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Golabek J, Schiefer M, Wong JK, Saxena S, Patrick E. Artificial neural network-based rapid predictor of biological nerve fiber activation for DBS applications. J Neural Eng 2023; 20. [PMID: 36599158 DOI: 10.1088/1741-2552/acb016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 01/04/2023] [Indexed: 01/06/2023]
Abstract
Objective.Computational models are powerful tools that can enable the optimization of deep brain stimulation (DBS). To enhance the clinical practicality of these models, their computational expense and required technical expertise must be minimized. An important aspect of DBS models is the prediction of neural activation in response to electrical stimulation. Existing rapid predictors of activation simplify implementation and reduce prediction runtime, but at the expense of accuracy. We sought to address this issue by leveraging the speed and generalization abilities of artificial neural networks (ANNs) to create a novel predictor of neural fiber activation in response to DBS.Approach.We developed six variations of an ANN-based predictor to predict the response of individual, myelinated axons to extracellular electrical stimulation. ANNs were trained using datasets generated from a finite-element model of an implanted DBS system together with multi-compartment cable models of axons. We evaluated the ANN-based predictors using three white matter pathways derived from group-averaged connectome data within a patient-specific tissue conductivity field, comparing both predicted stimulus activation thresholds and pathway recruitment across a clinically relevant range of stimulus amplitudes and pulse widths.Main results.The top-performing ANN could predict the thresholds of axons with a mean absolute error (MAE) of 0.037 V, and pathway recruitment with an MAE of 0.079%, across all parameters. The ANNs reduced the time required to predict the thresholds of 288 axons by four to five orders of magnitude when compared to multi-compartment cable models.Significance.We demonstrated that ANNs can be fast, accurate, and robust predictors of neural activation in response to DBS.
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Affiliation(s)
- Justin Golabek
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States of America
| | - Matthew Schiefer
- Malcom Randall Department of Veterans Affairs Medical Center, Gainesville, FL, United States of America
| | - Joshua K Wong
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States of America
| | - Shreya Saxena
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States of America
| | - Erin Patrick
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States of America
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Silveira C, Khushaba RN, Brunton E, Nazarpour K. Spatio-temporal feature extraction in sensory electroneurographic signals. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2022; 380:20210268. [PMID: 35658682 PMCID: PMC9289791 DOI: 10.1098/rsta.2021.0268] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Accepted: 11/08/2021] [Indexed: 06/15/2023]
Abstract
The recording and analysis of peripheral neural signal can provide insight for various prosthetic and bioelectronics medicine applications. However, there are few studies that investigate how informative features can be extracted from population activity electroneurographic (ENG) signals. In this study, five feature extraction frameworks were implemented on sensory ENG datasets and their classification performance was compared. The datasets were collected in acute rat experiments where multi-channel nerve cuffs recorded from the sciatic nerve in response to proprioceptive stimulation of the hindlimb. A novel feature extraction framework, which incorporates spatio-temporal focus and dynamic time warping, achieved classification accuracies above 90% while keeping a low computational cost. This framework outperformed the remaining frameworks tested in this study and has improved the discrimination accuracy of the sensory signals. Thus, this study has extended the tools available to extract features from sensory population activity ENG signals. This article is part of the theme issue 'Advanced neurotechnologies: translating innovation for health and well-being'.
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Affiliation(s)
- C. Silveira
- School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - R. N. Khushaba
- Australian Center for Field Robotics, The University of Sydney, New South Wales 2006, Australia
| | - E. Brunton
- National Vision Research Institute, Australian College of Optometry, Carlton, Victoria 3053, Australia
- Department of Optometry and Vision Sciences, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Parkville, Victoria 3010, Australia
| | - K. Nazarpour
- Edinburgh Neuroprosthetics Laboratory, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK
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Dupan S, McNeill Z, Sarda E, Brunton E, Nazarpour K. How fast is too fast? Boundaries to the perception of electrical stimulation of peripheral nerves. IEEE Trans Neural Syst Rehabil Eng 2022; 30:782-788. [PMID: 35271444 DOI: 10.1109/tnsre.2022.3158067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Transcutaneous electrical stimulation is a promising technique for providing prosthetic hand users with information about sensory events. However, questions remain over how to design the stimulation paradigms to provide users the best opportunity to discriminate these events. Here, we investigate if the refractory period influences how the amplitude of the applied stimulus is perceived. Twenty participants completed a two-alternative forced choice experiment. We delivered two stimuli spaced between 250 ms to 450 ms apart (inter-stimulus-interval, isi). The participants reported which stimulus they perceived as strongest. Each stimulus consisted of either a single or paired pulse delivered transcutaneously. The inter-pulse interval (ipi) for the paired pulse stimuli varied between 6 and 10 ms. We found paired pulses with an ipi of 6 ms were perceived stronger than a single pulse less often than paired pulses with an ipi of 8 ms (p = 0.001) or 10 ms (p < 0.0001). Additionally, we found when the isi was 250 ms, participants were less likely to identify the paired pulse as strongest, than when the isi was 350 or 450 ms. This study emphasizes the importance of basing stimulation paradigms on the underlying neural physiology. The results indicate there is an upper limit to the commonly accepted notion that higher stimulation frequencies lead to stronger perception. If frequency is to be used to encode sensory events, then the results suggest stimulus paradigms should be designed using frequencies below 125 Hz.
