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Artykuły w czasopismach na temat „Neural prosthesis”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 11 marca 2023

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1

Lin, Xiangli. "Neurophysiology Based on Deep Neural Network under Artificial Prosthesis Vision." Journal of Physics: Conference Series 2074, no. 1 (November 1, 2021): 012083. http://dx.doi.org/10.1088/1742-6596/2074/1/012083.

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Abstract With the vigorous development of electronic technology and computer technology, as well as the continuous advancement of research in the fields of neurophysiology, bionics and medicine, the artificial visual prosthesis has brought hope to the blind to restore their vision. Artificial optical prosthesis research has confirmed that prosthetic vision can restore part of the visual function of patients with non-congenital blindness, but the mechanism of early prosthetic image processing still needs to be clarified through neurophysiological research. The purpose of this article is to stud

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Di, Giovanna, W. Gong, C. Haburcakova, V. Kögler, J. Carpaneto, V. Genovese, D. Merfeld, et al. "Development of a closed-loop neural prosthesis for vestibular disorders." Journal of Automatic Control 20, no. 1 (2010): 27–32. http://dx.doi.org/10.2298/jac1001027d.

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Vestibular disorders can cause severe problems including spatial disorientation, imbalance, nausea, visual blurring, and even cognitive deficits. The CLONS project is developing a closed-loop, sensory neural prosthesis to alleviate these symptoms [1]. In this article, we outline the different components necessary to develop this prosthetic. A short version of this work was presented in the NEUREL 2010 [1]. Conceptually, the prosthesis restores vestibular information based on inertial sensors rigidly affixed to the user. These sensors provide information about rotational velocity of the head; t

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Boshlyakov, Andrew A., and Alexander S. Ermakov. "Development of a Vision System for an Intelligent Robotic Hand Prosthesis Using Neural Network Technology." ITM Web of Conferences 35 (2020): 04006. http://dx.doi.org/10.1051/itmconf/20203504006.

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A brief review of the existing auxiliary prosthetic control systems was carried out. The concept of an intelligent prosthesis is proposed, which will expand the possibilities of application and simplify the use of the prosthesis. The required actions of the vision system in automatic and manual capture modes are considered. The sequence of operation of the subsystems of the technical vision system is determined. The possibility of implementing a prosthesis vision system based on neural network technology is shown. The method of using a ready-made neural network for recognition of objects by a

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Pitkin, Mark, Charles Cassidy, Maxim A. Shevtsov, Joshua R. Jarrell, Hangue Park, Brad J. Farrell, John F. Dalton, et al. "Recent Progress in Animal Studies of the Skin- and Bone-integrated Pylon With Deep Porosity for Bone-Anchored Limb Prosthetics With and Without Neural Interface." Military Medicine 186, Supplement_1 (January 1, 2021): 688–95. http://dx.doi.org/10.1093/milmed/usaa445.

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ABSTRACT Introduction The three major unresolved problems in bone-anchored limb prosthetics are stable, infection-free integration of skin with a percutaneous bone implant, robust skeletal fixation between the implant and host bone, and a secure interface of sensory nerves and muscles with a prosthesis for the intuitive bidirectional prosthetic control. Here we review results of our completed work and report on recent progress. Materials and Methods Eight female adult cats received skin- and bone-integrated pylon (SBIP) and eight male adult cats received SBIP-peripheral neural interface (PNI)

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Mundkur, Nipun. "Bionic Human: A Review of Interface Modalities for Externally Powered Prosthetic Limbs." McGill Science Undergraduate Research Journal 14, no. 1 (April 10, 2019): 46–49. http://dx.doi.org/10.26443/msurj.v14i1.53.

