Neural Interface with the Peripheral Nervous System

Auteur

Dominique M. Durand is an E. L. Lindseth professor of biomedical engineering and neurosciences and director of the Neural Engineering Center at Case Western Reserve University, Cleveland, Ohio, USA. He was honored with the 2024 North American Neuromodulation Society (NANS) Engineering Innovator Award to recognize his pioneering work and implementation of innovative solutions in neuromodulation. Prof. Durand is an IEEE fellow and also a fellow of the American Institute for Medical and Biomedical Engineering and the Institute of Physics. He serves on 14 editorial boards of peer-reviewed scientific journals and is the editor-in-chief and founding editor of the Journal of Neural Engineering. He has published more than 170 peer-reviewed articles and has been a consultant for several biotechnology companies and foundations. He has been involved in groundbreaking research on the neural aspects of melanoma metastasis and his work aims to understand how the nervous system influences cancer development, which could lead to new methods for predicting and treating melanoma

Texte du rabat

This book relates to the analysis and the development of methods to for a nerve-machine interface. The goal is to provide a theoretical and experimental understanding of how one can recover neural signals from the various fascicles or selectively control the activation of these fascicles.

Résumé

Neural interfacing represents a riveting journey of scientific curiosity, innovation, and the relentless pursuit of solutions to some of the most complex challenges in neurology and bioengineering. Over the past two decades, pioneering studies have significantly propelled the field forward, particularly in the realm of peripheral nerves. These groundbreaking works have transformed our understanding of how to connect with the nervous system, allowing researchers and clinicians to uncover new therapeutic possibilities. Exploring peripheral nerve recording selectivity alongside multiple-contact nerve electrodes has brought unprecedented precision, enabling targeted treatments that minimize side effects and hold immense potential for both therapeutic interventions and diagnostics. The efforts continue to refine these technologies with the aim to reduce the mechanical and biological footprint of electrodes within the nervous system, and the ultimate vision is to develop neural interfaces that seamlessly integrate with both peripheral and central nervous systems for several years, enhancing the quality of life for individuals affected by neurological conditions.

This book highlights the remarkable progress in neural interfacing, from theoretical models to intricate designs of long-term implantable electrodes. It provides foundational knowledge and cutting-edge solutions for future breakthroughs in neuroprosthetics, neuromodulation, and the treatment of neurological disorders. It discusses pioneering research that laid the groundwork for predicting nerve fiber responses to electrical stimuli. It reviews the early models that forecast axonal excitation that simplified the complex, computational process, making neural interface design more practical and scalable. It analyzes innovations such as slowly penetrating interfascicular electrodes and spiral nerve cuff electrodes that significantly enhance precision and stability in neural recordings, minimizing tissue damage and expanding applications in prosthetics and sensory restoration. The book also covers key advancements in chronic neural interfaces and functional electrical stimulation that allow for fine-tuned muscle activation and novel neuromodulation treatments and analyzes closed-loop stimulation systems that utilize spontaneous nerve activity as feedback. It explores peripheral nerve recording selectivity that further boosts targeted therapeutic interventions and diagnostics, offering promising solutions for future neuroprosthetic devices. The book is a comprehensive resource that traces the evolution of nerve stimulation and recording technologies and is a testament to the collaboration, ingenuity, and perseverance of scientists, engineers, and clinicians dedicated to pushing the boundaries of what is possible.

Contenu

1. Spiral Nerve Cuff Electrode for Recordings of Respiratory Output
   2. Chronic Recordings of Hypoglossal Nerve Activity in a Dog Model of Upper Airway Obstruction
   3. Subfascicle Stimulation Selectivity with the Flat Interface Nerve Electrode
   4. Chronic Response of the Rat Sciatic Nerve to the Flat Interface Nerve Electrode
   5. Effects of Selective Hypoglossal Nerve Stimulation on Canine Upper Airway Mechanics
   6. Extracellular Voltage Profile for Reversing the Recruitment Order of Peripheral Nerve Stimulation: A Simulation Study
   7. Dilation of the Oropharynx via Selective Stimulation of the Hypoglossal Nerve
   8. Electrode Array for Reversing the Recruitment Order of Peripheral Nerve Stimulation: Experimental Studies
   9. Blind Source Separation of Peripheral Nerve Recordings
   10. Chronic Histological Effects of the Flat Interface Nerve Electrode
   11. Hierarchical Beamformer and Cross-Talk Reduction in Electroneurography
   12. Motion Control of Musculoskeletal Systems with Redundancy 13. Block of Peripheral Pain Response by High-Frequency Sinusoidal Stimulation 14. Motion Control of the Ankle Joint with a Multiple Contact Nerve Cuff Electrode: A Simulation Study 15. Motion Control of the Rabbit Ankle Joint with a Flat Interface Nerve Electrode 16. Selective Recovery of Fascicular Activity in Peripheral Nerves 17. Fabrication of High Contact-Density, Flat-Interface Nerve Electrodes for Recording and Stimulation Applications 18. Model-Based Bayesian Signal Extraction Algorithm for Peripheral Nerves 19. Chronic Interfacing with the Autonomic Nervous System Using Carbon Nanotube (CNT) Yarn Electrodes 20. Flexural Characterization of Carbon Nanotube (CNT) Yarn Neural Electrodes 21. Recovering Motor Activation with Chronic Peripheral Nerve Computer Interface 22. Spatiotemporal Characteristics of Neural Activity in Tibial Nerves with Carbon Nanotube Yarn Electrodes 23. Ultra-Low Noise Miniaturized Neural Amplifier with Hardware Averaging