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Parastarfeizabadi M, Sillitoe RV, Kouzani AZ. Multi-disease Deep Brain Stimulation. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2020; 8:216933-216947. [PMID: 33381359 PMCID: PMC7771650 DOI: 10.1109/access.2020.3041942] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Current closed-loop deep brain stimulation (DBS) devices can generally tackle one disorder. This paper presents the design and evaluation of a multi-disease closed-loop DBS device that can sense multiple brain biomarkers, detect a disorder, and adaptively deliver electrical stimulation pulses based on the disease state. The device consists of: (i) a neural sensor, (ii) a controller involving a feature extractor, a disease classifier, and a control strategy, and (iii) neural stimulator. The neural sensor records and processes local field potentials and spikes from within the brain using two low-frequency and high-frequency channels. The feature extractor digitally processes the output of the neural sensor, and extracts five potential biomarkers: alpha, beta, slow gamma, high-frequency oscillations, and spikes. The disease classifier identifies the type of the neurological disorder through an analysis of the biomarkers' amplitude features. The control strategy considers the disease state and supplies the stimulation settings to the neural stimulator. Both the disease classifier and control strategy are based on fuzzy algorithms. The neural stimulator generates electrical stimulation pulses according to the control commands, and delivers them to the target area of the brain. The device can generate current stimulation pulses with specific amplitude, frequency, and duration. The fabricated device has the maximum radius of 15 mm. Its total weight including the circuit board, battery and battery holder is 5.1 g. The performance of the integrated device has been evaluated through six bench and in-vitro experiments. The experimental results are presented, analyzed, and discussed. Six bench and in-vitro experiments were conducted using sinusoidal, normal pre-recorded, and diseased neural signals representing normal, epilepsy, depression and PD conditions. The results obtained through these tests indicate the successful neural sensing, classification, control, and neural stimulating performance.
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Affiliation(s)
| | - Roy V. Sillitoe
- Department of Pathology and Immunology, Department of Neuroscience, Jan and Dan Duncan Neurological Research Institute, and Baylor College of Medicine, Texas Children’s Hospital, Houston, TX 77030, USA
| | - Abbas Z. Kouzani
- School of Engineering, Deakin University, Geelong, VIC 3216, Australia
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Miterko LN, Baker KB, Beckinghausen J, Bradnam LV, Cheng MY, Cooperrider J, DeLong MR, Gornati SV, Hallett M, Heck DH, Hoebeek FE, Kouzani AZ, Kuo SH, Louis ED, Machado A, Manto M, McCambridge AB, Nitsche MA, Taib NOB, Popa T, Tanaka M, Timmann D, Steinberg GK, Wang EH, Wichmann T, Xie T, Sillitoe RV. Consensus Paper: Experimental Neurostimulation of the Cerebellum. CEREBELLUM (LONDON, ENGLAND) 2019; 18:1064-1097. [PMID: 31165428 PMCID: PMC6867990 DOI: 10.1007/s12311-019-01041-5] [Citation(s) in RCA: 95] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The cerebellum is best known for its role in controlling motor behaviors. However, recent work supports the view that it also influences non-motor behaviors. The contribution of the cerebellum towards different brain functions is underscored by its involvement in a diverse and increasing number of neurological and neuropsychiatric conditions including ataxia, dystonia, essential tremor, Parkinson's disease (PD), epilepsy, stroke, multiple sclerosis, autism spectrum disorders, dyslexia, attention deficit hyperactivity disorder (ADHD), and schizophrenia. Although there are no cures for these conditions, cerebellar stimulation is quickly gaining attention for symptomatic alleviation, as cerebellar circuitry has arisen as a promising target for invasive and non-invasive neuromodulation. This consensus paper brings together experts from the fields of neurophysiology, neurology, and neurosurgery to discuss recent efforts in using the cerebellum as a therapeutic intervention. We report on the most advanced techniques for manipulating cerebellar circuits in humans and animal models and define key hurdles and questions for moving forward.