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Background: The loss of a limb is a debilitating incident and can leave patients significantly disabled and often unable to perform activities of daily living. Prosthetic limbs can provide some modicum of normalcy back to their lives, and there has been much research over the past few decades into restoration of biomedical and physiological function with the use of externally powered and robotic prostheses. This review aims to explore the various approaches to machine-body interfacing that can be employed to achieve intuitive and meaningful control of these complex devices, and to discuss the

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Copeland, Christopher, Mukul Mukherjee, Yingying Wang, Kaitlin Fraser, and Jorge M. Zuniga. "Changes in Sensorimotor Cortical Activation in Children Using Prostheses and Prosthetic Simulators." Brain Sciences 11, no. 8 (July 27, 2021): 991. http://dx.doi.org/10.3390/brainsci11080991.

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This study aimed to examine the neural responses of children using prostheses and prosthetic simulators to better elucidate the emulation abilities of the simulators. We utilized functional near-infrared spectroscopy (fNIRS) to evaluate the neural response in five children with a congenital upper limb reduction (ULR) using a body-powered prosthesis to complete a 60 s gross motor dexterity task. The ULR group was matched with five typically developing children (TD) using their non-preferred hand and a prosthetic simulator on the same hand. The ULR group had lower activation within the primary m

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Richter, Claus-Peter, Andrew J. Fishman, and Agnella D. Izzo. "Cochlear Nerve Stimulation With Optical Radiation." Otolaryngology–Head and Neck Surgery 139, no. 2_suppl (August 2008): P99. http://dx.doi.org/10.1016/j.otohns.2008.05.519.

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Problem Neural prosthetic devices are artificial extensions to the body that restore or supplement nervous system function that was lost during disease or injury. The devices stimulate remaining neural tissue with electric current, providing some input to the nervous system. Hereby, the challenge for neural prostheses is to stimulate remaining neurons selectively. However, electrical current spread does not easily allow stimulation of small neuron populations. In neural prostheses developments, particular success has been realized in the cochlear prostheses development. The devices bypass dama

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Cunningham, John P., Paul Nuyujukian, Vikash Gilja, Cindy A. Chestek, Stephen I. Ryu, and Krishna V. Shenoy. "A closed-loop human simulator for investigating the role of feedback control in brain-machine interfaces." Journal of Neurophysiology 105, no. 4 (April 2011): 1932–49. http://dx.doi.org/10.1152/jn.00503.2010.

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Neural prosthetic systems seek to improve the lives of severely disabled people by decoding neural activity into useful behavioral commands. These systems and their decoding algorithms are typically developed “offline,” using neural activity previously gathered from a healthy animal, and the decoded movement is then compared with the true movement that accompanied the recorded neural activity. However, this offline design and testing may neglect important features of a real prosthesis, most notably the critical role of feedback control, which enables the user to adjust neural activity while us

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LARYIONAVA, KATSIARYNA, and DOMINIK GROSS. "Public Understanding of Neural Prosthetics in Germany: Ethical, Social, and Cultural Challenges." Cambridge Quarterly of Healthcare Ethics 20, no. 3 (May 20, 2011): 434–39. http://dx.doi.org/10.1017/s0963180111000119.

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Since the development of the first neural prosthesis, that is, the cochlear implant in 1957, neural prosthetics have been one of the highly promising, yet most challenging areas of medicine, while having become a clinically accepted form of invasiveness into the human body. Neural prosthetic devices, of which at least one part is inserted into the body, interact directly with the nervous system to restore or replace lost or damaged sensory, motor, or cognitive functions. This field is not homogenous and encompasses a variety of technologies, which are in various stages of development. Some dev

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Bakay, Roy A. E., and Prasad S. S. V. Vannemreddy. "Neural Prosthesis: Concept and Progress." World Neurosurgery 78, no. 6 (December 2012): 576–78. http://dx.doi.org/10.1016/j.wneu.2011.10.023.

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Chang, Ying, Lan Wang, Lingjie Lin, and Ming Liu. "Deep Neural Network for Electromyography Signal Classification via Wearable Sensors." International Journal of Distributed Systems and Technologies 13, no. 3 (July 1, 2022): 1–11. http://dx.doi.org/10.4018/ijdst.307988.

