Relevant bibliographies by topics / Neural prosthesis

Academic literature on the topic 'Neural prosthesis'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 March 2023

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Journal articles on the topic "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 study neurophysiology based on deep neural networks under simulated prosthetic vision. This article uses neurophysiological experiments and mathematical statistical methods to study the vision of simulated prostheses, and test and improve the image processing strategies used to simulate the visual design of prostheses. In this paper, based on the low-pixel image recognition of the simulating irregular phantom view point array, the deep neural network is used in the image processing strategy of prosthetic vision, and the effect of the image processing method on object image recognition is evaluated by the recognition rate. The experimental results show that the recognition rate of the two low-pixel segmentation and low-pixel background reduction methods proposed by the deep neural network under simulated prosthetic vision is about 70%, which can significantly increase the impact of object recognition, thereby improving the overall recognition ability of visual guidance.
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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; the prosthetic then transfers the information to the vestibular nerve via electrical stimulation. Here we present a project overview, development details, and summarize our progress in animal models and selected human volunteers.
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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 prosthesis is considered. The possibilities of using the considered neural network technologies in the mathematical education of engineers are presented. A version of the prosthesis design is proposed. The possibility of constructing the described prosthesis is shown.
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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) pylon into the right distal tibia. The latter pylons provided PNI for connection between a powered sensing transtibial prosthesis and electrodes in residual soleus muscle and on residual distal tibial nerve. If signs of infection were absent 28-70 days after implantation, cats started wearing a passive prosthesis. We recorded and analyzed full-body mechanics of level and slope locomotion in five cats with passive prostheses and in one cat with a powered sensing prosthesis. We also performed histological analyses of tissue integration with the implants in nine cats. Four pigs received SBIPs into the left hindlimb and two pigs—into the left forelimb. We recorded vertical ground reaction forces before amputation and following osseointegration. We also conducted pullout postmortem tests on the implanted pylons. One pig received in dorsum the modified SBIPs with and without silver coating. Results Six cats from the SBIP groups had implant for 70 days. One cat developed infection and did not receive prosthesis. Five cats had pylon for 148 to 183 days, showed substantial loading of the prosthesis during locomotion (40.4% below presurgery control), and demonstrated deep ingrowth of skin and bone tissue into SBIP (over 60%). Seven of eight cats from the SBIP-PNI group demonstrated poor pylon integration without clinical signs of infection. One cat had prosthesis for 824 days (27 months). The use of the bidirectionally controlled prosthesis by this animal during level walking demonstrated increased vertical loading to nearly normal values, although the propulsion force was significantly reduced. From the study on pigs, it was found that symmetry in loading between the intact and prosthetic limbs during locomotion was 80 ± 5.5%. Skin-implant interface was infection-free, but developed a stoma, probably because of the high mobility of the skin and soft tissues in the pig’s thigh. Dorsal implantation resulted in the infection-free deep ingrowth of skin into the SBIP implants. Conclusions Cats with SBIP (n = 5) and SBIP-PNI (n = 1) pylons developed a sound interface with the residuum skin and bone and demonstrated substantial loading of prosthetic limb during locomotion. One animal with SBIP developed infection and seven cats with SBIP-PNI demonstrated poor bone integration without signs of infection. Future studies of the SBIP-PNI should focus on reliability of integration with the residuum. Ongoing study with pigs requires decreasing the extra mobility of skin and soft tissues until the skin seal is developed within the SBIP implant.
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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 individual benefits and drawbacks of each method. Methods: Studies looked at include both primary and secondary sources of research. Identification was via a PubMed search for the terms “prosthetic limb”, “powered prostheses”, “myoelectric prostheses”, “neural interface”, “prosthetic somatosensory feedback”, and “brain-machine interface”, which resulted in a total of 3892 papers retrieved. Of these, 28 were retained as sources for this review. Selection was based on relevance to control of powered prostheses. Summary: Significant strides have been made in expanding the choice of interface sites for bionic prosthesis control. Muscles, nerves, and the brain are all options, each with varying degrees of invasiveness and corresponding resolution of information obtained, and non-muscle interfacing prostheses may soon be commercially available. These advances have allowed for increasingly precise control of prosthetic limbs. However, this is limited by the challenge of returning sensory information from the prosthesis back to the user.
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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 motor cortex (M1) and supplementary motor area (SMA) compared to the TD group, but nonsignificant differences in the primary somatosensory area (S1). Compared to using their non-preferred hand, the TD group exhibited significantly higher action in S1 when using the simulator, but nonsignificant differences in M1 and SMA. The non-significant differences in S1 activation between groups and the increased activation evoked by the simulator’s use may suggest rapid changes in feedback prioritization during tool use. We suggest that prosthetic simulators may elicit increased reliance on proprioceptive and tactile feedback during motor tasks. This knowledge may help to develop future prosthesis rehabilitative training or the improvement of tool-based skills.
