireless system with adaptive supply control for deep brain stimulation. IEEE J. Solid State Circuits. 48(9), 2203–2216 (2013)
A. Aldaoud, C. Laurenson, F. Rivet, M. Yuce, J. -M. Redoute, Design of a miniaturized wireless blood pressure sensing interface using capacitive coupling. IEEE/ASME Trans. Mech. 1, 487 (2015)
X. Liu, M. Zhang, T. Xiong, A.G. Richardson, T.H. Lucas, P.S. Chin, R. Etienne-Cummings, T.D. Tran, J.V. der Spiegel, A fully integrated wireless compressed sensing neural signal acquisition system for chronic recording and brain machine interface. IEEE Trans. Biomed. Circuits Syst. 10(4), 874–883 (2016)
J.V. der Spiegel, M. Zhang, X. Liu, The next-generation brain machine interface system for neuroscience research and neuroprosthetics development. In: 2017 IEEE 12th International Conference on ASIC (ASICON), pp. 436–439 (2017)
L. Karumbaiah, T. Saxena, D. Carlson, K. Patil, R. Patkar, E.A. Gaupp, M. Betancur, G.B. Stanley, L. Carin, R.V. Bellamkonda, Relationship between intracortical electrode design and chronic recording function. Biomaterials. 34, 8061–8074 (2013)
B. Ljungquist, P. Petersson, A.J. Johansson, J. Schouenborg, M. Garwicz, A bit-encoding based new data structure for time and memory efficient handling of spike times in an electrophysiological setup. Neuroinformatics. 16(2), 217–229 (2018)
A. Aldaoud, J. Redoute, K. Ganesan, G. Rind, S. John, S. Ronayne, N. Opie, D. Garrett, S. Prawer, A stent-based power and data link for sensing intravascular biological indicators. IEEE Sens. Lett. 2 (4), 1–4 (2018)
A. Aldaoud, S. Lui, K.S. Keng, S. Moshfegh, A. Soto-Breceda, W. Tong, J.-M. Redoute, D.J. Garrett, Y.T. Wong, S. Prawer, Wide dipole antennas for wireless powering of miniaturised bioelectronic devices. Sensing and Bio-Sensing Research (2019)
E. Musk, Neuralink An integrated brain-machine interface platform with thousands of channels. bioRxiv (2019)
S. Gabriel, R.W. Lau, C. Gabriel, The dielectric properties of biological tissues: Ii. measurements in the frequency range 10 hz to 20 ghz. Phys. Med. Biol. 41(11), 2251–2269 (1996)
R. Pomfret, K. Sillay, G. Miranpuri, Investigation of the electrical properties of agarose gel: characterization of concentration using nyquist plot phase angle and the implications of a more comprehensive in vitro model of the brain. Ann. Neurosci. 20(3), 99–107 (2013)
D.T. Brocker, W.M. Grill, Chapter 1: Principles of electrical stimulation of neural tissue. Handbook of Clinical Neurology. 116(Brain Stimulation), 3–18 (2013)
B.J. Roth, A mathematical model of make and break electrical stimulation of cardiac tissue by a unipolar anode or cathode. IEEE Transactions on Biomedical Engineering, Biomedical Engineering, IEEE Transactions on, IEEE Trans. Biomed. Eng. 12, 1174 (1995)
J.D. Jackson. Classical Electrodynamics (Wiley, New York, 1998)
U.V. Rienen, Numerical methods in computational electrodynamics: linear systems in practical applications., ser. Lecture notes in computational science and engineering Springer (2001)
G.L. E. Dhatt, G. Touzot, Finite Element Method. Wiley (2012)
H. Gao, R. Walker, P. Nuyujukian, K. Makinwa, K. Shenoy, B. Murmann, T. Meng, Hermese: a 96-channel full data rate direct neural interface in 0.13 μ m cmos. IEEE Journal of Solid-State Circuits, Solid-State Circuits, IEEE Journal of, IEEE J. Solid-State Circuits. 4, 1043 (2012)
L. Luan, X. Wei, Z. Zhao, J.J. Siegel, O. Potnis, C.A. Tuppen, S. Lin, S. Kazmi, R.A. Fowler, S. Holloway, A.K. Dunn, R.A. Chitwood, C. Xie, Ultraflexible nanoelectronic probes form reliable, glial scar-free neural integration. Science Advances 3(2) (2017). 10.1126/sciadv.1601966. https://advances.sciencemag.org/content/3/2/e1601966
J.J. Pancrazio, F. Deku, A. Ghazavi, A.M. Stiller, R. Rihani, C.L. Frewin, V.D. Varner, T.J. Gardner, S.F. Cogan, Thinking small: Progress on microscale neurostimulation technology. Neuromodulation. 8, 745 (2017)
Z. Zhao, X. Li, F. He, X. Wei, S. Lin, C. Xie, Parallel, minimally-invasive implantation of ultra-flexible neural electrode arrays. Journal Of Neural Engineering (2019)
W. Tong, K. Fox, K. Ganesan, A.M. Turnley, O. Shimoni, P.A. Tran, A. Lohrmann, T. McFarlane, A. Ahnood, D.J. Garrett, H. Meffin, N.M. O’Brien-Simpson, E.C. Reynolds, S. Prawer, Fabrication of planarised conductively patterned diamond for bio-applications. Mater. Sci. Eng. C. 43, 135–144 (2014)
A.R. Harris, C. Newbold, P. Carter, R. Cowan, G.G. Wallace, Measuring the effective area and charge density of platinum electrodes for bionic devices. J. Neural. Eng. 4(15), 046015 (2018)
R. Liu, R. Chen, A.T. Elthakeb, S.H. Lee, S. Hinckley, M.L. Khraiche, J. Scott, D. Pre, Y. Hwang, A. Tanaka, Y.G. Ro, A.K. Matsushita, X. Dai, C. Soci, S. Biesmans, A. James, J. Nogan, K.L. Jungjohann, D.V. Pete, D.B. Webb, Y. Zou, A.G. Bang, S.A. Dayeh, High density individually addressable nanowire arrays record intracellular activity from primary rodent and human stem cell derived neurons. Nano Lett. 17(5), 2757–2764 (2017)