1
|
Wang X, Zhang Y, Guo T, Wu S, Zhong J, Cheng C, Sui X. Selective intrafascicular stimulation of myelinated and unmyelinated nerve fibers through a longitudinal electrode: A computational study. Comput Biol Med 2024; 176:108556. [PMID: 38733726 DOI: 10.1016/j.compbiomed.2024.108556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 05/05/2024] [Indexed: 05/13/2024]
Abstract
Carbon nanotube (CNT) fiber electrodes have demonstrated exceptional spatial selectivity and sustained reliability in the context of intrafascicular electrical stimulation, as evidenced through rigorous animal experimentation. A significant presence of unmyelinated C fibers, known to induce uncomfortable somatosensory experiences, exists within peripheral nerves. This presence poses a considerable challenge to the excitation of myelinated Aβ fibers, which are crucial for tactile sensation. To achieve nuanced tactile sensory feedback utilizing CNT fiber electrodes, the selective stimulation of Aβ sensory afferents emerges as a critical factor. In confronting this challenge, the present investigation sought to refine and apply a rat sciatic-nerve model leveraging the capabilities of the COMSOL-NEURON framework. This approach enables a systematic evaluation of the influence exerted by stimulation parameters and electrode geometry on the activation dynamics of both myelinated Aβ and unmyelinated C fibers. The findings advocate for the utilization of current pulses featuring a pulse width of 600 μs, alongside the deployment of CNT fibers characterized by a diminutive diameter of 10 μm, with an exclusively exposed cross-sectional area, to facilitate reduced activation current thresholds. Comparative analysis under monopolar and bipolar electrical stimulation conditions revealed proximate activation thresholds, albeit with bipolar stimulation exhibiting superior fiber selectivity relative to its monopolar counterpart. Concerning pulse waveform characteristics, the adoption of an anodic-first biphasic stimulation modality is favored, taking into account the dual criteria of activation threshold and fiber selectivity optimization. Consequently, this investigation furnishes an efficacious stimulation paradigm for the selective activation of touch-related nerve fibers, alongside provisioning a comprehensive theoretical foundation for the realization of natural tactile feedback within the domain of prosthetic hand applications.
Collapse
Affiliation(s)
- Xintong Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Yapeng Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Tianruo Guo
- Graduate School of Biomedical Engineering, The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Shuhui Wu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Junwen Zhong
- Department of Electromechanical Engineering, University of Macau, Macau SAR, 999078, China
| | - Chengkung Cheng
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China; Med-X Research Institute, Shanghai Jiao Tong University, Engineering Research Center of Digital Medicine, Ministry of Education, Shanghai, China
| | - Xiaohong Sui
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
| |
Collapse
|
2
|
Katic Secerovic N, Balaguer JM, Gorskii O, Pavlova N, Liang L, Ho J, Grigsby E, Gerszten PC, Karal-Ogly D, Bulgin D, Orlov S, Pirondini E, Musienko P, Raspopovic S, Capogrosso M. Neural population dynamics reveals disruption of spinal circuits' responses to proprioceptive input during electrical stimulation of sensory afferents. Cell Rep 2024; 43:113695. [PMID: 38245870 PMCID: PMC10962447 DOI: 10.1016/j.celrep.2024.113695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 11/08/2023] [Accepted: 01/06/2024] [Indexed: 01/23/2024] Open
Abstract
While neurostimulation technologies are rapidly approaching clinical applications for sensorimotor disorders, the impact of electrical stimulation on network dynamics is still unknown. Given the high degree of shared processing in neural structures, it is critical to understand if neurostimulation affects functions that are related to, but not targeted by, the intervention. Here, we approach this question by studying the effects of electrical stimulation of cutaneous afferents on unrelated processing of proprioceptive inputs. We recorded intraspinal neural activity in four monkeys while generating proprioceptive inputs from the radial nerve. We then applied continuous stimulation to the radial nerve cutaneous branch and quantified the impact of the stimulation on spinal processing of proprioceptive inputs via neural population dynamics. Proprioceptive pulses consistently produce neural trajectories that are disrupted by concurrent cutaneous stimulation. This disruption propagates to the somatosensory cortex, suggesting that electrical stimulation can perturb natural information processing across the neural axis.
Collapse
Affiliation(s)
- Natalija Katic Secerovic
- School of Electrical Engineering, University of Belgrade, 11000 Belgrade, Serbia; The Mihajlo Pupin Institute, University of Belgrade, 11060 Belgrade, Serbia; Laboratory for Neuroengineering, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092 Zürich, Switzerland
| | - Josep-Maria Balaguer
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Oleg Gorskii
- Institute of Translational Biomedicine, Saint-Petersburg State University, 199034 Saint-Petersburg, Russia; Pavlov Institute of Physiology, Russian Academy of Sciences, 199034 Saint-Petersburg, Russia; National University of Science and Technology "MISIS," 4 Leninskiy Pr., 119049 Moscow, Russia
| | - Natalia Pavlova
- Institute of Translational Biomedicine, Saint-Petersburg State University, 199034 Saint-Petersburg, Russia
| | - Lucy Liang
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Jonathan Ho
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Erinn Grigsby
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Peter C Gerszten
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Dzhina Karal-Ogly
- National Research Centre "Kurchatov Institute," 123098 Moscow, Russia
| | - Dmitry Bulgin
- National Research Centre "Kurchatov Institute," 123098 Moscow, Russia; Sirius University of Science and Technology, 354340 Sochi, Russia
| | - Sergei Orlov
- National Research Centre "Kurchatov Institute," 123098 Moscow, Russia
| | - Elvira Pirondini
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Neural Basis of Cognition, Pittsburgh, PA, USA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Pavel Musienko
- Institute of Translational Biomedicine, Saint-Petersburg State University, 199034 Saint-Petersburg, Russia; Sirius University of Science and Technology, 354340 Sochi, Russia; Life Improvement by Future Technologies Center "LIFT," 143025 Moscow, Russia
| | - Stanisa Raspopovic
- Laboratory for Neuroengineering, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092 Zürich, Switzerland.
| | - Marco Capogrosso
- Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA; Center for Neural Basis of Cognition, Pittsburgh, PA, USA; Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA.
| |
Collapse
|
3
|
Musselman ED, Pelot NA, Grill WM. Validated computational models predict vagus nerve stimulation thresholds in preclinical animals and humans. J Neural Eng 2023; 20:10.1088/1741-2552/acda64. [PMID: 37257454 PMCID: PMC10324064 DOI: 10.1088/1741-2552/acda64] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 05/31/2023] [Indexed: 06/02/2023]
Abstract
Objective.We demonstrated how automated simulations to characterize electrical nerve thresholds, a recently published open-source software for modeling stimulation of peripheral nerves, can be applied to simulate accurately nerve responses to electrical stimulation.Approach.We simulated vagus nerve stimulation (VNS) for humans, pigs, and rats. We informed our models using histology from sample-specific or representative nerves, device design features (i.e. cuff, waveform), published material and tissue conductivities, and realistic fiber models.Main results.Despite large differences in nerve size, cuff geometry, and stimulation waveform, the models predicted accurate activation thresholds across species and myelinated fiber types. However, our C fiber model thresholds overestimated thresholds across pulse widths, suggesting that improved models of unmyelinated nerve fibers are needed. Our models of human VNS yielded accurate thresholds to activate laryngeal motor fibers and captured the inter-individual variability for both acute and chronic implants. For B fibers, our small-diameter fiber model underestimated threshold and saturation for pulse widths >0.25 ms. Our models of pig VNS consistently captured the range ofin vivothresholds across all measured nerve and physiological responses (i.e. heart rate, Aδ/B fibers, Aγfibers, electromyography, and Aαfibers). In rats, our smallest diameter myelinated fibers accurately predicted fast fiber thresholds across short and intermediate pulse widths; slow unmyelinated fiber thresholds overestimated thresholds across shorter pulse widths, but there was overlap for pulse widths >0.3 ms.Significance.We elevated standards for models of peripheral nerve stimulation in populations of models across species, which enabled us to model accurately nerve responses, demonstrate that individual-specific differences in nerve morphology produce variability in neural and physiological responses, and predict mechanisms of VNS therapeutic and side effects.