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The human-computer interaction has been widely used in many fields, such intelligent prosthetic control, sports medicine, rehabilitation medicine, and clinical medicine. It has gradually become a research focus of social scientists. In the field of intelligent prosthesis, sEMG signal has become the most widely used control signal source because it is easy to obtain. The off-line sEMG control intelligent prosthesis needs to recognize the gestures to execute associated action. In order solve this issue, this paper adopts a CNN plus BiLSTM to automatically extract sEMG features and recognize the

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Valle, Giacomo, Albulena Saliji, Ezra Fogle, Andrea Cimolato, Francesco M. Petrini, and Stanisa Raspopovic. "Mechanisms of neuro-robotic prosthesis operation in leg amputees." Science Advances 7, no. 17 (April 2021): eabd8354. http://dx.doi.org/10.1126/sciadv.abd8354.

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Above-knee amputees suffer the lack of sensory information, even while using most advanced prostheses. Restoring intraneural sensory feedback results in functional and cognitive benefits. It is unknown how this artificial feedback, restored through a neuro-robotic leg, influences users’ sensorimotor strategies and its implications for future wearable robotics. To unveil these mechanisms, we measured gait markers of a sensorized neuroprosthesis in two leg amputees during motor tasks of different difficulty. Novel sensorimotor strategies were intuitively promoted, allowing for a higher walking s

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Ramírez-García, Alfredo, Lorenzo Leija, and Roberto Muñoz. "Active Upper Limb Prosthesis Based on Natural Movement Trajectories." Prosthetics and Orthotics International 34, no. 1 (March 2010): 58–72. http://dx.doi.org/10.3109/03093640903463792.

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The motion of the current prostheses is sequential and does not allow natural movements. In this work, complex natural motion patterns from a healthy upper limb were characterized in order to be emulated for a trans-humeral prosthesis with three degrees of freedom at the elbow. Firstly, it was necessary to define the prosthesis workspace, which means to establish a relationship using an artificial neural network (ANN), between the arm-forearm (3-D) angles allowed by the prosthesis, and its actuators length. The 3-D angles were measured between the forearm and each axis of the reference system

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Dai, W. H., and Xiao Dong Zhang. "Design on the System of Brain-Computer Interface Driving Neural Prosthesis Hand." Key Engineering Materials 392-394 (October 2008): 1012–18. http://dx.doi.org/10.4028/www.scientific.net/kem.392-394.1012.

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In this paper, the system of brain-computer interface driving neural prosthesis hand is designed using EEG signal as the control signal source. First, a whole design scheme of the system of BCI driving neural prosthesis hand is constructed and the method of EEG detection and recognition is introduced. Then, on the basis of prosthesis hand wildly used by amputees, a three-degree of freedom prosthesis hand is chosen as the control object through rebuilt according to system requirement. The serial communication channel is constructed and the recognition result of hand action is sent to the prosth

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Broderick, Barry, Paul Breen, and Gearóid Ólaighin. "Electronic stimulators for surface neural prosthesis." Journal of Automatic Control 18, no. 2 (2008): 25–33. http://dx.doi.org/10.2298/jac0802025b.

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This paper presents the technological advancements in neural prosthesis devices using Functional Electrical Stimulation (FES). FES refers to the restoration of motor functions lost due to spinal cord injury (SCI), stroke, head injury, or diseases such as Cerebral Palsy or Multiple Sclerosis by eliciting muscular contractions through the use of a neuromuscular electrical stimulator device. The field has developed considerably since its inception, with the miniaturisation of circuity, the development of programmable and adaptable stimulators and the enhancement of sensors used to trigger the app

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Zhang, Xinglei, Binghui Fan, Chuanjiang Wang, Xiaolin Cheng, Hongguang Feng, and Zhaohui Tian. "Random Target Localization for an Upper Limb Prosthesis." Shock and Vibration 2021 (June 19, 2021): 1–14. http://dx.doi.org/10.1155/2021/5297043.

