Gotowe bibliografie tematyczne / Neural prosthesis

Spis treści

  1. Artykuły w czasopismach
  2. Rozprawy doktorskie
  3. Książki
  4. Części książek
  5. Streszczenia konferencji
  6. Raporty organizacyjne

Gotowa bibliografia na temat „Neural prosthesis”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 11 marca 2023

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Artykuły w czasopismach na temat "Neural prosthesis"

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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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Rozprawy doktorskie na temat "Neural prosthesis"

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Williamson, Richard. "A new generation neural prosthesis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0021/NQ46945.pdf.

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Dommel, Norbert Brian Graduate School of Biomedical Engineering Faculty of Engineering UNSW. "A vision prosthesis neurostimulator: progress towards the realisation of a neural prosthesis for the blind." Publisher:University of New South Wales. Graduate School of Biomedical Engineering, 2008. http://handle.unsw.edu.au/1959.4/41249.

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Restoring vision to the blind has been an objective of several research teams for a number of years. It is known that spots of light -- phosphenes -- can be elicited by way of electrical stimulation of surviving retinal neurons. Beyond this, however, our understanding of prosthetic vision remains rudimentary. To advance the realisation of a clinically viable prosthesis for the blind, a versatile integrated circuit neurostimulator was designed, manufactured, and verified. The neurostimulator provides electrical stimuli to surviving neurons in the visual pathway, affording blind patients some f
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Tan, Daniel. "Restoring Sensation in Human Upper Extremity Amputees using Chronic Peripheral Nerve Interfaces." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1405070015.

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BISONI, LORENZO. "An implantable micro-system for neural prosthesis control and sensory feedback restoration in amputees." Doctoral thesis, Università degli Studi di Cagliari, 2015. http://hdl.handle.net/11584/266608.

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In this work, the prototype of an electronic bi-directional interface between the Peripheral Nervous System (PNS) and a neuro-controlled hand prosthesis is presented. The system is composed of two Integrated Circuits (ICs): a standard CMOS device for neural recording and a High Voltage (HV) CMOS device for neural stimulation. The integrated circuits have been realized in two different 0.35μm CMOS processes available fromAustriaMicroSystem(AMS). The recoding IC incorporates 8 channels each including the analog front-end and the A/D conversion based on a sigma delta architecture. It has a
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Prodanov, Dimiter Petkov. "Morphometric analysis of the rat lower limb nerves anatomical data for neural prosthesis design /." Enschede : University of Twente [Host], 2006. http://doc.utwente.nl/51110.

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Siu, Timothy Lok Tin Medical Sciences Faculty of Medicine UNSW. "Artificial vision: feasibility of an episcleral retinal prosthesis & implications of neuroplasticity." Awarded By:University of New South Wales. Medical Sciences, 2009. http://handle.unsw.edu.au/1959.4/42879.

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Background. A visual prosthesis is a conceptual device designed to activate residual functional neurons in the visual pathway of blind individuals to produce artificial vision. Such device, when applied to stimulate the vitreous surface of the retina, has proven feasible in producing patterned light perception in blind individuals suffering from dystrophic diseases of the retina, such as aged-related macular degeneration (AMD). However the practicality of such approach has been challenged by the difficulty of surgical access and the risks of damaging the neuroretina. Positioning a visual impla
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Bugbee, Martin Bryan. "An implantable stimulator for the selective stimulation of nerves." Thesis, University College London (University of London), 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369068.

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Al-Shueli, Assad. "Signal processing for advanced neural recording systems." Thesis, University of Bath, 2013. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.577744.

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Many people around the world suffer from neurological injuries of various sorts that cause serious difficulties in their lives, due to the loss of important sensory and motor functions. Functional electrical stimulation (FES) provides a possible solution to these difficulties by means of a feedback connection allowing the target organ (or organs) to be controlled by electrical stimulation. The control signals can be provided using recorded data extracted from the nerves (electroneurogram, ENG). The most common and safe approaches for interfacing with nerves is called cuff electrodes which deli
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Smith, Alan. "Myoelectric control techniques for a rehabilitation robot /." Online version of thesis, 2009. http://hdl.handle.net/1850/10893.

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Hallum, Luke Edward Graduate School of Biomedical Engineering Faculty of Engineering UNSW. "Prosthetic vision : Visual modelling, information theory and neural correlates." Publisher:University of New South Wales. Graduate School of Biomedical Engineering, 2008. http://handle.unsw.edu.au/1959.4/41450.