Collapse
Affiliation(s)
- Eric D Musselman
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Nicole A Pelot
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Warren M Grill
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America
- Department of Neurobiology, Duke University, Durham, NC, United States of America
- Department of Neurosurgery, Duke University, Durham, NC, United States of America
| |
Collapse
|
4
|
Ciotti F, Cimolato A, Valle G, Raspopovic S. Design of an adaptable intrafascicular electrode (AIR) for selective nerve stimulation by model-based optimization. PLoS Comput Biol 2023; 19:e1011184. [PMID: 37228174 DOI: 10.1371/journal.pcbi.1011184] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 05/15/2023] [Indexed: 05/27/2023] Open
Abstract
Peripheral nerve stimulation is being investigated as a therapeutic tool in several clinical scenarios. However, the adopted devices have restricted ability to obtain desired outcomes with tolerable off-target effects. Recent promising solutions are not yet employed in clinical practice due to complex required surgeries, lack of long-term stability, and implant invasiveness. Here, we aimed to design a neural interface to address these issues, specifically dimensioned for pudendal and sacral nerves to potentially target sexual, bladder, or bowel dysfunctions. We designed the adaptable intrafascicular radial electrode (AIR) through realistic computational models. They account for detailed human anatomy, inhomogeneous anisotropic conductance, following the trajectories of axons along curving and branching fascicles, and detailed biophysics of axons. The model was validated against available experimental data. Thanks to computationally efficient geometry-based selectivity estimations we informed the electrode design, optimizing its dimensions to obtain the highest selectivity while maintaining low invasiveness. We then compared the AIR with state-of-the-art electrodes, namely InterStim leads, multipolar cuffs and transversal intrafascicular multichannel electrodes (TIME). AIR, comprising a flexible substrate, surface active sites, and radially inserted intrafascicular needles, is designed to be implanted in a few standard steps, potentially enabling fast implants. It holds potential for repeatable stimulation outcomes thanks to its radial structural symmetry. When compared in-silico, AIR consistently outperformed cuff electrodes and InterStim leads in terms of recruitment threshold and stimulation selectivity. AIR performed similarly or better than a TIME, with quantified less invasiveness. Finally, we showed how AIR can adapt to different nerve sizes and varying shapes while maintaining high selectivity. The AIR electrode shows the potential to fill a clinical need for an effective peripheral nerve interface. Its high predicted performance in all the identified requirements was enabled by a model-based approach, readily applicable for the optimization of electrode parameters in any peripheral nerve stimulation scenario.
Collapse
Affiliation(s)
- Federico Ciotti
- Department of Health Sciences and Technology, Institute of Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
| | - Andrea Cimolato
- Department of Health Sciences and Technology, Institute of Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
| | - Giacomo Valle
- Department of Health Sciences and Technology, Institute of Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
| | - Stanisa Raspopovic
- Department of Health Sciences and Technology, Institute of Robotics and Intelligent Systems, ETH Zürich, Zürich, Switzerland
| |
Collapse
|
5
|
Symbiotic electroneural and musculoskeletal framework to encode proprioception via neurostimulation: ProprioStim. iScience 2023; 26:106248. [PMID: 36923003 PMCID: PMC10009292 DOI: 10.1016/j.isci.2023.106248] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 11/23/2022] [Accepted: 02/16/2023] [Indexed: 02/23/2023] Open
Abstract
Peripheral nerve stimulation in amputees achieved the restoration of touch, but not proprioception, which is critical in locomotion. A plausible reason is the lack of means to artificially replicate the complex activity of proprioceptors. To uncover this, we coupled neuromuscular models from ten subjects and nerve histologies from two implanted amputees to develop ProprioStim: a framework to encode proprioception by electrical evoking neural activity in close agreement with natural proprioceptive activity. We demonstrated its feasibility through non-invasive stimulation on seven healthy subjects comparing it with standard linear charge encoding. Results showed that ProprioStim multichannel stimulation was felt more natural, and hold promises for increasing accuracy in knee angle tracking, especially in future implantable solutions. Additionally, we quantified the importance of realistic 3D-nerve models against extruded models previously adopted for further design and validation of novel neurostimulation encoding strategies. ProprioStim provides clear guidelines for the development of neurostimulation policies restoring natural proprioception.
Collapse
|
6
|
Ottaviani MM, Vallone F, Micera S, Recchia FA. Closed-Loop Vagus Nerve Stimulation for the Treatment of Cardiovascular Diseases: State of the Art and Future Directions. Front Cardiovasc Med 2022; 9:866957. [PMID: 35463766 PMCID: PMC9021417 DOI: 10.3389/fcvm.2022.866957] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 03/14/2022] [Indexed: 01/07/2023] Open
Abstract
The autonomic nervous system exerts a fine beat-to-beat regulation of cardiovascular functions and is consequently involved in the onset and progression of many cardiovascular diseases (CVDs). Selective neuromodulation of the brain-heart axis with advanced neurotechnologies is an emerging approach to corroborate CVDs treatment when classical pharmacological agents show limited effectiveness. The vagus nerve is a major component of the cardiac neuroaxis, and vagus nerve stimulation (VNS) is a promising application to restore autonomic function under various pathological conditions. VNS has led to encouraging results in animal models of CVDs, but its translation to clinical practice has not been equally successful, calling for more investigation to optimize this technique. Herein we reviewed the state of the art of VNS for CVDs and discuss avenues for therapeutic optimization. Firstly, we provided a succinct description of cardiac vagal innervation anatomy and physiology and principles of VNS. Then, we examined the main clinical applications of VNS in CVDs and the related open challenges. Finally, we presented preclinical studies that aim at overcoming VNS limitations through optimization of anatomical targets, development of novel neural interface technologies, and design of efficient VNS closed-loop protocols.