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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 damaged hair cells in the auditory system by direct electrical stimulation of the auditory nerve. Stimulating discrete spiral ganglion cell populations in cochlear implant users’ ears is similar to the encoding of small acoustic frequency bands in a normal-hearing person's ear. In contemporary cochlear implants, however, the injected electric current is spread widely along the scala tympani and across turns. Consequently, stimulation of spatially discrete spiral ganglion cell populations is difficult. Methods Spiral ganglion cells in guinea pigs were stimulated with laser pulses from an Aculight Capella infrared laser. Results With our experiments we demonstrate that extreme spatially selective stimulation is possible using light. Conclusion Our long-term goal is to develop and build an optical cochlear implant prosthesis to stimulate small populations of spiral ganglion cells. Significance Our long-term goal is to develop and build an optical cochlear implant prosthesis to stimulate small populations of spiral ganglion cells. Support This project has been funded with federal funds from the National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Department of Health and Human Services, under Contract No. HHSN260-2006-00006-C / NIH No. N01-DC-6-0.
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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 using the prosthesis. We hypothesize that understanding and optimally designing high-performance decoders require an experimental platform where humans are in closed-loop with the various candidate decode systems and algorithms. It remains unexplored the extent to which the subject can, for a particular decode system, algorithm, or parameter, engage feedback and other strategies to improve decode performance. Closed-loop testing may suggest different choices than offline analyses. Here we ask if a healthy human subject, using a closed-loop neural prosthesis driven by synthetic neural activity, can inform system design. We use this online prosthesis simulator (OPS) to optimize “online” decode performance based on a key parameter of a current state-of-the-art decode algorithm, the bin width of a Kalman filter. First, we show that offline and online analyses indeed suggest different parameter choices. Previous literature and our offline analyses agree that neural activity should be analyzed in bins of 100- to 300-ms width. OPS analysis, which incorporates feedback control, suggests that much shorter bin widths (25–50 ms) yield higher decode performance. Second, we confirm this surprising finding using a closed-loop rhesus monkey prosthetic system. These findings illustrate the type of discovery made possible by the OPS, and so we hypothesize that this novel testing approach will help in the design of prosthetic systems that will translate well to human patients.
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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 devices are well established in clinical practice and have become routine, such as cochlear implants. By comparison, other technologies are in experimental phases and still need to be further developed to achieve the desired results.
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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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Dissertations / Theses on the topic "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 form of patterned vision; besides other benefits (independence), this limited vision would let patients distinguish between day and night (resetting their circadian rhythm). This thesis presents the development of the neurostimulator, an interdisciplinary work bridging engineering and medicine. Features of the neurostimulator include: high-voltage CMOS transistors in key circuits, to prevent voltage compliance issues due to an unknown or changing combined tissue and electrode/tissue interface impedance; simultaneous stimulation using current sources and sinks, with return electrodes configured to provide maximum charge containment at each stimulation site; stimuli delivered to a two dimensional mosaic of hexagonally packed electrodes, multiplexing current sources and sinks to allow each electrode in the whole mosaic to become a stimulation site; electrode shorting to remove excess charge accumulated during each stimulation phase. Detailed electrical testing and characterisation verified that the neurostimulator performed as specified, and comparable to, or better than, other vision prostheses neurostimulators. In addition, results from several animal experiments verified that the neurostimulator can elicit electrically evoked visual responses. The features of the neurostimulator enable research into how simultaneous electrical stimulation affects the visual neural pathways; those research results could impact other neural prosthetics research and devices.
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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 total area of 16.8mm2 and exhibits an overall power consumption of 27.2mW. The neural stimulation IC is able to provide biphasic current pulses to stimulate 8 electrodes independently. A voltage booster generates a 17V voltage supply in order to guarantee the programmed stimulation current even in case of high impedances at the electrode-tissue interface in the order of tens of k­. The stimulation patterns, generated by a 5-bit current DAC, are programmable in terms of amplitude, frequency and pulse width. Due to the huge capacitors of the implemented voltage boosters, the stimulation IC has a wider area of 18.6mm2. In addition, a maximum power consumption of 29mW was measured. Successful in-vivo experiments with rats having a TIME electrode implanted in the sciatic nerve were carried out, showing the capability of recording neural signals in the tens of microvolts, with a global noise of 7μVrms , and to selectively elicit the tibial and plantarmuscles using different active sites of the electrode. In order to get a completely implantable interface, a biocompatible and biostable package was designed. It hosts the developed ICs with the minimal electronics required for their proper operation. The package consists of an alumina tube closed at both extremities by two ceramic caps hermetically sealed on it. Moreover, the two caps serve as substrate for the hermetic feedthroughs to enable the device powering and data exchange with the external digital controller implemented on a Field-Programmable Gate Array (FPGA) board. The package has an outer diameter of 7mm and a total length of 26mm. In addition, a humidity and temperature sensor was also included inside the package to allow future hermeticity and life-time estimation tests. Moreover, a wireless, wearable and non-invasive EEG recording system is proposed in order to improve the control over the artificial limb,by integrating the neural signals recorded from the PNS with those directly acquired from the brain. To first investigate the system requirements, a Component-Off-The-Shelf (COTS) device was designed. It includes a low-power 8- channel acquisition module and a Bluetooth (BT) transceiver to transmit the acquired data to a remote platform. It was designed with the aimof creating a cheap and user-friendly system that can be easily interfaced with the nowadays widely spread smartphones or tablets by means of a mobile-based application. The presented system, validated through in-vivo experiments, allows EEG signals recording at different sample rates and with a maximum bandwidth of 524Hz. It was realized on a 19cm2 custom PCB with a maximum power consumption of 270mW.