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To achieve the purpose of accurately grasping a random target with the upper limb prosthesis, the acquisition of target localization information is especially important. For this reason, a novel type of random target localization algorithm is proposed. Firstly, an initial localization algorithm (ILA) that uses two 3D attitude sensors and a laser range sensor to detect the target attitude and distance is presented. Secondly, an error correction algorithm where a multipopulation genetic algorithm (MPGA) optimizes backpropagation neural network (BPNN) is utilized to improve the accuracy of ILA. T

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Mao, Lin, Xiao Lu, Chao Yu, and Kuiying Yin. "Physiological and Neural Changes with Rehabilitation Training in a 53-Year Amputee: A Case Study." Brain Sciences 12, no. 7 (June 26, 2022): 832. http://dx.doi.org/10.3390/brainsci12070832.

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Many people who received amputation wear sEMG prostheses to assist in their daily lives. How these prostheses promote muscle growth and change neural activity remains elusive. We recruited a subject who had his left hand amputated for over 53 years to participate in a six-week rehabilitation training using an sEMG prosthesis. We tracked the muscle growth of his left forearm and changes in neural activity over six weeks. The subject showed an increase in fast muscle fiber in his left forearm during the training period. In an analysis of complex networks of neural activity, we observed that the

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Markowitz, Jared, Pavitra Krishnaswamy, Michael F. Eilenberg, Ken Endo, Chris Barnhart, and Hugh Herr. "Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model." Philosophical Transactions of the Royal Society B: Biological Sciences 366, no. 1570 (May 27, 2011): 1621–31. http://dx.doi.org/10.1098/rstb.2010.0347.

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Control schemes for powered ankle–foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle–tendon model that produces estimates of the acti

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Sattar, Neelum Yousaf, Zareena Kausar, Syed Ali Usama, Umer Farooq, Muhammad Faizan Shah, Shaheer Muhammad, Razaullah Khan, and Mohamed Badran. "fNIRS-Based Upper Limb Motion Intention Recognition Using an Artificial Neural Network for Transhumeral Amputees." Sensors 22, no. 3 (January 18, 2022): 726. http://dx.doi.org/10.3390/s22030726.

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Prosthetic arms are designed to assist amputated individuals in the performance of the activities of daily life. Brain machine interfaces are currently employed to enhance the accuracy as well as number of control commands for upper limb prostheses. However, the motion prediction for prosthetic arms and the rehabilitation of amputees suffering from transhumeral amputations is limited. In this paper, functional near-infrared spectroscopy (fNIRS)-based approach for the recognition of human intention for six upper limb motions is proposed. The data were extracted from the study of fifteen healthy

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Yan, Gongxing, Jialing Li, Hui Xie, and Minggui Zhou. "5G Virtual Reality System for Prosthetic Wearer Gait Evaluation and Application in Intelligent Prosthesis Debugging." Mobile Information Systems 2022 (September 16, 2022): 1–13. http://dx.doi.org/10.1155/2022/6311065.

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The main purpose of developing intelligent lower limb prostheses is to improve the quality of life of the disabled and promote the development of medical care. At the same time, the research of robotic intelligent lower limb prosthesis is a research direction that has been widely concerned in the field of robotics and biomedical engineering technology in recent years. This paper aims to research and discuss the 5G virtual reality system based on the gait evaluation of prosthetic wearers and its application in the debugging of intelligent prostheses. First, this paper analyzes the combination o

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Gibas, Christian, Luca Mülln, and Rainer Brück. "Use of artificial intelligence and neural networks for analysis and gesture detection in electrical impedance tomography." Current Directions in Biomedical Engineering 6, no. 3 (September 1, 2020): 489–92. http://dx.doi.org/10.1515/cdbme-2020-3126.