Collapse
Affiliation(s)
- Matteo Maria Ottaviani
- Institute of Life Sciences, Scuola Superiore Sant’Anna, Pisa, Italy
- Department of Excellence in Robotics and Artificial Intelligence, The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy
| | - Fabio Vallone
- Department of Excellence in Robotics and Artificial Intelligence, The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy
| | - Silvestro Micera
- Department of Excellence in Robotics and Artificial Intelligence, The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy
- Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics, Institute of Bioengineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Fabio A. Recchia
- Institute of Life Sciences, Scuola Superiore Sant’Anna, Pisa, Italy
- Fondazione Toscana Gabriele Monasterio, Pisa, Italy
- Department of Physiology, Cardiovascular Research Center, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, United States
| |
Collapse
|
7
|
Roh H, Yoon YJ, Park JS, Kang DH, Kwak SM, Lee BC, Im M. Fabrication of High-Density Out-of-Plane Microneedle Arrays with Various Heights and Diverse Cross-Sectional Shapes. NANO-MICRO LETTERS 2021; 14:24. [PMID: 34888758 PMCID: PMC8656445 DOI: 10.1007/s40820-021-00778-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/16/2021] [Indexed: 06/01/2023]
Abstract
Out-of-plane microneedle structures are widely used in various applications such as transcutaneous drug delivery and neural signal recording for brain machine interface. This work presents a novel but simple method to fabricate high-density silicon (Si) microneedle arrays with various heights and diverse cross-sectional shapes depending on photomask pattern designs. The proposed fabrication method is composed of a single photolithography and two subsequent deep reactive ion etching (DRIE) steps. First, a photoresist layer was patterned on a Si substrate to define areas to be etched, which will eventually determine the final location and shape of each individual microneedle. Then, the 1st DRIE step created deep trenches with a highly anisotropic etching of the Si substrate. Subsequently, the photoresist was removed for more isotropic etching; the 2nd DRIE isolated and sharpened microneedles from the predefined trench structures. Depending on diverse photomask designs, the 2nd DRIE formed arrays of microneedles that have various height distributions, as well as diverse cross-sectional shapes across the substrate. With these simple steps, high-aspect ratio microneedles were created in the high density of up to 625 microneedles mm-2 on a Si wafer. Insertion tests showed a small force as low as ~ 172 µN/microneedle is required for microneedle arrays to penetrate the dura mater of a mouse brain. To demonstrate a feasibility of drug delivery application, we also implemented silk microneedle arrays using molding processes. The fabrication method of the present study is expected to be broadly applicable to create microneedle structures for drug delivery, neuroprosthetic devices, and so on.
Collapse
Affiliation(s)
- Hyeonhee Roh
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, South Korea
- Division of Electrical Engineering, College of Engineering, Korea University, Seoul, 02841, South Korea
| | - Young Jun Yoon
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, South Korea
| | - Jin Soo Park
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, South Korea
- Division of Electrical Engineering, College of Engineering, Korea University, Seoul, 02841, South Korea
| | - Dong-Hyun Kang
- Micro/Nano Fabrication Center, KIST, Seoul, 02792, South Korea
| | - Seung Min Kwak
- Micro/Nano Fabrication Center, KIST, Seoul, 02792, South Korea
| | - Byung Chul Lee
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, South Korea
| | - Maesoon Im
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, South Korea.
- Division of Bio-Medical Science & Technology, KIST School, University of Science & Technology (UST), Seoul, 02792, South Korea.
| |
Collapse
|
8
|
Badi M, Wurth S, Scarpato I, Roussinova E, Losanno E, Bogaard A, Delacombaz M, Borgognon S, C Vanc Ara P, Fallegger F, Su DK, Schmidlin E, Courtine G, Bloch J, Lacour SP, Stieglitz T, Rouiller EM, Capogrosso M, Micera S. Intrafascicular peripheral nerve stimulation produces fine functional hand movements in primates. Sci Transl Med 2021; 13:eabg6463. [PMID: 34705521 DOI: 10.1126/scitranslmed.abg6463] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
[Figure: see text].
Collapse
Affiliation(s)
- Marion Badi
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, and Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Sophie Wurth
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, and Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Ilaria Scarpato
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, and Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Evgenia Roussinova
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, and Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Elena Losanno
- Biorobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56025 Pisa, Italy
| | - Andrew Bogaard
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and Medicine, University of Fribourg, 1700 Fribourg, Switzerland
| | - Maude Delacombaz
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and Medicine, University of Fribourg, 1700 Fribourg, Switzerland
| | - Simon Borgognon
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and Medicine, University of Fribourg, 1700 Fribourg, Switzerland.,Center for Neuroprosthetics and Brain Mind Institute, School of Life Sciences, EPFL, 1015 Lausanne, Switzerland
| | - Paul C Vanc Ara
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, Bernstein Center Freiburg, and BrainLinks-BrainTools Center, University of Freiburg, 79110 Freiburg, Germany
| | - Florian Fallegger
- Bertarelli Foundation Chair in Neuroprosthetic Technology, Laboratory for Soft Bioelectronics Interface, Institute of Microengineering, Institute of Bioengineering, Centre for Neuroprosthetics, 1202 Geneva, Switzerland
| | - David K Su
- Neurological Surgery, Harborview Medical Center, Seattle, WA 98104, USA
| | - Eric Schmidlin
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and Medicine, University of Fribourg, 1700 Fribourg, Switzerland
| | - Grégoire Courtine
- Center for Neuroprosthetics and Brain Mind Institute, School of Life Sciences, EPFL, 1015 Lausanne, Switzerland.,Defitech Center for Interventional Neurotherapies (NeuroRestore), EPFL, University Hospital of Lausanne (CHUV), and University of Lausanne (UNIL), 1015 Lausanne, Switzerland
| | - Jocelyne Bloch
- Defitech Center for Interventional Neurotherapies (NeuroRestore), EPFL, University Hospital of Lausanne (CHUV), and University of Lausanne (UNIL), 1015 Lausanne, Switzerland
| | - Stéphanie P Lacour
- Bertarelli Foundation Chair in Neuroprosthetic Technology, Laboratory for Soft Bioelectronics Interface, Institute of Microengineering, Institute of Bioengineering, Centre for Neuroprosthetics, 1202 Geneva, Switzerland
| | - Thomas Stieglitz
- Laboratory for Biomedical Microtechnology, Department of Microsystems Engineering-IMTEK, Bernstein Center Freiburg, and BrainLinks-BrainTools Center, University of Freiburg, 79110 Freiburg, Germany
| | - Eric M Rouiller
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and Medicine, University of Fribourg, 1700 Fribourg, Switzerland
| | - Marco Capogrosso
- Department of Neuroscience and Movement Sciences, Platform of Translational Neurosciences, Section of Medicine, Faculty of Sciences and Medicine, University of Fribourg, 1700 Fribourg, Switzerland.,Department of Neurological Surgery, Rehabilitation and Neural Engineering Laboratories, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Silvestro Micera
- Bertarelli Foundation Chair in Translational Neuroengineering, Center for Neuroprosthetics, and Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.,Biorobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56025 Pisa, Italy
| |
Collapse
|
9
|
Vallone F, Ottaviani MM, Dedola F, Cutrone A, Romeni S, Panarese AM, Bernini F, Cracchiolo M, Strauss I, Gabisonia K, Gorgodze N, Mazzoni A, Recchia FA, Micera S. Simultaneous decoding of cardiovascular and respiratory functional changes from pig intraneural vagus nerve signals. J Neural Eng 2021; 18. [PMID: 34153949 DOI: 10.1088/1741-2552/ac0d42] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 06/21/2021] [Indexed: 12/15/2022]
Abstract
Objective. Bioelectronic medicine is opening new perspectives for the treatment of some major chronic diseases through the physical modulation of autonomic nervous system activity. Being the main peripheral route for electrical signals between central nervous system and visceral organs, the vagus nerve (VN) is one of the most promising targets. Closed-loop VN stimulation (VNS) would be crucial to increase effectiveness of this approach. Therefore, the extrapolation of useful physiological information from VN electrical activity would represent an invaluable source for single-target applications. Here, we present an advanced decoding algorithm novel to VN studies and properly detecting different functional changes from VN signals.Approach. VN signals were recorded using intraneural electrodes in anaesthetized pigs during cardiovascular and respiratory challenges mimicking increases in arterial blood pressure, tidal volume and respiratory rate. We developed a decoding algorithm that combines discrete wavelet transformation, principal component analysis, and ensemble learning made of classification trees.Main results. The new decoding algorithm robustly achieved high accuracy levels in identifying different functional changes and discriminating among them. Interestingly our findings suggest that electrodes positioning plays an important role on decoding performances. We also introduced a new index for the characterization of recording and decoding performance of neural interfaces. Finally, by combining an anatomically validated hybrid neural model and discrimination analysis, we provided new evidence suggesting a functional topographical organization of VN fascicles.Significance. This study represents an important step towards the comprehension of VN signaling, paving the way for the development of effective closed-loop VNS systems.
