Download or read book Machine Learning to Optimize Embedded Adaptive Deep Brain Stimulation written by Benjamin Isaac Ferleger and published by . This book was released on 2020 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on the development and application of novel machine learning approaches to the problem of optimization in adaptive deep brain stimulation. As brain-computer and brain-machine interfacing has rapidly developed in the past few years, attention in the relevant research has shifted from proof-of-concept to proof-of-feasibility. One of the first and, therefore, best-developed neurotechnologies is deep brain stimulation (DBS). DBS is a surgical intervention prescribed for several treatment-refractory neurological conditions. First, a stimulating electrode is chronically implanted into a condition-specific deep brain structure. The parameters of the stimulation provided by this electrode are then set bya clinician. Stimulation remains at these parameters continuously unless a patient actively chooses to disable their treatment. As has been repeatedly demonstrated, DBS is a safe and effective treatment for a number of movement disorders and is under active investigation for potential use in several psychiatric conditions.DBS, however, is not a panacea. Battery replacement requires a revision surgery, and even rechargeable systems0́9 batteries must generally be replaced at least once within a device's lifetime. Additionally, DBS therapy is associated with a number of unpleasant and sometimes dangerous side effects. These side effects can range from transient paresthesias to episodes of depression and mania, and are broadly correlated with high levels of stimulation over long periods of time. In addition to concerns over battery life and side effects, the programming procedure for DBS is based primarily on a back-and-forth between clinicians and patients in a clinical setting. If we define "optimal" treatment as the most complete suppression of symptoms with the least manifestation of side effects, then achieving the corresponding settings is the goal of this procedure. The time consuming nature of this procedure, when considered in the context of clinical time constraints and patient fatigue, means that the parameters selected are far more likely to be the first passable setting than the truly optimal one. Patients are generally given the ability to disable their stimulation or select from a small range of amplitudes, but cannot actively reprogram their devices outside of a clinical setting. One technique with the potential to alleviate concerns about side effects and battery life is adaptive deep brain stimulation (aDBS). aDBS refers to any method that uses feedback on a patient's state to modulate stimulation parameters in real time. This feedback could come in the form of gyroscope and accelerometer data in the case of movement disorders, or could be derived from neural signals that are correlated with the onset of symptoms. These signals are then processed and meaningful features extracted from them, which may in turn be used to determine the appropriate stimulation parameters. This ensures that stimulation is only applied as needed. It is important to note that aDBS systems also intrinsically expand the state space forDBS programming, potentially adding yet more complexity to an already laborious procedure. As directional leads become more common in DBS devices, this expanded programming state space further reduces the likelihood of optimal settings being reached. A twin requirement to developing effective aDBS systems is thus the design of a streamlined procedure for parameter optimization in DBS programming. This may be accomplished through the introduction of an automated programming pipeline. Through the collection of quantified data on symptom severity through the use of gyroscope or accelerometer data and the digitization of patient feedback on side effects, this pipeline could considerably speed testing.In addition, the digitization of the data required to analyze aDBS parameter performance could be integrated with modern optimization techniques, such that a personalized optimal treatment may be determined to within an increased degree of certainty. This work details approaches for resolving these deeply interwoven problems in aDBS treatment through insights from the fields of machine learning and optimization. We begin by considering the current state of the art in adaptive deep brain stimulation, its accomplishments, but especially its limitations. The principal limitations are: a general reliance on distributed systems that hinder free movement in patients; a focus solely on computationally inexpensive, but potentially suboptimal, binary aDBS control strategies; and the lack of an effective pipeline to deploy optimization methods during or after programming. Furthermore, recognition that these limitations are fundamentally interrelated implies that an integrated approach is required. The three key developments detailed in this work are thus themselves closely interrelated.Despite minor reductions in power savings, fully embedded binary aDBS is specifically de-signed to maximize therapeutic efficacy and ease of programming. Our results demonstrate that such a system is prepared for widespread studies in movement disorders. Our graded aDBS system yielded inconclusive results with regards to power savings and therapeutic efficacy. However, basing our approach to feature selection for symptom estimation from neural data on a model-free foundation has yielded promising evidence for relying on data-driven feature extraction. This approach to feature extraction intrinsically requires less direct programming, and instead maximizes the insights that may be gained from the data itself. Our development of a pipeline for automated programming of DBS parameters based on inertial measurements and patient feedback on side effects was designed to generalize easily into future integration with aDBS programming procedures. Finally, our computational approach to extracting information from a tablet- and mobile-based application demonstrates that semi- or fully-automated remote symptom assessment has the potential to significantly improve the future delivery of optimized, individualized treatment. Throughout this work, integration is a key component of discussion and consideration. Each result extracted from the developments discussed herein represents a small step away from the current standard of care. Considered individually, these steps would be taken incompletely different directions. It is the hope of the author that this work instead constitutes a realignment of these disparate goals and an explicit recognition of their inter-relatedness. Only by treating these problems as different faces of the same die can we arrive at truly optimized personalized treatment in aDBS.