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AbstractArtificial intelligence and neural networks are getting more and more relevant for several types of application. The field of prosthesis technology currently uses electromyography for controllable prosthesis. The precision of the control suffers from the use of EMG. More precise and more collected data with the help of EIT allows a much more precise analysis and control of the prosthesis. In this paper a neural network for gesture detection using EIT is developed and presented in a user-friendly way.

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Caravaca-Rodriguez, Daniel, Susana P. Gaytan, Gregg J. Suaning, and Alejandro Barriga-Rivera. "Implications of Neural Plasticity in Retinal Prosthesis." Investigative Opthalmology & Visual Science 63, no. 11 (October 17, 2022): 11. http://dx.doi.org/10.1167/iovs.63.11.11.

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Guenther, Frank H. "Real‐time speech synthesis for neural prosthesis." Journal of the Acoustical Society of America 125, no. 4 (April 2009): 2496. http://dx.doi.org/10.1121/1.4783342.

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Hepp, D., J. Kirsch, and F. Capanni. "Smartphone supported upper limb prosthesis." Current Directions in Biomedical Engineering 1, no. 1 (September 1, 2015): 484–87. http://dx.doi.org/10.1515/cdbme-2015-0116.

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AbstractState of the art upper limb prostheses offer up to six active DoFs (degrees of freedom) and are controlled using different grip patterns. This low number of DoFs combined with a machine-human-interface which does not provide control over all DoFs separately result in a lack of usability for the patient. The aim of this novel upper limb prosthesis is both offering simplified control possibilities for changing grip patterns depending on the patients’ priorities and the improvement of grasp capability. Design development followed the design process requirements given by the European Medic

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Gini, Giuseppina, Matteo Arvetti, Ian Somlai, and Michele Folgheraiter. "Acquisition and Analysis of EMG Signals to Recognize Multiple Hand Movements for Prosthetic Applications." Applied Bionics and Biomechanics 9, no. 2 (2012): 145–55. http://dx.doi.org/10.1155/2012/792359.

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One of the main problems in developing active prosthesis is how to control them in a natural way. In order to increase the effectiveness of hand prostheses there is a need in better exploiting electromyography (EMG) signals. After an analysis of the movements necessary for grasping, we individuated five movements for the wrist-hand mobility. Then we designed the basic electronics and software for the acquisition and the analysis of the EMG signals. We built a small size electronic device capable of registering them that can be integrated into a hand prosthesis. Among all the numerous muscles t

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Lin, Chin-Yu, Wan-Shiun Lou, Jyh-Chern Chen, Kuo-Yao Weng, Ming-Cheng Shih, Ya-Wen Hung, Zhu-Yin Chen, and Mei-Chih Wang. "Bio-Compatibility and Bio-Insulation of Implantable Electrode Prosthesis Ameliorated by A-174 Silane Primed Parylene-C Deposited Embedment." Micromachines 11, no. 12 (November 30, 2020): 1064. http://dx.doi.org/10.3390/mi11121064.

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Microelectrodes for pain management, neural prosthesis or assistances have a huge medical demand, such as the application of pain management chip or retinal prosthesis addressed on age-related macular degeneration (AMD) and the retinitis pigmentosa (RP). Due to lifelong implanted in human body and direct adhesion of neural tissues, the electrodes and associated insulation materials should possess an ideal bio-compatibility, including non-cytotoxicity and no safety concern elicited by immune responses. Our goal intended to develop retinal prosthesis, an electrical circuit chip used for assistin

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Davoodi, Rahman, and Gerald E. Loeb. "Development of a Physics-Based Target Shooting Game to Train Amputee Users of Multijoint Upper Limb Prostheses." Presence: Teleoperators and Virtual Environments 21, no. 1 (February 2012): 85–95. http://dx.doi.org/10.1162/pres_a_00091.