Collapse
Affiliation(s)
- Fabio Vallone
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Matteo Maria Ottaviani
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy.,Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Francesca Dedola
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Annarita Cutrone
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Simone Romeni
- Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Adele Macrí Panarese
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Fabio Bernini
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Marina Cracchiolo
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Ivo Strauss
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Khatia Gabisonia
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Nikoloz Gorgodze
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Alberto Mazzoni
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Fabio A Recchia
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Fondazione Toscana Gabriele Monasterio, Pisa, Italy.,Department of Physiology, Cardiovascular Research Center, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, United States of America
| | - Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy.,Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| |
Collapse
|
10
|
Tutorial: a computational framework for the design and optimization of peripheral neural interfaces. Nat Protoc 2020; 15:3129-3153. [DOI: 10.1038/s41596-020-0377-6] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 06/15/2020] [Indexed: 01/05/2023]
|
11
|
Capllonch-Juan M, Sepulveda F. Modelling the effects of ephaptic coupling on selectivity and response patterns during artificial stimulation of peripheral nerves. PLoS Comput Biol 2020; 16:e1007826. [PMID: 32479499 PMCID: PMC7263584 DOI: 10.1371/journal.pcbi.1007826] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 03/27/2020] [Indexed: 11/18/2022] Open
Abstract
Artificial electrical stimulation of peripheral nerves for sensory feedback restoration can greatly benefit from computational models for simulation-based neural implant design in order to reduce the trial-and-error approach usually taken, thus potentially significantly reducing research and development costs and time. To this end, we built a computational model of a peripheral nerve trunk in which the interstitial space between the fibers and the tissues was modelled using a resistor network, thus enabling distance-dependent ephaptic coupling between myelinated axons and between fascicles as well. We used the model to simulate a) the stimulation of a nerve trunk model with a cuff electrode, and b) the propagation of action potentials along the axons. Results were used to investigate the effect of ephaptic interactions on recruitment and selectivity stemming from artificial (i.e., neural implant) stimulation and on the relative timing between action potentials during propagation. Ephaptic coupling was found to increase the number of fibers that are activated by artificial stimulation, thus reducing the artificial currents required for axonal recruitment, and it was found to reduce and shift the range of optimal stimulation amplitudes for maximum inter-fascicular selectivity. During propagation, while fibers of similar diameters tended to lock their action potentials and reduce their conduction velocities, as expected from previous knowledge on bundles of identical axons, the presence of many other fibers of different diameters was found to make their interactions weaker and unstable.
Collapse
|
12
|
Raspopovic S, Cimolato A, Panarese A, Vallone F, Del Valle J, Micera S, Navarro X. Neural signal recording and processing in somatic neuroprosthetic applications. A review. J Neurosci Methods 2020; 337:108653. [PMID: 32114143 DOI: 10.1016/j.jneumeth.2020.108653] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 11/30/2019] [Accepted: 02/26/2020] [Indexed: 12/11/2022]
Abstract
Neurointerfaces have acquired major relevance as both rehabilitative and therapeutic tools for patients with spinal cord injury, limb amputations and other neural disorders. Bidirectional neural interfaces are a key component for the functional control of neuroprosthetic devices. The two main neuroprosthetic applications of interfaces with the peripheral nervous system (PNS) are: the refined control of artificial prostheses with sensory neural feedback, and functional electrical stimulation (FES) systems attempting to generate motor or visceral responses in paralyzed organs. The results obtained in experimental and clinical studies with both, extraneural and intraneural electrodes are very promising in terms of the achieved functionality for the neural stimulation mode. However, the results of neural recordings with peripheral nerve interfaces are more limited. In this paper we review the different existing approaches for PNS signals recording, denoising, processing and classification, enabling their use for bidirectional interfaces. PNS recordings can provide three types of signals: i) population activity signals recorded by using extraneural electrodes placed on the outer surface of the nerve, which carry information about cumulative nerve activity; ii) spike activity signals recorded with intraneural electrodes placed inside the nerve, which carry information about the electrical activity of a set of individual nerve fibers; and iii) hybrid signals, which contain both spiking and cumulative signals. Finally, we also point out some of the main limitations, which are hampering clinical translation of neural decoding, and indicate possible solutions for improvement.
Collapse
Affiliation(s)
- Stanisa Raspopovic
- Neuroengineering Lab, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092, Zürich, Switzerland
| | - Andrea Cimolato
- Neuroengineering Lab, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH Zürich, 8092, Zürich, Switzerland; NEARLab - Neuroengineering and Medical Robotics Laboratory, DEIB Department of Electronics, Information and Bioengineering, Politecnico Di Milano, 20133, Milano, Italy; IIT Central Research Labs Genova, Istituto Italiano Tecnologia, 16163, Genova, Italy
| | | | - Fabio Vallone
- The BioRobotics Institute, Scuola Superiore Sant'Anna, I-56127, Pisa, Italy
| | - Jaume Del Valle
- Institute of Neurosciences and Department of Cell Biology, Physiology and Immunology, Universitat Autònoma De Barcelona, CIBERNED, 08193, Bellaterra, Spain
| | - Silvestro Micera
- The BioRobotics Institute, Scuola Superiore Sant'Anna, I-56127, Pisa, Italy; Translational Neural Engineering Laboratory, Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale De Lausanne, Lausanne, CH-1015, Switzerland.
| | - Xavier Navarro
- Institute of Neurosciences and Department of Cell Biology, Physiology and Immunology, Universitat Autònoma De Barcelona, CIBERNED, 08193, Bellaterra, Spain; Institut Guttmann De Neurorehabilitació, Badalona, Spain.