Download or read book Machine Learning Methods for Motor Performance Decoding in Adaptive Deep Brain Stimulation written by Sebastián Castaño-Candamil and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Applied Software Development With Python Machine Learning By Wearable Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation written by Robert Lemoyne and published by World Scientific. This book was released on 2021-08-26 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to Cloud computing resources.Imperative to the realization of these objectives is the organization of the software development process. Requirements and pseudo code are derived, and software automation using Python for post-processing the inertial sensor signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provided. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system.Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity.Related Link(s)

Download or read book Applied Software Development With Python Machine Learning By Wearable Wireless Systems For Movement Disorder Treatment Via Deep Brain Stimulation written by Robert Charles LeMoyne and published by . This book was released on 2021 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The book presents the confluence of wearable and wireless inertial sensor systems, such as a smartphone, for deep brain stimulation for treating movement disorders, such as essential tremor, and machine learning. The machine learning distinguishes between distinct deep brain stimulation settings, such as 'On' and 'Off' status. This achievement demonstrates preliminary insight with respect to the concept of Network Centric Therapy, which essentially represents the Internet of Things for healthcare and the biomedical industry, inclusive of wearable and wireless inertial sensor systems, machine learning, and access to Cloud computing resources. Imperative to the realization of these objectives is the organization of the software development process. Requirements and pseudo code are derived, and software automation using Python for post-processing the inertial sensor signal data to a feature set for machine learning is progressively developed. A perspective of machine learning in terms of a conceptual basis and operational overview is provided. Subsequently, an assortment of machine learning algorithms is evaluated based on quantification of a reach and grasp task for essential tremor using a smartphone as a wearable and wireless accelerometer system. Furthermore, these skills regarding the software development process and machine learning applications with wearable and wireless inertial sensor systems enable new and novel biomedical research only bounded by the reader's creativity"--

Download or read book Stereotactic and Functional Neurosurgery written by Nader Pouratian and published by Springer Nature. This book was released on 2020-02-28 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents a comprehensive and state-of the-art approach to stereotactic and functional neurosurgery. Overarching sections include achieving stereotactic precision, defining trajectories and targets, the biophysics of stereotactic therapies, diseases and targets, and the future of functional neurosurgery. Each section is designed to be inclusive of all relevant topics, serving as an unbiased resource to new clinicians in this field or established clinicians that are aiming to better understand complementary methods. Importantly, each section and the associated chapters can be used by basic and translational scientists as well as engineers and industry to better understand and deliver innovation to the field. Chapters within each section methodically analyze traditional and recently emerging concepts and techniques; address underlying principles with examples drawn from specific diseases and applications; and cover patient selection, target selection, available stereotactic methods, nuanced surgical methods, and clinical evidence across treatment options. Written by experts in each area, Stereotactic and Functional Neurosurgery is a definitive guide to the latest developments in stereotactic targeting, electrode implantation, surgical treatment of neurological and psychiatric disorders, the renaissance of stereotactic lesions, and the frontier of restorative neurosurgery for a variety of disorders that have no other therapeutic options.