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For upper limb amputees, learning the control of myoelectric prostheses is difficult and challenging. Introduction of newer prostheses with multiple degrees of freedom controlled by various neural commands will make such training even more difficult. To produce smooth and human-like movements, the user must learn to produce multiple neural commands with precise amplitude and timing. To aid in training of the amputee users, we have developed a realistic and motivating virtual environment (VE) consisting of a physics-based target shooting game. The users' neural commands such as EMG, cortical ne

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BARRETT, JOHN MARTIN, ROLANDO BERLINGUER-PALMINI, and PATRICK DEGENAAR. "Optogenetic approaches to retinal prosthesis." Visual Neuroscience 31, no. 4-5 (August 6, 2014): 345–54. http://dx.doi.org/10.1017/s0952523814000212.

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AbstractThe concept of visual restoration via retinal prosthesis arguably started in 1992 with the discovery that some of the retinal cells were still intact in those with the retinitis pigmentosa disease. Two decades later, the first commercially available devices have the capability to allow users to identify basic shapes. Such devices are still very far from returning vision beyond the legal blindness. Thus, there is considerable continued development of electrode materials, and structures and electronic control mechanisms to increase both resolution and contrast. In parallel, the field of

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Sinkjaer, Thomas. "Integrating Sensory Nerve Signals Into Neural Prosthesis Devices." Neuromodulation: Technology at the Neural Interface 3, no. 1 (January 2000): 34–41. http://dx.doi.org/10.1046/j.1525-1403.2000.00035.x.

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Gilja, Vikash, Chethan Pandarinath, Christine H. Blabe, Paul Nuyujukian, John D. Simeral, Anish A. Sarma, Brittany L. Sorice, et al. "Clinical translation of a high-performance neural prosthesis." Nature Medicine 21, no. 10 (September 28, 2015): 1142–45. http://dx.doi.org/10.1038/nm.3953.

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Ionescu, C. M., and R. M. C. De Keyser. "Control of paralyzed skeletal muscles: A neural prosthesis." Computer Methods in Biomechanics and Biomedical Engineering 8, sup1 (September 2005): 145–46. http://dx.doi.org/10.1080/10255840512331388678.

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Normann, Richard A., Edwin M. Maynard, Patrick J. Rousche, and David J. Warren. "A neural interface for a cortical vision prosthesis." Vision Research 39, no. 15 (July 1999): 2577–87. http://dx.doi.org/10.1016/s0042-6989(99)00040-1.

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Hussain, Jabbar Salman, Ahmed Al-Khazzar, and Mithaq Nama Raheema. "Recognition of additional myo armband gestures for myoelectric prosthetic applications." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 6 (December 1, 2020): 5694. http://dx.doi.org/10.11591/ijece.v10i6.pp5694-5702.

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Myoelectric prostheses are a viable solution for people with amputations. The challenge in implementing a usable myoelectric prosthesis lies in accurately recognizing different hand gestures. The current myoelectric devices usually implement very few hand gestures. In order to approximate a real hand functionality, a myoelectric prosthesis should implement a large number of hand and ﬁnger gestures. However, increasing number of gestures can lead to a decrease in recognition accuracy. In this work a Myo arm band device is used to recognize fourteen gestures (ﬁve build in gestures of Myo armband

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Sun, Baofeng, and Wanzhong Chen. "CLASSIFICATION OF sEMG SIGNALS USING INTEGRATED NEURAL NETWORK WITH SMALL SIZED TRAINING DATA." Biomedical Engineering: Applications, Basis and Communications 24, no. 04 (August 2012): 365–76. http://dx.doi.org/10.4015/s1016237212500329.

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The sEMG (Surface electromyography) signals detected from activated muscles can be used as a control source for prosthesis. So an efficient and accurate method for the classification of sEMG signal patterns has become a hot research in recent years. Artificial neural network is a popular used method in this field, however, most neural networks require large numbers of samples in the training stage to obtain the potential relationships between input feature vectors and the outputs. In this paper, Integrated back propagation neural network (IBPNN) is used to classify sEMG signals acquired during

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Murray, Rosemarie, Joel Mendez, Lukas Gabert, Nicholas P. Fey, Honghai Liu, and Tommaso Lenzi. "Ambulation Mode Classification of Individuals with Transfemoral Amputation through A-Mode Sonomyography and Convolutional Neural Networks." Sensors 22, no. 23 (December 1, 2022): 9350. http://dx.doi.org/10.3390/s22239350.