| |
Collapse
|
13
|
Zelechowski M, Valle G, Raspopovic S. A computational model to design neural interfaces for lower-limb sensory neuroprostheses. J Neuroeng Rehabil 2020; 17:24. [PMID: 32075654 PMCID: PMC7029520 DOI: 10.1186/s12984-020-00657-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 02/13/2020] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Leg amputees suffer the lack of sensory feedback from a prosthesis, which is connected to their low confidence during walking, falls and low mobility. Electrical peripheral nerve stimulation (ePNS) of upper-limb amputee's residual nerves has shown the ability to restore the sensations from the missing limb via intraneural (TIME) and epineural (FINE) neural interfaces. Physiologically plausible stimulation protocols targeting lower limb sciatic nerve hold promise to induce sensory feedback restoration that should facilitate close-to-natural sensorimotor integration and therefore walking corrections. The sciatic nerve, innervating the foot and lower leg, has very different dimensions in respect to upper-limb nerves. Therefore, there is a need to develop a computational model of its behavior in response to the ePNS. METHODS We employed a hybrid FEM-NEURON model framework for the development of anatomically correct sciatic nerve model. Based on histological images of two distinct sciatic nerve cross-sections, we reconstructed accurate FEM models for testing neural interfaces. Two different electrode types (based on TIME and FINE) with multiple active sites configurations were tested and evaluated for efficiency (selective recruitment of fascicles). We also investigated different policies of stimulation (monopolar and bipolar), as well as the optimal number of implants. Additionally, we optimized the existing simulation framework significantly reducing the computational load. RESULTS The main findings achieved through our modelling study include electrode manufacturing and surgical placement indications, together with beneficial stimulation policy of use. It results that TIME electrodes with 20 active sites are optimal for lower limb and the same number has been obtained for FINE electrodes. To interface the huge sciatic nerve, model indicates that 3 TIMEs is the optimal number of surgically implanted electrodes. Through the bipolar policy of stimulation, all studied configurations were gaining in the efficiency. Also, an indication for the optimized computation is given, which decreased the computation time by 80%. CONCLUSIONS This computational model suggests the optimal interfaces to use in human subjects with lower limb amputation, their surgical placement and beneficial bipolar policy of stimulation. It will potentially enable the clinical translation of the sensory neuroprosthetics towards the lower limb applications.
Collapse
Affiliation(s)
- Marek Zelechowski
- Center for medical Image Analysis & Navigation, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Giacomo Valle
- Neuroengineering Lab, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH, Zürich, Switzerland
| | - Stanisa Raspopovic
- Neuroengineering Lab, Department of Health Sciences and Technology, Institute for Robotics and Intelligent Systems, ETH, Zürich, Switzerland.
| |
Collapse
|
14
|
Davids M, Guérin B, Klein V, Schmelz M, Schad LR, Wald LL. Optimizing selective stimulation of peripheral nerves with arrays of coils or surface electrodes using a linear peripheral nerve stimulation metric. J Neural Eng 2020; 17:016029. [PMID: 31665707 DOI: 10.1088/1741-2552/ab52bd] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVE We present a PNS oracle, which solves these computation time and linearity problems and is, therefore, well-suited for fast optimization of voltage distributions in contact electrode arrays and current drive patterns in non-contact magnetic coil arrays. APPROACH The PNS oracle metric for a nerve fiber is computed from an electric field map using only linear operations (projection, differentiation, convolution, scaling). Due to its linearity, this PNS metric can be precomputed for a set of coil or electrode segments, allowing rapid PNS prediction and comparison of any possible coil or electrode stimulation configuration constructed from this set. The PNS oracle is closely related to the classical activating function and modified driving functions but is adjusted to better correlate with full neurodynamic modeling of myelinated mammalian nerves. MAIN RESULTS We validated the PNS oracle in three MRI gradient coils and two body models and found good correlation between the PNS oracle and the full neurodynamic modeling approach (R 2 > 0.995). Finally, we demonstrated its potential utility by optimizing the driving currents and voltages of arrays of 108 magnetic coils or 108 contact electrodes to selectively stimulate target nerves in the lower leg. SIGNIFICANCE Peripheral nerve stimulation (PNS) by electromagnetic fields can be accurately simulated using coupled electromagnetic and neurodynamic modeling. Such simulations are slow and non-linear in the electric field, which makes it difficult to iteratively optimize coil and electrode configurations or drive patterns aiming to avoid PNS or to initiate it for therapeutic purposes.
Collapse
Affiliation(s)
- Mathias Davids
- A A Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America. Harvard Medical School, Boston, Massachusetts, United States of America. Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | | | | | | | | |
Collapse
|
15
|
Lubba CH, Le Guen Y, Jarvis S, Jones NS, Cork SC, Eftekhar A, Schultz SR. PyPNS: Multiscale Simulation of a Peripheral Nerve in Python. Neuroinformatics 2019; 17:63-81. [PMID: 29948844 PMCID: PMC6394768 DOI: 10.1007/s12021-018-9383-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Bioelectronic Medicines that modulate the activity patterns on peripheral nerves have promise as a new way of treating diverse medical conditions from epilepsy to rheumatism. Progress in the field builds upon time consuming and expensive experiments in living organisms. To reduce experimentation load and allow for a faster, more detailed analysis of peripheral nerve stimulation and recording, computational models incorporating experimental insights will be of great help. We present a peripheral nerve simulator that combines biophysical axon models and numerically solved and idealised extracellular space models in one environment. We modelled the extracellular space as a three-dimensional resistive continuum governed by the electro-quasistatic approximation of the Maxwell equations. Potential distributions were precomputed in finite element models for different media (homogeneous, nerve in saline, nerve in cuff) and imported into our simulator. Axons, on the other hand, were modelled more abstractly as one-dimensional chains of compartments. Unmyelinated fibres were based on the Hodgkin-Huxley model; for myelinated fibres, we adapted the model proposed by McIntyre et al. in 2002 to smaller diameters. To obtain realistic axon shapes, an iterative algorithm positioned fibres along the nerve with a variable tortuosity fit to imaged trajectories. We validated our model with data from the stimulated rat vagus nerve. Simulation results predicted that tortuosity alters recorded signal shapes and increases stimulation thresholds. The model we developed can easily be adapted to different nerves, and may be of use for Bioelectronic Medicine research in the future.
Collapse
Affiliation(s)
- Carl H Lubba
- Department of Bioengineering, Imperial College London, South Kensington, London, SW7 2AZ, UK.
| | - Yann Le Guen
- Department of Bioengineering, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Sarah Jarvis
- Department of Bioengineering, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Nick S Jones
- Department of Mathematics, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Simon C Cork
- Department of Medicine, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Amir Eftekhar
- Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Simon R Schultz
- Department of Bioengineering, Imperial College London, South Kensington, London, SW7 2AZ, UK.