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Pena AE, Abbas JJ, Jung R. Channel-hopping during surface electrical neurostimulation elicits selective, comfortable, distally referred sensations. J Neural Eng 2021; 18. [PMID: 33770781 DOI: 10.1088/1741-2552/abf28c] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 03/23/2021] [Indexed: 11/12/2022]
Abstract
Objective.Lack of sensation from a hand or prosthesis can result in substantial functional deficits. Surface electrical stimulation of the peripheral nerves is a promising non-invasive approach to restore lost sensory function. However, the utility of standard surface stimulation methods has been hampered by localized discomfort caused by unintended activation of afferents near the electrodes and limited ability to specifically target underlying neural tissue. The objectives of this work were to develop and evaluate a novel channel-hopping interleaved pulse scheduling (CHIPS) strategy for surface stimulation that is designed to activate deep nerves while reducing activation of fibers near the electrodes.Approach.The median nerve of able-bodied subjects was activated by up to two surface stimulating electrode pairs placed around their right wrist. Subjects received biphasic current pulses either from one electrode pair at a time (single-channel), or interleaved between two electrode pairs (multi-channel). Percept thresholds were characterized for five pulse durations under each approach, and psychophysical questionnaires were used to interrogate the perceived modality, quality and location of evoked sensations.Main results.Stimulation with CHIPS elicited enhanced tactile percepts that were distally referred, while avoiding the distracting sensations and discomfort associated with localized charge densities. These effects were reduced after introduction of large delays between interleaved pulses.Significance.These findings demonstrate that our pulse scheduling strategy can selectively elicit referred sensations that are comfortable, thus overcoming the primary limitations of standard surface stimulation methods. Implementation of this strategy with an array of spatially distributed electrodes may allow for rapid and effective stimulation fitting. The ability to elicit comfortable and referred tactile percepts may enable the use of this neurostimulation strategy to provide meaningful and intuitive feedback from a prosthesis, enhance tactile feedback after sensory loss secondary to nerve damage, and deliver non-invasive stimulation therapies to treat various pain conditions.
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Affiliation(s)
- A E Pena
- Department of Biomedical Engineering, Florida International University, Miami, FL, United States of America
| | - J J Abbas
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, United States of America
| | - R Jung
- Department of Biomedical Engineering, Florida International University, Miami, FL, United States of America
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Dupan SSG, McNeill Z, Brunton E, Nazarpour K. Temporal Modulation of Transcutaneous Electrical Nerve Stimulation Influences Sensory Perception. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3885-3888. [PMID: 33018849 DOI: 10.1109/embc44109.2020.9176472] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The incorporation of sensory feedback in prosthetics can lead to a range of benefits, such as improved hand control, increased prosthesis embodiment, and the reduction of phantom limb pain. However, the creation of reliable sensory feedback is complicated by the temporal modulation of the nervous system. Sensory fibres in the hand are primed to react to changing conditions, firing when discrete mechanical events occur. In this study, we investigate the minimal possible stimulation needed to distinguish different sensory patterns that can be used to indicate events. We presented a two-alternative forced-choice task of transcutaneous electrical nerve stimuli to 10 participants. The results showed that different stimuli can be distinguished when double pulses have an inter-stimulus-interval of 10 ms. Additionally, providing a pause of at least 350 ms between stimuli increases the discrimination of the perception. These results suggest that humans can distinguish different patterns of transcutaneous electrical nerve stimulation with as little as two stimuli, illustrating the possibility of providing event-related stimulation.
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Williams I, Brunton E, Rapeaux A, Liu Y, Luan S, Nazarpour K, Constandinou T. SenseBack - An Implantable System for Bidirectional Neural Interfacing. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2020; PP:1079-1087. [PMID: 32915746 DOI: 10.1109/tbcas.2020.3022839] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Chronic in-vivo neurophysiology experiments require highly miniaturized, remotely powered multi-channel neural interfaces which are currently lacking in power or flexibility post implantation. To resolve this problem we present the SenseBack system, a post-implantation reprogrammable wireless 32-channel bidirectional neural interfacing device that can enable chronic peripheral electrophysiology experiments in freely behaving small animals. The large number of channels for a peripheral neural interface, coupled with fully implantable hardware and complete software flexibility enable complex in-vivo studies where the system can adapt to evolving study needs as they arise. In complementary \textit{ex-vivo} and \textit{in-vivo} preparations, we demonstrate that this system can record neural signals and perform high-voltage, bipolar stimulation on any channel. In addition, we demonstrate transcutaneous power delivery and Bluetooth 5 data communication with a PC. The SenseBack system is capable of stimulation on any channel with 20 V of compliance and up to 315 A of current, and highly configurable recording with per-channel adjustable gain and filtering with 8 sets of 10-bit ADCs to sample data at 20 kHz for each channel. To our knowledge this is the first such implantable research platform offering this level of performance and flexibility post-implantation (including complete reprogramming even after encapsulation) for small animal electrophysiology. Here we present initial acute trials, demonstrations and progress towards a system that we expect to enable a wide range of electrophysiology experiments in freely behaving animals.
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Silveira C, Brunton E, Escobedo-Cousin E, Gupta G, Whittaker R, O'Neill A, Nazarpour K. W:Ti Flexible Transversal Electrode Array for Peripheral Nerve Stimulation: A Feasibility Study. IEEE Trans Neural Syst Rehabil Eng 2020; 28:2136-2143. [PMID: 32790633 DOI: 10.1109/tnsre.2020.3014812] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The development of hardware for neural interfacing remains a technical challenge. We introduce a flexible, transversal intraneural tungsten:titanium electrode array for acute studies. We characterize the electrochemical properties of this new combination of tungsten and titanium using cyclic voltammetry and electrochemical impedance spectroscopy. With an in-vivo rodent study, we show that the stimulation of peripheral nerves with this electrode array is possible and that more than half of the electrode contacts can yield a stimulation selectivity index of 0.75 or higher at low stimulation currents. This feasibility study paves the way for the development of future cost-effective and easy-to-fabricate neural interfacing electrodes for acute settings, which ultimately can inform the development of technologies that enable bi-directional communication with the human nervous system.
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