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Many people struggle with mobility impairments due to lower limb amputations. To participate in society, they need to be able to walk on a wide variety of terrains, such as stairs, ramps, and level ground. Current lower limb powered prostheses require different control strategies for varying ambulation modes, and use data from mechanical sensors within the prosthesis to determine which ambulation mode the user is in. However, it can be challenging to distinguish between ambulation modes. Efforts have been made to improve classification accuracy by adding electromyography information, but this

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Li, Will X. Y., Ray C. C. Cheung, Yao Xin, Dong Song, and Theodore W. Berger. "An FPGA-Based High-Performance Neural Ensemble Spiking Activity Simulator Utilizing Generalized Volterra Kernel and Complexity Analysis." Journal of Circuits, Systems and Computers 25, no. 01 (November 15, 2015): 1640004. http://dx.doi.org/10.1142/s0218126616400041.

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Neural information is represented and transmitted among neuronal units by a series of all-or-none “neural codes”. During the process of neural prosthesis design, generally, a large amount of “neural codes” need to be captured and analyzed, which brings about an important discipline, known as neuroinformatics. However, in neuroinformatics study, this coding process, also termed as “spiking activity”, is not straightforward for prediction. It is owing to the high nonlinearity and dynamic property involved in generation of the neuronal spikes. In this paper, a novel generalized Volterra kernel-ba

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Buss, Stephanie. "From Visual Plasticity to the Bionic Eye." Einstein Journal of Biology and Medicine 27, no. 1 (March 2, 2016): 10. http://dx.doi.org/10.23861/ejbm20112725.

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While visual plasticity is strongest in early infancy, new studies show that plasticity is maintained well into adult life.This possibility is compellingly demonstrated by one patient, SK, who gained vision for the first time in adult life andsignificantly improved his ability to see the world around him. The persistence of visual plasticity in adults is promisingnews for the developing field of visual prosthesis.In recent years, there has been an explosion of research on prosthetic devices for the brain. While memory-enhancingbrain chips are still science fiction, cochlear implants, which sti

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Jothi Lakshmi, D., G. Illakiya, and R. Rajkamal. "A Novel Approach and Design of Embedded Controlled Prosthetic Upper Limb to Assist the above Elbow Amputees." Advanced Materials Research 403-408 (November 2011): 2039–45. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.2039.

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The existing prosthetic upper limb design and control is divided into two broad categories. One is the myoelectric prosthesis where electromechanical active joints actuate the arm segments and is directly activated by acquiring Electromyogram (EMG) signals from the amputee which is sensed by myoelectric electrodes. Acquiring of the EMG signals is a tedious process as it involves adequate amplification and proper filtering. Also isolation of noise from EMG signals poses difficulty. The other category falls under intelligent prosthetic hand where neural networks (NN) are involved. It requires ad

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Emayavaramban, G., A. Amudha, T. Rajendran, M. Sivaramkumar, K. Balachandar, and T. Ramesh. "Identifying User Suitability in sEMG Based Hand Prosthesis Using Neural Networks." Current Signal Transduction Therapy 14, no. 2 (October 10, 2019): 158–64. http://dx.doi.org/10.2174/1574362413666180604100542.

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Background: Identifying user suitability plays a vital role in various modalities like neuromuscular system research, rehabilitation engineering and movement biomechanics. This paper analysis the user suitability based on neural networks (NN), subjects, age groups and gender for surface electromyogram (sEMG) pattern recognition system to control the myoelectric hand. Six parametric feature extraction algorithms are used to extract the features from sEMG signals such as AR (Autoregressive) Burg, AR Yule Walker, AR Covariance, AR Modified Covariance, Levinson Durbin Recursion and Linear Predicti

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Lai, Qiuxia, Dingyin Hu, Ang Ke, and Jiping He. "Providing Sensory Feedback Using Electrical Stimulation for Neural Prosthesis." Neuroscience and Biomedical Engineering 2, no. 2 (April 10, 2015): 99–104. http://dx.doi.org/10.2174/2213385203666150328002141.