| |
Collapse
|
16
|
Gaillet V, Cutrone A, Artoni F, Vagni P, Mega Pratiwi A, Romero SA, Lipucci Di Paola D, Micera S, Ghezzi D. Spatially selective activation of the visual cortex via intraneural stimulation of the optic nerve. Nat Biomed Eng 2019; 4:181-194. [DOI: 10.1038/s41551-019-0446-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Accepted: 07/18/2019] [Indexed: 01/22/2023]
|
17
|
Kosta P, Warren DJ, Lazzi G. Selective stimulation of rat sciatic nerve using an array of mm-size magnetic coils: a simulation study. Healthc Technol Lett 2019; 6:70-75. [PMID: 31341631 PMCID: PMC6595541 DOI: 10.1049/htl.2018.5020] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Revised: 03/10/2019] [Accepted: 04/12/2019] [Indexed: 01/15/2023] Open
Abstract
This work proposes and computationally investigate the use of magnetic neural stimulation as an alternative to electrical stimulation to achieve selective activation of rat sciatic nerve. In particular, they assess the effectiveness of an array of small coils to obtain selective neural stimulation, as compared to a single coil. Specifically, an array of four mm-sized coils is used to stimulate rat sciatic nerve, targeting the regions of fascicles that are associated with different muscles of the leg. To evaluate the selectivity of activation, a three-dimensional heterogeneous multi-resolution nerve model is implemented using the impedance method for the computation of the magnetic and electric fields in the nerve. The performance metric ‘selectivity index’ is defined that measures the recruitment of the targeted region compared to other non-targeted regions of the nerve. The selectivity index takes values between −1 (least selective) and 1 (most selective). For each targeted region, a selectivity index of 0.75 or better is predicted for the proposed array configuration. The results suggest that an array of coils can provide superior spatial control of the electric field induced in the neural tissue compared to traditional extraneural electrode arrays, thus opening the possibility to applications where selective neurostimulation is of interest.
Collapse
Affiliation(s)
- Pragya Kosta
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | - David J Warren
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112, USA
| | - Gianluca Lazzi
- Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089, USA.,Department of Ophthalmology, University of Southern California, Los Angeles, CA 90033, USA
| |
Collapse
|
18
|
Paradigms for restoration of somatosensory feedback via stimulation of the peripheral nervous system. Clin Neurophysiol 2018; 129:851-862. [DOI: 10.1016/j.clinph.2017.12.027] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 12/05/2017] [Accepted: 12/13/2017] [Indexed: 02/08/2023]
|
19
|
Žužek MC, Rozman J, Pečlin P, Vrecl M, Frangež R. Analysis of compound action potentials elicited with specific current stimulating pulses in an isolated rat sciatic nerve. ACTA ACUST UNITED AC 2017; 62:37-48. [DOI: 10.1515/bmt-2015-0167] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2015] [Accepted: 01/26/2016] [Indexed: 11/15/2022]
Abstract
AbstractThe ability to selectively stimulate Aα, Aβ-fibers and Aδ-fibers in an isolated rat sciatic nerve (SNR) was assessed. The stimulus used was a current, biphasic pulse with a quasitrapezoidal cathodic phase and rectangular anodic phase where parameters were systematically varied: intensity of the cathodic phase (i
Collapse
|
20
|
Carboni C, Bisoni L, Carta N, Puddu R, Raspopovic S, Navarro X, Raffo L, Barbaro M. An integrated interface for peripheral neural system recording and stimulation: system design, electrical tests and in-vivo results. Biomed Microdevices 2016; 18:35. [PMID: 27007860 DOI: 10.1007/s10544-016-0043-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The prototype of an electronic bi-directional interface between the Peripheral Nervous System (PNS) and a neuro-controlled hand prosthesis is presented. The system is composed of 2 integrated circuits: a standard CMOS device for neural recording and a HVCMOS device for neural stimulation. The integrated circuits have been realized in 2 different 0.35μ m CMOS processes available from ams. The complete system incorporates 8 channels each including the analog front-end, the A/D conversion, based on a sigma delta architecture and a programmable stimulation module implemented as a 5-bit current DAC; two voltage boosters supply the output stimulation stage with a programmable voltage scalable up to 17V. Successful in-vivo experiments with rats having a TIME electrode implanted in the sciatic nerve were carried out, showing the capability of recording neural signals in the tens of microvolts, with a global noise of 7μ V r m s , and to selectively elicit the tibial and plantar muscles using different active sites of the electrode.
Collapse
|
21
|
Xiang Z, Liu J, Lee C. A flexible three-dimensional electrode mesh: An enabling technology for wireless brain-computer interface prostheses. MICROSYSTEMS & NANOENGINEERING 2016; 2:16012. [PMID: 31057819 PMCID: PMC6444742 DOI: 10.1038/micronano.2016.12] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2015] [Revised: 02/21/2016] [Accepted: 03/01/2016] [Indexed: 05/14/2023]
Abstract
The neural interface is a key component in wireless brain-computer prostheses. In this study, we demonstrate that a unique three-dimensional (3D) microneedle electrode on a flexible mesh substrate, which can be fabricated without complicated micromachining techniques, is conformal to the tissues with minimal invasiveness. Furthermore, we demonstrate that it can be applied to different functional layers in the nervous system without length limitation. The microneedle electrode is fabricated using drawing lithography technology from biocompatible materials. In this approach, the profile of a 3D microneedle electrode array is determined by the design of a two-dimensional (2D) pattern on the mask, which can be used to access different functional layers in different locations of the brain. Due to the sufficient stiffness of the electrode and the excellent flexibility of the mesh substrate, the electrode can penetrate into the tissue with its bottom layer fully conformal to the curved brain surface. Then, the exposed contact at the end of the microneedle electrode can successfully acquire neural signals from the brain.
Collapse
Affiliation(s)
- Zhuolin Xiang
- Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
- Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore, 28 Medical Drive, #05-COR, Singapore 117456, Singapore
- Center for Intelligent Sensors and MEMS, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
- NUS Suzhou Research Institute (NUSRI), Suzhou Industrial Park, Suzhou 215123, China
| | - Jingquan Liu
- National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Department of Micro/NanoElectronics, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Chengkuo Lee
- Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
- Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore, 28 Medical Drive, #05-COR, Singapore 117456, Singapore
- Center for Intelligent Sensors and MEMS, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
- NUS Suzhou Research Institute (NUSRI), Suzhou Industrial Park, Suzhou 215123, China
- ()
| |
Collapse
|
22
|
RamRakhyani AK, Kagan ZB, Warren DJ, Normann RA, Lazzi G. A μm-Scale Computational Model of Magnetic Neural Stimulation in Multifascicular Peripheral Nerves. IEEE Trans Biomed Eng 2015; 62:2837-49. [PMID: 26087483 DOI: 10.1109/tbme.2015.2446761] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
There has been recurring interest in using magnetic neural stimulation for implantable localized stimulation. However, the large stimulation voltages and energies necessary to evoke neuronal activity have tempered this interest. To investigate the potential of magnetic stimulation as a viable methodology and to provide the ability to investigate novel coil designs that can result in lower stimulation threshold voltages and energies, there is a need for a model that accurately predicts the magnetic field-tissue interaction that results in neuronal stimulation. In this study, we provide a computational framework to accurately estimate the stimulation threshold and have validated the model with in vivo magnetic stimulation experiments. To make such predictions, we developed a micrometer-resolution anatomically driven computational model of rat sciatic nerve and quantified the effect of tissue heterogeneity (i.e., fascicular organization, axon distribution, and density) and axonal membrane capacitance on the resulting threshold. Using the multiresolution impedance method, we computed the spatial-temporal distribution of the induced electric field in the nerve and applied this field to a Frankenhaeuser-Huxley axon model in NEURON to simulate the nonlinear mechanisms of the membrane channels. The computational model developed predicts the stimulation thresholds for four magnetic coil designs with different geometrical parameters within the 95% confidence interval (experiments count = 4) of measured in vivo stimulation thresholds for the rat sciatic nerve.