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Electrical stimulation of the retina affected by photoreceptor loss (e.g., cases of retinitis pigmentosa) elicits the perception of luminous spots (so-called phosphenes) in the visual field. This phenomenon, attributed to the relatively high survival rates of neurons comprising the retina's inner layer, serves as the cornerstone of efforts to provide a microelectronic retinal prosthesis -- a device analogous to the cochlear implant. This thesis concerns phosphenes -- their elicitation and modulation, and, in turn, image analysis for use in a prosthesis. This thesis begins with a comparative r
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Książki na temat "Neural prosthesis"

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Yang, Zhi, ed. Neural Computation, Neural Devices, and Neural Prosthesis. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-8151-5.

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Maciunas, Robert J. Neural prostheses. Edited by AANS Publications Committee. Rolling Meadows, Ill: American Association of Neurological Surgeons, 2000.

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Maciunas, Robert J. Neural prostheses. Edited by AANS Publications Committee. Rolling Meadows, Ill: American Association of Neurological Surgeons, 2000.

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1925-, Agnew William F., and McCreery Douglas B, eds. Neural prostheses: Fundamental studies. Englewood Cliffs, N.J: Prentice Hall, 1990.

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D, Zhou David, and Greenbaum Elias S, eds. Implantable neural prostheses 1: Devices and applications. Dordrecht: Springer, 2009.

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1940-, Stein Richard B., Peckham P. Hunter, and Popović Dejan, eds. Neural prostheses: Replacing motor function after disease or disability. New York: Oxford University Press, 1992.

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Chapin, John K., Ph. D. and Moxon Karen A, eds. Neural prostheses for restoration of sensory and motor function. Boca Raton: CRC Press, 2001.

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Hans-Werner, Bothe, Samii Madjid, Eckmiller Rolf 1942-, and International Workshop on Neurobionics (1st : 1992 : Goslar, Germany), eds. Neurobionics: An interdisciplinary approach to substitute impaired functions of the human nervous system. Amsterdam: North-Holland, 1993.

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Dössel, Olaf. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany: Vol. 25/4 Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2009.

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Selzer, Michael E. Textbook of neural repair and rehabilitation: Medical neurorehabilitation. Cambridge: Cambridge University Press, 2006.

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Części książek na temat "Neural prosthesis"

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Weiland, James, and Mark S. Humayun. "Retinal Prosthesis." In Neural Engineering, 567–80. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43395-6_20.

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Weiland, James, and Mark Humayun. "Retinal Prosthesis." In Neural Engineering, 635–55. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-5227-0_15.

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Brindley, G. S. "Blindness, Neural Prosthesis." In Sensory System I, 5. Boston, MA: Birkhäuser Boston, 1988. http://dx.doi.org/10.1007/978-1-4899-6647-6_3.

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Weitz, Andrew C., and James D. Weiland. "Visual Prostheses." In Neural Computation, Neural Devices, and Neural Prosthesis, 157–88. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-8151-5_7.

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Thotahewa, Kasun M. S., Ahmed I. Al-Kalbani, Jean-Michel Redouté, and Mehmet Rasit Yuce. "Electromagnetic Effects of Wireless Transmission for Neural Implants." In Neural Computation, Neural Devices, and Neural Prosthesis, 1–22. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-8151-5_1.

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Bazopoulou, Daphne, and Nikos Chronis. "Microfluidics for Neuronal Imaging." In Neural Computation, Neural Devices, and Neural Prosthesis, 243–59. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-8151-5_10.

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Stanaćević, M., Y. Lin, and E. Salman. "Analysis and Design of 3-D Potentiostat for Deep Brain Implantable Devices." In Neural Computation, Neural Devices, and Neural Prosthesis, 261–87. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-8151-5_11.

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Chan, Rosa H. M., Terrence Mak, and Chung Tin. "Computational Models and Hardware Implementations for Real-Time Neuron–Machine Interactions." In Neural Computation, Neural Devices, and Neural Prosthesis, 289–311. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-8151-5_12.

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Ho, John S., Alexander J. Yeh, Sanghoek Kim, and Ada S. Y. Poon. "Wireless Powering for Miniature Implantable Systems." In Neural Computation, Neural Devices, and Neural Prosthesis, 313–33. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-8151-5_13.

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Zhao, Qi, and Christof Koch. "Advances in Learning Visual Saliency: From Image Primitives to Semantic Contents." In Neural Computation, Neural Devices, and Neural Prosthesis, 335–60. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-8151-5_14.