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Affiliation(s)
- Lauren N Miterko
- Department of Pathology and Immunology, Department of Neuroscience, Program in Developmental Biology, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute of Texas Children's Hospital, 1250 Moursund Street, Suite 1325, Houston, TX, 77030, USA
| | - Kenneth B Baker
- Neurological Institute, Department of Neurosurgery, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
| | - Jaclyn Beckinghausen
- Department of Pathology and Immunology, Department of Neuroscience, Program in Developmental Biology, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute of Texas Children's Hospital, 1250 Moursund Street, Suite 1325, Houston, TX, 77030, USA
| | - Lynley V Bradnam
- Department of Exercise Science, Faculty of Science, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand
| | - Michelle Y Cheng
- Department of Neurosurgery, Stanford University School of Medicine, 1201 Welch Road, MSLS P352, Stanford, CA, 94305-5487, USA
| | - Jessica Cooperrider
- Neurological Institute, Department of Neurosurgery, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
| | - Mahlon R DeLong
- Department of Neurology, Emory University, Atlanta, GA, 30322, USA
| | - Simona V Gornati
- Department of Neuroscience, Erasmus Medical Center, 3015 AA, Rotterdam, Netherlands
| | - Mark Hallett
- Human Motor Control Section, NINDS, NIH, Building 10, Room 7D37, 10 Center Dr MSC 1428, Bethesda, MD, 20892-1428, USA
| | - Detlef H Heck
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, 855 Monroe Ave, Memphis, TN, 38163, USA
| | - Freek E Hoebeek
- Department of Neuroscience, Erasmus Medical Center, 3015 AA, Rotterdam, Netherlands
- NIDOD Department, Wilhelmina Children's Hospital, University Medical Center Utrecht Brain Center, Utrecht, Netherlands
| | - Abbas Z Kouzani
- School of Engineering, Deakin University, Geelong, VIC, 3216, Australia
| | - Sheng-Han Kuo
- Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, 10032, USA
| | - Elan D Louis
- Department of Neurology, Yale School of Medicine, Department of Chronic Disease Epidemiology, Yale School of Public Health, Center for Neuroepidemiology and Clinical Research, Yale School of Medicine, Yale University, New Haven, CT, 06520, USA
| | - Andre Machado
- Neurological Institute, Department of Neurosurgery, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH, 44195, USA
| | - Mario Manto
- Service de Neurologie, CHU-Charleroi, 6000, Charleroi, Belgium
- Service des Neurosciences, Université de Mons, 7000, Mons, Belgium
| | - Alana B McCambridge
- Graduate School of Health, Physiotherapy, University of Technology Sydney, PO Box 123, Broadway, Sydney, NSW, 2007, Australia
| | - Michael A Nitsche
- Department of Psychology and Neurosiences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
- Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | | | - Traian Popa
- Human Motor Control Section, NINDS, NIH, Building 10, Room 7D37, 10 Center Dr MSC 1428, Bethesda, MD, 20892-1428, USA
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Ecole Polytechnique Federale de Lausanne (EPFL), Sion, Switzerland
| | - Masaki Tanaka
- Department of Physiology, Hokkaido University School of Medicine, Sapporo, 060-8638, Japan
| | - Dagmar Timmann
- Department of Neurology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Gary K Steinberg
- Department of Neurosurgery, Stanford University School of Medicine, 1201 Welch Road, MSLS P352, Stanford, CA, 94305-5487, USA
- R281 Department of Neurosurgery, Stanfod University School of Medicine, 300 Pasteur Drive, Stanford, CA, 94305, USA
| | - Eric H Wang
- Department of Neurosurgery, Stanford University School of Medicine, 1201 Welch Road, MSLS P352, Stanford, CA, 94305-5487, USA
| | - Thomas Wichmann
- Department of Neurology, Emory University, Atlanta, GA, 30322, USA
- Yerkes National Primate Research Center, Emory University, Atlanta, GA, 30322, USA
| | - Tao Xie
- Department of Neurology, University of Chicago, 5841 S. Maryland Avenue, MC 2030, Chicago, IL, 60637-1470, USA
| | - Roy V Sillitoe
- Department of Pathology and Immunology, Department of Neuroscience, Program in Developmental Biology, Baylor College of Medicine, Jan and Dan Duncan Neurological Research Institute of Texas Children's Hospital, 1250 Moursund Street, Suite 1325, Houston, TX, 77030, USA.
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Adams SD, Bennet KE, Tye SJ, Berk M, Kouzani AZ. Development of a miniature device for emerging deep brain stimulation paradigms. PLoS One 2019; 14:e0212554. [PMID: 30789946 PMCID: PMC6383994 DOI: 10.1371/journal.pone.0212554] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Accepted: 02/05/2019] [Indexed: 11/18/2022] Open
Abstract
Deep brain stimulation (DBS) is a neuromodulatory approach for treatment of several neurological and psychiatric disorders. A new focus on optimising the waveforms used for stimulation is emerging regarding the mechanism of DBS treatment. Many existing DBS devices offer only a limited set of predefined waveforms, mainly rectangular, and hence are inapt for exploring the emerging paradigm. Advances in clinical DBS are moving towards incorporating new stimulation parameters, yet we remain limited in our capacity to test these in animal models, arguably a critical first step. Accordingly, there is a need for the development of new miniature, low-power devices to enable investigation into the new DBS paradigms in preclinical settings. The ideal device would allow for flexibility in the stimulation waveforms, while remaining suitable for chronic, tetherless, biphasic deep brain stimulation. In this work, we elucidate several key parameters in a DBS system, identify gaps in existing solutions, and propose a new device to support preclinical DBS. The device allows for a high degree of flexibility in the output waveform with easily altered shape, frequency, pulse-width and amplitude. The device is suitable for both traditional and modern stimulation schemes, including those using non-rectangular waveforms, as well as delayed feedback schemes. The device incorporates active charge balancing to ensure safe operation, and allows for simple production of custom biphasic waveforms. This custom waveform output is unique in the field of preclinical DBS devices, and could be advantageous in performing future DBS studies investigating new treatment paradigms. This tetherless device can be easily and comfortably carried by an animal in a back-mountable configuration. The results of in-vitro tests are presented and discussed.
