603 resources related to Neural prosthesis
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2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting
The joint meeting is intended to provide an international forum for the exchange of information on state of the art research in the area of antennas and propagation, electromagnetic engineering and radio science
The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE
ECTC is the premier international conference sponsored by the IEEE Components, Packaging and Manufacturing Society. ECTC paper comprise a wide spectrum of topics, including 3D packaging, electronic components, materials, assembly, interconnections, device and system packaging, optoelectronics, reliability, and simulation.
The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
ISSCC is the foremost global forum for solid-state circuits and systems-on-a-chip. The Conference offers 5 days of technical papers and educational events related to integrated circuits, including analog, digital, data converters, memory, RF, communications, imagers, medical and MEMS ICs.
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
Educational methods, technology, and programs; history of technology; impact of evolving research on education.
Publishes original and significant contributions relating to the theory, design, performance and reliability of electron devices, including optoelectronics devices, nanoscale devices, solid-state devices, integrated electronic devices, energy sources, power devices, displays, sensors, electro-mechanical devices, quantum devices and electron tubes.
Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.
2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236), 2001
Two artificial neural net (ANN) based controllers using interfaces to the peripheral nervous system are presented. The aim of the paper is to show the ANNs' capability to interact with the biological nervous system for control purposes. First, we present a system for controlling a limb prostheses by means of biological nerve signals. Recordings of nerve signals done by regeneration ...
Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Societ, 1993
Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology, 2002
Sensory prostheses generally require dense multichannel interfaces in a small place that is difficult to access but mechanically protected. Motor prostheses must activate a relatively modest number of muscles distributed widely over limbs subject to constant motion and external impacts. Sensory prostheses require high data rates to recreate complex temporospatial patterns of neural activity while muscles are unidimensional low-pass filters. ...
Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143), 2000
Presents some recently obtained results regarding possibility of application of wavelet neural networks (WNN) for both description and further analysis of events happening with the artificial heart valves. It is extremely important to create a tool allowing analysis of flow pattern through an artificial heart valve prosthesis, which makes possible the extraction of some conclusions leading to valve prosthesis design ...
SENSORS, 2003 IEEE, 2003
An analog circuit has been designed to mimic the dynamic function of a unilateral semicircular canal of the vestibular system. The circuitry is an integral part of a novel MEMS-based electrostimulatory prosthesis currently investigated by this research group. The device is intended for restoration of permanently damaged balance function. The present experimental results indicate that under the same inertial loading ...
Ted Berger: Far Futures Panel - Technologies for Increasing Human Memory - TTM 2018
The Design of Wearable Robots for Lower-Extremity Human Augmentation
Development of Neural Interfaces for Robotic Prosthetic Limbs
Achieving Swarm Intelligence with Spiking Neural Oscillators - IEEE Rebooting Computing 2017
Auditory Neural Pathway Simulation - IEEE Rebooting Computing 2017
Towards On-Chip Optical FFTs for Convolutional Neural Networks - IEEE Rebooting Computing 2017
20 Years of Neural Networks: A Promising Start, A brilliant Future- Video contents
On the Physical Underpinnings of the Unusual Effectiveness of Probabilistic and Neural Computation - IEEE Rebooting Computing 2017
Improved Deep Neural Network Hardware Accelerators Based on Non-Volatile-Memory: the Local Gains Technique: IEEE Rebooting Computing 2017
Lizhong Zheng's Globecom 2019 Keynote
Large-scale Neural Systems for Vision and Cognition
Artificial Neural Networks, Intro
Emergent Neural Network in reinforcement learning
Spike Timing, Rhythms, and the Effective Use of Neural Hardware
Overcoming the Static Learning Bottleneck - the Need for Adaptive Neural Learning - Craig Vineyard: 2016 International Conference on Rebooting Computing
High Throughput Neural Network based Embedded Streaming Multicore Processors - Tarek Taha: 2016 International Conference on Rebooting Computing
Deep Learning and the Representation of Natural Data
Complex-Valued Neural Networks
Behind Artificial Neural Networks
Two artificial neural net (ANN) based controllers using interfaces to the peripheral nervous system are presented. The aim of the paper is to show the ANNs' capability to interact with the biological nervous system for control purposes. First, we present a system for controlling a limb prostheses by means of biological nerve signals. Recordings of nerve signals done by regeneration type neurosensors interfacing the peripheral nerve system are processed by ANNs in order to control a commercial available hand prostheses. The second system presented is the inverse of the presented controller above. In this case, the aim of the controller is the restoration of lost hand function for disabled persons Here, the ANN is the kernel of a closed loop control calculating stimulation patterns for the peripheral nerve system in order to evoke hand movements related to the patient's intent.