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Gong, Wangsong, and Daniel M. Merfeld. "Prototype Neural Semicircular Canal Prosthesis using Patterned Electrical Stimulation." Annals of Biomedical Engineering 28, no. 5 (May 2000): 572–81. http://dx.doi.org/10.1114/1.293.

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Troyk, P., and Zhe Hu. "Simplified Design Equations for Class-E Neural Prosthesis Transmitters." IEEE Transactions on Biomedical Engineering 60, no. 5 (May 2013): 1414–21. http://dx.doi.org/10.1109/tbme.2012.2237172.

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Purcell, E. K., J. P. Seymour, S. Yandamuri, and D. R. Kipke. "In vivoevaluation of a neural stem cell-seeded prosthesis." Journal of Neural Engineering 6, no. 4 (July 22, 2009): 049801. http://dx.doi.org/10.1088/1741-2552/6/4/049801.

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Hageman, Kristin N., Zaven K. Kalayjian, Francisco Tejada, Bryce Chiang, Mehdi A. Rahman, Gene Y. Fridman, Chenkai Dai, et al. "A CMOS Neural Interface for a Multichannel Vestibular Prosthesis." IEEE Transactions on Biomedical Circuits and Systems 10, no. 2 (April 2016): 269–79. http://dx.doi.org/10.1109/tbcas.2015.2409797.

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Kalanovic, Vojislav D., and Nils T. Skaug. "Feedback Error Learning Neural Network for Above-Knee Prosthesis." IFAC Proceedings Volumes 30, no. 6 (May 1997): 1617–22. http://dx.doi.org/10.1016/s1474-6670(17)43592-0.

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Purcell, E. K., J. P. Seymour, S. Yandamuri, and D. R. Kipke. "In vivoevaluation of a neural stem cell-seeded prosthesis." Journal of Neural Engineering 6, no. 2 (March 13, 2009): 026005. http://dx.doi.org/10.1088/1741-2560/6/2/026005.

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Seligman, Peter. "Prototype to product—developing a commercially viable neural prosthesis." Journal of Neural Engineering 6, no. 6 (October 23, 2009): 065006. http://dx.doi.org/10.1088/1741-2560/6/6/065006.

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Berger, Theodore W., Robert E. Hampson, Dong Song, Anushka Goonawardena, Vasilis Z. Marmarelis, and Sam A. Deadwyler. "A cortical neural prosthesis for restoring and enhancing memory." Journal of Neural Engineering 8, no. 4 (June 15, 2011): 046017. http://dx.doi.org/10.1088/1741-2560/8/4/046017.

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Kalanovic, V. D., D. Popovic, and N. T. Skaug. "Feedback error learning neural network for trans-femoral prosthesis." IEEE Transactions on Rehabilitation Engineering 8, no. 1 (March 2000): 71–80. http://dx.doi.org/10.1109/86.830951.

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Miler, Vera, Goran Bijelic, and Laszlo Schwirtlich. "Neural prosthesis for the therapy of low back pain." Journal of Automatic Control 18, no. 2 (2008): 93–97. http://dx.doi.org/10.2298/jac0802093m.

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We present methods to treat Low Back Pain (LBP) with electrical stimulation. The conventional method of treating LBP with electrical stimulation is based on mechanisms of reduction of pain. The method that we suggest uses electrical stimulation of trunk muscles at motor suprathreshold level synchronized with exercising of the trunk muscles. The hypothesis was that the combination of voluntary activity augmented with electrical stimulation would lead to higher levels of recovery of postural control and thereby, reduction of LBP. The electrical stimulation in this treatment was delivered with th

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