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Affiliation(s)
- Scott D. Adams
- Deakin University, School of Engineering, Geelong, Victoria, Australia
| | - Kevin E. Bennet
- Division of Engineering, Mayo Clinic, Rochester, MN, United States of America
| | - Susannah J. Tye
- Queensland Brain Institute, the University of Queensland, St Lucia QLD, Australia
| | - Michael Berk
- Deakin University, School of Medicine, IMPACT SRC, Barwon Health, Geelong, Victoria, Australia
| | - Abbas Z. Kouzani
- Deakin University, School of Engineering, Geelong, Victoria, Australia
- * E-mail:
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Parastarfeizabadi M, Kouzani AZ, Beckinghausen J, Lin T, Sillitoe RV. A Programmable Multi-biomarker Neural Sensor for Closed-loop DBS. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2018; 7:230-244. [PMID: 30976472 PMCID: PMC6453143 DOI: 10.1109/access.2018.2885336] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Most of the current closed-loop DBS devices use a single biomarker in their feedback loop which may limit their performance and applications. This paper presents design, fabrication, and validation of a programmable multi-biomarker neural sensor which can be integrated into closed-loop DBS devices. The device is capable of sensing a combination of low-frequency (7-45 Hz), and high-frequency (200-1000 Hz) neural signals. The signals can be amplified with a digitally programmable gain within the range 50-100 dB. The neural signals can be stored into a local memory for processing and validation. The sensing and storage functions are implemented via a combination of analog and digital circuits involving preamplifiers, filters, programmable post-amplifiers, microcontroller, digital potentiometer, and flash memory. The device is fabricated, and its performance is validated through: (i) bench tests using sinusoidal and pre-recorded neural signals, (ii) in-vitro tests using pre-recorded neural signals in saline solution, and (iii) in-vivo tests by recording neural signals from freely-moving laboratory mice. The animals were implanted with a PlasticsOne electrode, and recording was conducted after recovery from the electrode implantation surgery. The experimental results are presented and discussed confirming the successful operation of the device. The size and weight of the device enable tetherless back-mountable use in pre-clinical trials.
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Affiliation(s)
| | - Abbas Z. Kouzani
- School of Engineering, Deakin University, Geelong, VIC 3216, Australia
| | - Jaclyn Beckinghausen
- Department of Pathology and Immunology, Department of Neuroscience, and Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, 1250 Moursund Street, Suite 1325, Houston Texas 77030, USA
| | - Tao Lin
- Department of Pathology and Immunology, and Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, 1250 Moursund Street, Suite 1325, Houston Texas 77030, USA
| | - Roy V. Sillitoe
- Department of Pathology and Immunology, Department of Neuroscience, Program in Developmental Biology, Baylor College of Medicine, and Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, 1250 Moursund Street, Suite 1325, Houston Texas 77030, USA
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Adams SD, Kouzani AZ, Tye SJ, Bennet KE, Berk M. An investigation into closed-loop treatment of neurological disorders based on sensing mitochondrial dysfunction. J Neuroeng Rehabil 2018; 15:8. [PMID: 29439744 PMCID: PMC5811973 DOI: 10.1186/s12984-018-0349-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Accepted: 02/05/2018] [Indexed: 12/14/2022] Open
Abstract
Dynamic feedback based closed-loop medical devices offer a number of advantages for treatment of heterogeneous neurological conditions. Closed-loop devices integrate a level of neurobiological feedback, which allows for real-time adjustments to be made with the overarching aim of improving treatment efficacy and minimizing risks for adverse events. One target which has not been extensively explored as a potential feedback component in closed-loop therapies is mitochondrial function. Several neurodegenerative and psychiatric disorders including Parkinson's disease, Major Depressive disorder and Bipolar disorder have been linked to perturbations in the mitochondrial respiratory chain. This paper investigates the potential to monitor this mitochondrial function as a method of feedback for closed-loop neuromodulation treatments. A generic model of the closed-loop treatment is developed to describe the high-level functions of any system designed to control neural function based on mitochondrial response to stimulation, simplifying comparison and future meta-analysis. This model has four key functional components including: a sensor, signal manipulator, controller and effector. Each of these components are described and several potential technologies for each are investigated. While some of these candidate technologies are quite mature, there are still technological gaps remaining. The field of closed-loop medical devices is rapidly evolving, and whilst there is a lot of interest in this area, widespread adoption has not yet been achieved due to several remaining technological hurdles. However, the significant therapeutic benefits offered by this technology mean that this will be an active area for research for years to come.
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Affiliation(s)
- Scott D. Adams
- School of Engineering, Deakin University, Geelong, VIC 3216 Australia
| | - Abbas Z. Kouzani
- School of Engineering, Deakin University, Geelong, VIC 3216 Australia
| | - Susannah J. Tye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905 USA
| | - Kevin E. Bennet
- Division of Engineering, Mayo Clinic, Rochester, MN 55905 USA
| | - Michael Berk
- School of Medicine, Deakin University, Waurn Ponds, VIC 3216 Australia
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