Sensory prostheses generally require dense multichannel interfaces in a small place that is difficult to access but mechanically protected. Motor prostheses must activate a relatively modest number of muscles distributed widely over limbs subject to constant motion and external impacts. Sensory prostheses require high data rates to recreate complex temporospatial patterns of neural activity while muscles are unidimensional low-pass filters. Sensory prostheses generally need one sophisticated interface for stimulation while sensorimotor prostheses require a wealth of command and feedback signals employing different electrical and mechanical sensing modalities. Sensory prostheses do as little signal processing as necessary to enable the brain to do the difficult perceptual computations while sensorimotor prostheses must replace the functionality of motor planning and coordination centers whose normal functions we barely understand. Sensory deficits (e.g. deafness, blindness) tend to affect large numbers of patients in homogeneous and stable ways while motor deficits come in a much wider variety and change over time due to neural and muscular plasticity. We are just starting to assemble the diverse armamentarium of implantable interfaces, control strategies and fitting tools that will be needed to treat motor disabilities successfully.
Presents some recently obtained results regarding possibility of application of wavelet neural networks (WNN) for both description and further analysis of events happening with the artificial heart valves. It is extremely important to create a tool allowing analysis of flow pattern through an artificial heart valve prosthesis, which makes possible the extraction of some conclusions leading to valve prosthesis design process improvement.
An analog circuit has been designed to mimic the dynamic function of a unilateral semicircular canal of the vestibular system. The circuitry is an integral part of a novel MEMS-based electrostimulatory prosthesis currently investigated by this research group. The device is intended for restoration of permanently damaged balance function. The present experimental results indicate that under the same inertial loading conditions it is feasible to design a prosthesis that matches the signal recorded from the vestibular nerve in squirrel monkey experiments reported in the literature (Jiayin Liu et al., 2003).
This paper presents two case studies of the reliability of implantable neural stimulators, designed specifically as auditory prostheses. These reliability results, collected from lifetime experiments, failure analysis, and manufacturing testing, confirm the crucial roles of well planned design and packaging in system reliability. Guidelines are proposed for the design of reliable implantable systems. The improvements in the second design can be traced to the better electronic design and manufacture, the careful considerations of metallurgical characteristics in bonding and connecting components, the package design, and the exhaustive tests at each step of the manufacturing process. The reliability of these designs, and of implantable systems in general, is by no means resolved nor well understood. There is a definite need for comprehensive data bases and techniques for reliability analysis of these systems as well as the systematic manufacturing test for reliability assurance, which is a growing concern in the research and development of artificial organs.
Surgical techniques are a critical contributor to the level of success achieved with chronically implanted cortical neuroprosthetic devices. Many different factors contribute to the amount of irritation the tissue is exposed to from the implanted device. Factors include mechanical irritations, infectious pathogens, dural regrowth, etc. In this paper we describe a novel application of the hydrogel polymer, ALGEL/spl reg/ (Neural Intervention Technologies, Ann Arbor, MI), in conjunction with an implanted Michigan probe (CNCT, University of Michigan). This polymer contains many inherent properties that are beneficial to this type of procedure. Properties include: 1) ease of application, 2) biocompatibility, 3) exemplary mechanical properties, and 4) translucent clarity. We believe that ALGEL has been a large contributor to the high level of success achieved with our chronic electrode implantations.
Throughout the history of mankind, tools have served the role as passive extensions of the body. Recently, the development of neuroprosthesis has changed the scope of how humans interact with tools. Neuroprosthetics enable direct interfacing with the brain and have the great potential for restoring communication and control in disabled individuals. The transformative aspect of direct neural interfaces is that they can be designed as 'intelligent tools' that not only carry out intent but also have the capability to assist, evolve, and grow with the user. Unlike other tools, neuroprosthetics exist in a shared space that seamlessly spans the user's internal representation of the world and the physical environment enabling a much deeper human tool symbiosis. Recent advancements in the engineering of neuroprosthetics are providing a blueprint for how new co-adaptive designs change the nature of a user's ability to accomplish tasks that were not possible using conventional methodologies. This paper analyzes how key advances in science and technology supporting the development of intelligent neuroprosthesis and contrasts them with "lessons learned" from the past 50 years in the IEEE.
Construction of a brain-machine interface system for neuroprosthetic purposes is at the forefront of many current neural engineering thrusts. Due to recent breakthroughs in device technology and implantation techniques, a basic framework is now sufficiently developed to allow design of systems level interface strategies producing robust, scalable BMIs that adapt quickly to optimize information transfer at the interface. It is useful to develop brain- machine interface systems in a modular fashion, enabling individual component research and development. This study investigates cortical microstimulation as a mode of operation for a sensory encoding component of a brain-machine interface system. It has previously been shown that cortical stimulation of sensory cortical areas produces sensations. In this report we compare behavior induced by either natural auditory cues, or cortical microstimulation of the primary auditory cortex. Five rats were implanted with multi-channel microwire arrays in auditory cortex and required to discriminate cortical microstimulation separated by 1.75 mm. The behavior was compared to auditory discrimination of tones separated by four octaves. The microstimulation resulted in 17% faster response times across the five rats.
The long time for getting an acceptable response in myoelectric prosthesis has been a problem. Thanks to DSP processors, the myoelectric signal (MES) processing time has had a drastic reduction. This paper describes a control unit for a myoelectric prosthesis using statistic variables related to contraction force. ANOVA analysis was used to seek the best separable characteristic set. A MES stationarity detector was implemented and a perceptron artificial neural network was used as classifier. A dedicated system was built using a DSP processor and it has a fast response.
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