Download or read book Deep Brain Stimulation Think Tank Updates in Neurotechnology and Neuromodulation Volume IV written by Adolfo Ramirez-Zamora and published by Frontiers Media SA. This book was released on 2024-07-08 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, numerous developments have taken place in the field of neuromodulation. The introduction of newer technologies, software and increasing understanding of brain physiology in neurological and psychiatric conditions have shaped this rapidly growing field. To create a space where all stakeholders could freely interact to discuss challenges, advancements and opportunities in the field, the first Deep Brain Stimulation (DBS) Think Tank took place in 2012 in Gainesville Florida at the University of Florida. Since then, the meeting has grown to a hybrid virtual and in person meeting expanding the number of participants to over 200 world experts in the field. The most recent DBS think tank took place in Orlando Florida on August 25th to 27th, 2021. The meeting addressed new research, technologies, and neuroethical issues in the field of neuromodulation.

Download or read book Deep Brain Stimulation Think Tank Updates in Neurotechnology and Neuromodulation Volume II written by Adolfo Ramirez-Zamora and published by Frontiers Media SA. This book was released on 2022-06-27 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Classification written by Charu C. Aggarwal and published by CRC Press. This book was released on 2014-07-25 with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlyi

Download or read book Gaussian Processes for Machine Learning written by Carl Edward Rasmussen and published by MIT Press. This book was released on 2005-11-23 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.

Download or read book Implantable Electronic Medical Devices written by Dennis Fitzpatrick and published by Elsevier. This book was released on 2014-11-05 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implantable Electronic Medical Devices provides a thorough review of the application of implantable devices, illustrating the techniques currently being used together with overviews of the latest commercially available medical devices. This book provides an overview of the design of medical devices and is a reference on existing medical devices. The book groups devices with similar functionality into distinct chapters, looking at the latest design ideas and techniques in each area, including retinal implants, glucose biosensors, cochlear implants, pacemakers, electrical stimulation therapy devices, and much more. Implantable Electronic Medical Devices equips the reader with essential background knowledge on the application of existing medical devices as well as providing an introduction to the latest techniques being used. - A catalogue of existing implantable electronic medical devices - Up-to-date information on the design of implantable electronic medical devices - Background information and reviews on the application and design of up-to-date implantable electronic medical devices

Download or read book Deep Brain Stimulation Management written by William J. Marks, Jr and published by Cambridge University Press. This book was released on 2015-09-03 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essential reference guide for clinicians working with DBS patients, fully revised throughout with new chapters on epilepsy and psychiatric disorders.

Download or read book Transforming the Workforce for Children Birth Through Age 8 written by National Research Council and published by National Academies Press. This book was released on 2015-07-23 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: Children are already learning at birth, and they develop and learn at a rapid pace in their early years. This provides a critical foundation for lifelong progress, and the adults who provide for the care and the education of young children bear a great responsibility for their health, development, and learning. Despite the fact that they share the same objective - to nurture young children and secure their future success - the various practitioners who contribute to the care and the education of children from birth through age 8 are not acknowledged as a workforce unified by the common knowledge and competencies needed to do their jobs well. Transforming the Workforce for Children Birth Through Age 8 explores the science of child development, particularly looking at implications for the professionals who work with children. This report examines the current capacities and practices of the workforce, the settings in which they work, the policies and infrastructure that set qualifications and provide professional learning, and the government agencies and other funders who support and oversee these systems. This book then makes recommendations to improve the quality of professional practice and the practice environment for care and education professionals. These detailed recommendations create a blueprint for action that builds on a unifying foundation of child development and early learning, shared knowledge and competencies for care and education professionals, and principles for effective professional learning. Young children thrive and learn best when they have secure, positive relationships with adults who are knowledgeable about how to support their development and learning and are responsive to their individual progress. Transforming the Workforce for Children Birth Through Age 8 offers guidance on system changes to improve the quality of professional practice, specific actions to improve professional learning systems and workforce development, and research to continue to build the knowledge base in ways that will directly advance and inform future actions. The recommendations of this book provide an opportunity to improve the quality of the care and the education that children receive, and ultimately improve outcomes for children.