Collapse
|
23
|
Badia J, Raspopovic S, Carpaneto J, Micera S, Navarro X. Spatial and Functional Selectivity of Peripheral Nerve Signal Recording With the Transversal Intrafascicular Multichannel Electrode (TIME). IEEE Trans Neural Syst Rehabil Eng 2015; 24:20-7. [PMID: 26087496 DOI: 10.1109/tnsre.2015.2440768] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The selection of suitable peripheral nerve electrodes for biomedical applications implies a trade-off between invasiveness and selectivity. The optimal design should provide the highest selectivity for targeting a large number of nerve fascicles with the least invasiveness and potential damage to the nerve. The transverse intrafascicular multichannel electrode (TIME), transversally inserted in the peripheral nerve, has been shown to be useful for the selective activation of subsets of axons, both at inter- and intra-fascicular levels, in the small sciatic nerve of the rat. In this study we assessed the capabilities of TIME for the selective recording of neural activity, considering the topographical selectivity and the distinction of neural signals corresponding to different sensory types. Topographical recording selectivity was proved by the differential recording of CNAPs from different subsets of nerve fibers, such as those innervating toes 2 and 4 of the hindpaw of the rat. Neural signals elicited by sensory stimuli applied to the rat paw were successfully recorded. Signal processing allowed distinguishing three different types of sensory stimuli such as tactile, proprioceptive and nociceptive ones with high performance. These findings further support the suitability of TIMEs for neuroprosthetic applications, by exploiting the transversal topographical structure of the peripheral nerves.
Collapse
|
24
|
Pasquina PF, Perry BN, Miller ME, Ling GSF, Tsao JW. Recent advances in bioelectric prostheses. Neurol Clin Pract 2015; 5:164-170. [PMID: 29443190 DOI: 10.1212/cpj.0000000000000132] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Worldwide prevalence of amputation has created an increasing demand for improved upper and lower extremity prostheses. Current prosthetics are often uncomfortable and difficult to control and provide limited functional restoration. Moreover, the inability to normalize anthropomorphic biomechanics with a prosthesis increases one's risk of developing long-term health risks such as arthritis, skin breakdown, and pain. Recent advances in bionic prosthetic development hold great promise for rehabilitation and improving quality of life with limb loss. This brief review discusses the current state of advanced prostheses, the integration of robotics in the care of individuals with major limb amputation, and some innovative surgical techniques that are being explored for clinical feasibility.
Collapse
Affiliation(s)
- Paul F Pasquina
- Department of Physical Medicine & Rehabilitation (PFP), Center for Rehabilitation Sciences Research (PFP, JWT), and Department of Neurology (GSFL, JWT), Uniformed Services University of the Health Sciences, Bethesda, MD; Walter Reed National Military Medical Center (PFP, BNP, MEM, JWT), Bethesda, MD; and US Navy Bureau of Medicine and Surgery (JWT), Falls Church, VA
| | - Briana N Perry
- Department of Physical Medicine & Rehabilitation (PFP), Center for Rehabilitation Sciences Research (PFP, JWT), and Department of Neurology (GSFL, JWT), Uniformed Services University of the Health Sciences, Bethesda, MD; Walter Reed National Military Medical Center (PFP, BNP, MEM, JWT), Bethesda, MD; and US Navy Bureau of Medicine and Surgery (JWT), Falls Church, VA
| | - Matthew E Miller
- Department of Physical Medicine & Rehabilitation (PFP), Center for Rehabilitation Sciences Research (PFP, JWT), and Department of Neurology (GSFL, JWT), Uniformed Services University of the Health Sciences, Bethesda, MD; Walter Reed National Military Medical Center (PFP, BNP, MEM, JWT), Bethesda, MD; and US Navy Bureau of Medicine and Surgery (JWT), Falls Church, VA
| | - Geoffrey S F Ling
- Department of Physical Medicine & Rehabilitation (PFP), Center for Rehabilitation Sciences Research (PFP, JWT), and Department of Neurology (GSFL, JWT), Uniformed Services University of the Health Sciences, Bethesda, MD; Walter Reed National Military Medical Center (PFP, BNP, MEM, JWT), Bethesda, MD; and US Navy Bureau of Medicine and Surgery (JWT), Falls Church, VA
| | - Jack W Tsao
- Department of Physical Medicine & Rehabilitation (PFP), Center for Rehabilitation Sciences Research (PFP, JWT), and Department of Neurology (GSFL, JWT), Uniformed Services University of the Health Sciences, Bethesda, MD; Walter Reed National Military Medical Center (PFP, BNP, MEM, JWT), Bethesda, MD; and US Navy Bureau of Medicine and Surgery (JWT), Falls Church, VA
| |
Collapse
|
25
|
Maciejasz P, Badia J, Boretius T, Andreu D, Stieglitz T, Jensen W, Navarro X, Guiraud D. Delaying discharge after the stimulus significantly decreases muscle activation thresholds with small impact on the selectivity: an in vivo study using TIME. Med Biol Eng Comput 2015; 53:371-9. [PMID: 25652078 DOI: 10.1007/s11517-015-1244-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2014] [Accepted: 01/22/2015] [Indexed: 10/24/2022]
Abstract
The number of devices for electrical stimulation of nerve fibres implanted worldwide for medical applications is constantly increasing. Stimulation charge is one of the most important parameters of stimulation. High stimulation charge may cause tissue and electrode damage and also compromise the battery life of the electrical stimulators. Therefore, the objective of minimizing stimulation charge is an important issue. Delaying the second phase of biphasic stimulation waveform may decrease the charge required for fibre activation, but its impact on stimulation selectivity is not known. This information is particularly relevant when transverse intrafascicular multichannel electrode (TIME) is used, since it has been designed to provide for high selectivity. In this in vivo study, the rat sciatic nerve was electrically stimulated using monopolar and bipolar configurations with TIME. The results demonstrated that the inclusion of a 100-μs delay between the cathodic and the anodic phase of the stimulus allows to reduce charge requirements by around 30 %, while only slightly affecting stimulation selectivity. This study shows that adding a delay to the typical stimulation waveform significantly ([Formula: see text]) reduces the charge required for nerve fibres activation. Therefore, waveforms with the delayed discharge phase are more suitable for electrical stimulation of nerve fibres.
Collapse
Affiliation(s)
- Paweł Maciejasz
- DEMAR Team, LIRMM, INRIA, University of Montpellier 2, Montpellier, France,
| | | | | | | | | | | | | | | |
Collapse
|
26
|
Cutrone A, Del Valle J, Santos D, Badia J, Filippeschi C, Micera S, Navarro X, Bossi S. A three-dimensional self-opening intraneural peripheral interface (SELINE). J Neural Eng 2015; 12:016016. [PMID: 25605565 DOI: 10.1088/1741-2560/12/1/016016] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE In this study we present the development and testing in a rat model of the self-opening neural interface (SELINE), a novel flexible peripheral neural interface. APPROACH This polyimide-based electrode has a three-dimensional structure that provides an anchorage system to the nerve and confers stability after implant. This geometry has been achieved by means of the plastic deformation of polyimide. Mechanical and electrochemical characterizations have been performed to prove the integrity of the electrode with very good results. Functionality of SELINEs for fascicular stimulation has been tested during in vivo acute experiments in the rat. Chronic implants were made to test the biocompatibility of the device. MAIN RESULTS Results showed that SELINEs significantly improve mechanical anchorage to the nerve. Stimulation stability is considerably enhanced compared to common planar transversal electrodes and stimulation selectivity is increased for some motor fascicles. Chronic experimental results showed that SELINEs neither produce changes in the fascicular organization of sciatic nerves nor signs of nerve degeneration. SIGNIFICANCE The presented three-dimensional electrode provides an effective anchorage system to the nervous tissue that can improve the stability of the implant for acute and chronic studies.