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Streszczenia konferencji na temat "Neural prosthesis"

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Micera, Silvestro, Jack DiGiovanna, Alain Berthoz, Andreas Demosthenous, Jean-Philippe Guyot, Klaus-Peter Hoffmann, Daniel Merfeld, and Manfred Morari. "A closed-loop neural prosthesis for vestibular disorders." In 2010 10th Symposium on Neural Network Applications in Electrical Engineering (NEUREL 2010). IEEE, 2010. http://dx.doi.org/10.1109/neurel.2010.5644048.

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Yoo, P. B., and D. M. Durand. "Neural Prosthesis for Obstructive Sleep Apnea." In 2005 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2005. http://dx.doi.org/10.1109/iembs.2005.1615664.

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Tanaka, Martin L., Premkumar Subbukutti, David Hudson, Kimberly Hudson, Pablo Valenzuela, and Paul Yanik. "Quantifying the Accuracy of a Motion Detecting Neural Prosthesis." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23219.

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Abstract The neural prosthesis under development is designed to improve gait in people with muscle weakness. The strategy is to augment impaired or damaged neural connections between the brain and the muscles that control walking. This third-generation neural prosthesis contains triaxial inertial measurement units (IMUs - accelerometers, gyroscopes, and processing chip) to measure body segment position and force sensitive resistors placed under the feet to detect ground contact. A study was conducted to compare the accuracy of the neural prosthesis using a traditional camera motion capture sys
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Grossman, N., K. Nikolic, V. Poher, B. McGovern, E. Drankasis, M. Neil, C. Toumazou, and P. Degenaar. "Photostimulator for optogenetic retinal prosthesis." In 2009 4th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2009. http://dx.doi.org/10.1109/ner.2009.5109236.

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Osiceanu, Sanda, Monica Dascalu, Eduard Franti, and Adrian Barbilian. "Intelligent interfaces for locomotory prosthesis." In 2009 International Joint Conference on Neural Networks (IJCNN 2009 - Atlanta). IEEE, 2009. http://dx.doi.org/10.1109/ijcnn.2009.5178856.

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Ohta, J., T. Tokuda, K. Kagawa, A. Uehara, Y. Terasawa, K. Nakauchi, T. Fujikado, and Y. Tano. "Si-LSI Based Stimulators for Retinal Prosthesis." In 2007 International Joint Conference on Neural Networks. IEEE, 2007. http://dx.doi.org/10.1109/ijcnn.2007.4371397.

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Benitez Lopez, Mario A., Carlos Rodriguez, and Jonathan Camargo. "Real Time Pattern Recognition for Prosthetic Hand." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11788.

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Abstract Control of prosthetic hands is still an open problem, currently, commercial prostheses use direct myoelectric control for this purpose. However, as mechanical design advances, more dexterous prostheses with more degrees of freedom (DOF) are created, then a more precise control is required. State of the art has focused in the use of pattern recognition as a control strategy with promising results. Studies have shown similar results to classic control strategies with the advantage of being more intuitive for the user. Many works have tried to find the algorithms that best follows the us
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Huang, Ray, Changlin Pang, Yu-Chong Tai, Jeremy Emken, Cevat Ustun, and Richard Andersen. "Parylene coated silicon probes for neural prosthesis." In 2008 3rd IEEE International Conference on Nano/Micro Engineered and Molecular Systems. IEEE, 2008. http://dx.doi.org/10.1109/nems.2008.4484478.

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Torikai, Hiroyuki, and Sho Hashimoto. "Nonlinear dynamical system approaches towards neural prosthesis." In INTERNATIONAL CONFERENCE ON APPLICATIONS IN NONLINEAR DYNAMICS (ICAND 2010). AIP, 2011. http://dx.doi.org/10.1063/1.3574846.

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Jegadeesan, Rangarajan, Nitish V. Thakor, and Shih Cheng Yen. "Wireless for peripheral nerve prosthesis and safety." In 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2015. http://dx.doi.org/10.1109/ner.2015.7146706.

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Raporty organizacyjne na temat "Neural prosthesis"

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Shenoy, Krishna. Toward Neural Control of Prosthetic Devices. Fort Belvoir, VA: Defense Technical Information Center, May 2007. http://dx.doi.org/10.21236/ada468691.

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Weber, Douglas J. A New Animal Model for Developing a Somatosensory Neural Interface for Prosthetic Limbs. Fort Belvoir, VA: Defense Technical Information Center, February 2008. http://dx.doi.org/10.21236/ada482995.

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