Download or read book Whittle s Gait Analysis written by Jim Richards and published by Elsevier Health Sciences. This book was released on 2012-07-13 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whittle’s Gait Analysis – formerly known as Gait Analysis: an introduction – is now in its fifth edition with a new team of authors led by David Levine and Jim Richards. Working closely with Michael Whittle, the team maintains a clear and accessible approach to basic gait analysis. It will assist both students and clinicians in the diagnosis of and treatment plans for patients suffering from medical conditions that affect the way they walk. Highly readable, the book builds upon the basics of anatomy, physiology and biomechanics Describes both normal and pathological gait Covers the range of methods available to perform gait analysis, from the very simple to the very complex. Emphasizes the clinical applications of gait analysis Chapters on gait assessment of neurological diseases and musculoskeletal conditions and prosthetics and orthotics Methods of gait analysis Design features including key points A team of specialist contributors led by two internationally-renowned expert editors 60 illustrations, taking the total number to over 180 Evolve Resources containing video clips and animated skeletons of normal gait supported by MCQs, an image bank, online glossary and sources of further information. Log on to http://evolve.elsevier.com/Whittle/gait to register and start using these resources today!

Download or read book Handbook of Neuroengineering written by Nitish V. Thakor and published by Springer Nature. This book was released on 2023-02-02 with total page 3686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook serves as an authoritative reference book in the field of Neuroengineering. Neuroengineering is a very exciting field that is rapidly getting established as core subject matter for research and education. The Neuroengineering field has also produced an impressive array of industry products and clinical applications. It also serves as a reference book for graduate students, research scholars and teachers. Selected sections or a compendium of chapters may be used as “reference book” for a one or two semester graduate course in Biomedical Engineering. Some academicians will construct a “textbook” out of selected sections or chapters. The Handbook is also meant as a state-of-the-art volume for researchers. Due to its comprehensive coverage, researchers in one field covered by a certain section of the Handbook would find other sections valuable sources of cross-reference for information and fertilization of interdisciplinary ideas. Industry researchers as well as clinicians using neurotechnologies will find the Handbook a single source for foundation and state-of-the-art applications in the field of Neuroengineering. Regulatory agencies, entrepreneurs, investors and legal experts can use the Handbook as a reference for their professional work as well.​

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Download or read book Neuromodulation in Psychiatry written by Clement Hamani and published by John Wiley & Sons. This book was released on 2016-01-26 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by an expert multidisciplinary team, Neuromodulation in Psychiatry is the first reference guide to address both invasive and non-invasive neuromodulation strategies used in psychiatry. Covers basic principles, technical aspects, clinical applications and ethical considerations Presents up-to-date evidence in comprehensive summaries suitable for all levels of experience Each technique is clearly explained along with its implications for real-world clinical practice Allows psychiatrists to make informed decisions regarding neuromodulation for their patients

Download or read book Being There written by Andy Clark and published by MIT Press. This book was released on 1998-01-23 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain, body, and world are united in a complex dance of circular causation and extended computational activity. In Being There, Andy Clark weaves these several threads into a pleasing whole and goes on to address foundational questions concerning the new tools and techniques needed to make sense of the emerging sciences of the embodied mind. Clark brings together ideas and techniques from robotics, neuroscience, infant psychology, and artificial intelligence. He addresses a broad range of adaptive behaviors, from cockroach locomotion to the role of linguistic artifacts in higher-level thought.