Collapse
Affiliation(s)
- A Cutrone
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio 34, I-56025, Pontedera (PI), Italy
| | | | | | | | | | | | | | | |
Collapse
|
27
|
Abstract
Epidural electrical stimulation (EES) of lumbosacral segments can restore a range of movements after spinal cord injury. However, the mechanisms and neural structures through which EES facilitates movement execution remain unclear. Here, we designed a computational model and performed in vivo experiments to investigate the type of fibers, neurons, and circuits recruited in response to EES. We first developed a realistic finite element computer model of rat lumbosacral segments to identify the currents generated by EES. To evaluate the impact of these currents on sensorimotor circuits, we coupled this model with an anatomically realistic axon-cable model of motoneurons, interneurons, and myelinated afferent fibers for antagonistic ankle muscles. Comparisons between computer simulations and experiments revealed the ability of the model to predict EES-evoked motor responses over multiple intensities and locations. Analysis of the recruited neural structures revealed the lack of direct influence of EES on motoneurons and interneurons. Simulations and pharmacological experiments demonstrated that EES engages spinal circuits trans-synaptically through the recruitment of myelinated afferent fibers. The model also predicted the capacity of spatially distinct EES to modulate side-specific limb movements and, to a lesser extent, extension versus flexion. These predictions were confirmed during standing and walking enabled by EES in spinal rats. These combined results provide a mechanistic framework for the design of spinal neuroprosthetic systems to improve standing and walking after neurological disorders.
Collapse
|
28
|
Huggins JE, Guger C, Allison B, Anderson CW, Batista A, Brouwer AM(AM, Brunner C, Chavarriaga R, Fried-Oken M, Gunduz A, Gupta D, Kübler A, Leeb R, Lotte F, Miller LE, Müller-Putz G, Rutkowski T, Tangermann M, Thompson DE. Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future. BRAIN-COMPUTER INTERFACES 2014; 1:27-49. [PMID: 25485284 PMCID: PMC4255956 DOI: 10.1080/2326263x.2013.876724] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The Fifth International Brain-Computer Interface (BCI) Meeting met June 3-7th, 2013 at the Asilomar Conference Grounds, Pacific Grove, California. The conference included 19 workshops covering topics in brain-computer interface and brain-machine interface research. Topics included translation of BCIs into clinical use, standardization and certification, types of brain activity to use for BCI, recording methods, the effects of plasticity, special interest topics in BCIs applications, and future BCI directions. BCI research is well established and transitioning to practical use to benefit people with physical impairments. At the same time, new applications are being explored, both for people with physical impairments and beyond. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and high-lighting important issues for future research and development.
Collapse
Affiliation(s)
- Jane E. Huggins
- Department of Physical Medicine and Rehabilitation, Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States, 325 East Eisenhower, Room 3017; Ann Arbor, Michigan 48108-5744, 734-936-7177
| | - Christoph Guger
- Christoph Guger, g.tec medical engineering GmbH/Guger Technologies OG, Austria, Sierningstrasse 14, 4521 Schiedlberg, Austria, +43725122240-0
| | - Brendan Allison
- University of California at San Diego, La Jolla, CA 91942 (415) 490 7551
| | - Charles W. Anderson
- Department of Computer Science, Colorado State University, Fort Collins, CO 80523; telephone: 970-491-7491
| | - Aaron Batista
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 3501 5th Av, BST3 4074; Pittsburgh, PA 15261; (412) 383-5394
| | - Anne-Marie (A.-M.) Brouwer
- The Netherlands Organization for Applied Scientific Research; P.O. Box 23/Kampweg 5, 3769 ZG Soesterberg, the Netherlands, ++31 (0)888 665960
| | - Clemens Brunner
- Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz University of Technology, Inffeldgasse 13/4, 8010; Graz, Austria
| | - Ricardo Chavarriaga
- Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Switzerland, EPFL-STI-CNBI, Station 11, 1005 Lausanne, Switzerland; Telephone: +41 21 693 6968
| | - Melanie Fried-Oken
- Oregon Health & Science University; Institute on Development & Disability; 707 SW Gaines Street; Portland, Oregon, United States; O: 503.494.7587, F: 503.494.6868
| | - Aysegul Gunduz
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA; Phone: +1 (352) 273 6877; Fax: +1 (352) 273 9221
| | - Disha Gupta
- Dept. of Neurology, Albany Medical College/Brain Computer Interfacing Lab, Wadsworth Center, NY State Dept. of Health, Albany, New York, USA
| | - Andrea Kübler
- Institute of Psychology, University of Würzburg; Marcusstr.9-11; 97070 Würzburg, Germany. Phone.: 0049 931 31 80179; Fax: 0049 931 31 82424
| | - Robert Leeb
- Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Switzerland
| | - Fabien Lotte
- Inria Bordeaux Sud-Ouest/LaBRI, 200 avenue de la vieille tour, 33405, Talence Cedex, France, Tel: +33 5 24 57 41 26
| | - Lee E. Miller
- Departments of Physiology, Physical Medicine and Rehab, and Biomedical Engineering; Feinberg School of Medicine; Northwestern University; Chicago, Illinois, United States; Ward 5-01; 303 East Chicago Avenue; Chicago, Illinois 60611; Phone: (312) 503 – 8677; Fax: (312) 503 – 5101
| | - Gernot Müller-Putz
- Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz University of Technology, Inffeldgasse 13/4, 8010; Graz, Austria
| | - Tomasz Rutkowski
- Life Science Center of TARA, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8577 Japan; TEL: +81 (0)29-853-6261
| | - Michael Tangermann
- Excellence Cluster BrainLinks-BrainTools, Dept. Computer Science, University of Freiburg, Freiburg, Germany, Albertstr. 23; 79104 Freiburg; Germany; Phone: +49.(0)761.2038423, Fax : +49.(0)761.2038417
| | - David Edward Thompson
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, United States, 2800 Plymouth Road, Bdlg 26 Rm G06W-B; Ann Arbor, MI 48109; 734-763-7104
| |
Collapse
|
29
|
Bologna LL, Pinoteau J, Passot JB, Garrido JA, Vogel J, Vidal ER, Arleo A. A closed-loop neurobotic system for fine touch sensing. J Neural Eng 2013; 10:046019. [DOI: 10.1088/1741-2560/10/4/046019] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
|
30
|
Raspopovic S, Capogrosso M, Badia J, Navarro X, Micera S. Correction to “Experimental Validation of a Hybrid Computational Model for Selective Stimulation Using Transverse Intrafascicular Multichannel Electrodes” [May 12 395-404]. IEEE Trans Neural Syst Rehabil Eng 2012. [DOI: 10.1109/tnsre.2012.2207189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
|