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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 implant over the scleral surface of the eye could present a safer alternative but this stimulation modality has not been tested in diseased retinas. Additionally, recent research has shown that the adult neocortex retains substantial plasticity following a disruption to its visual input and the potential deterioration in visual capabilities as a result of such experience modification may undermine the overall bionic rescue strategy. Methods. Two animal models mimicking the principal pathologies found in AMD, namely photoreceptor degeneration and reduced retinal ganglion cell mass, were used to evaluate the efficacy of trans-scleral stimulation of the retina by recording electrical evoked potentials in the visual cortex. The visual performance following the loss of pattern vision induced by bilateral eyelid suturing in adult mice was examined by analysing visual evoked potentials. Findings. Spatially differentiated cortical activations were obtained notwithstanding the underlying retinopathy in the experiment animals. The charge density thresholds were found to be similar to controls and below the bioelectric safety limit. After prolonged visual deprivation (weeks) in the mouse, the visual cortical responses evoked by either electrical or photic stimuli were both significantly reduced. An assessment of different visual capabilities using patterned stimuli demonstrated that whilst visual acuity and motion sensitivity were preserved, significant depression in luminance and contrast sensitivities was detected. Conclusion. Trans-scleral stimulation of the retina is a feasible approach for the development of a visual prosthesis. Following visual loss the adult brain exhibits significant experience-dependent modifications. These new insights may force a revision on the current bionic rescue strategy.
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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 deliver the required feedback path for the implantable system with minimum risk. The amount of recorded information can be improved by increasing the number of electrodes within a single cuff known as multi-electrode cuffs (MECs) configuration. This strategy can increase the signal to noise ratio for the recorded signals which have typically very low amplitude (less than 5μV). Consequently multiple high gain amplifiers are used in order to amplify the signals and supply a multi-channel recorded data stream for signal processing or monitoring applications. The signal processing unit within the implantable system or outside the body is employed for classification and sorting the action potential signals (APs) depending on their conduction velocities. This method is called velocity selective recording (VSR). Basically, the idea of this approach is that the conduction velocity of AP can be determined by timing the appearance of the signal at two or more points along the nerve and then dividing the distance between the points by the delay. The purpose of this thesis to investigate an alternative approach using artificial network for APs detection and extraction in neural recording applications to increase the velocity selectivity based on VSR using MECs. The prototype systems impose four major requirements which are high velocity selectivity, small size, low power consumption and high reliability. The proposed method has been developed for applications which require online AP classification. A novel time delay neural network (TDNN) approach is used to decompose the recorded data into several matched velocity bands to allow for individual velocity selectivity at each band to be increased. Increasing the velocity selectivity leads to more accurate recording from the target fibre (or fibres) within the nerve bundle which can be used for applications that require AP classification such as bladder control and the adjustment of foot drop. The TDNN method was developed to obtain more information from an individual cuff without increasing the number of electrodes or the sampling rate. Moreover, the optimization of the hardware implementation for the proposed signal processing method permits savings in power consumption and silicon area. Finally, a nerve signal synthesiser and noise generator for the evaluation of the VSRmethod is described. This system generates multiple artificial AP signals with a time offset between the channels with additive white Gaussian noise (AWGN) to simulate the MEC and hence reduce the cost and the number of the animals required for experimental tests.
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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 review of visual modelling of electrical epiretinal stimulation and analogous acoustic modelling of electrical cochlear stimulation. The latter models involve coloured noise played to normal listeners so as to investigate speech processing and electrode design for use in cochlear implants. Subsequently, four experiments (three psychophysical and one numerical), and two statistical analyses, are presented. Intrinsic signal optical imaging in cerebral cortex is canvassed appendically. The first experiment describes a visual tracking task administered to 20 normal observers afforded simulated prosthetic vision. Fixation, saccade, and smooth pursuit, and the effect of practice, were assessed. Further, an image analysis scheme is demonstrated that, compared to existing approaches, assisted fixation and pursuit (but not saccade) accuracy (35.8% and 6.8%, respectively), and required less phosphene array scanning. Subsequently, (numerical) information-theoretic reasoning is provided for the scheme's superiority. This reasoning was then employed to further optimise the scheme (resulting in a filter comprising overlapping Gaussian kernels), and may be readily extended to arbitrary arrangements of many phosphenes. A face recognition study, wherein stimuli comprised either size- or intensity-modulated phosphenes, is then presented. The study involved unpracticed observers (n=85), and showed no 'size' --versus--'intensity' effect. Overall, a 400-phosphene (100-phosphene) image afforded subjects 89.0% (64.0%) correct recognition (two-interval forced-choice paradigm) when five seconds' scanning was allowed. Performance fell (64.5%) when the 400-phosphene image was stabilised on the retina and presented briefly. Scanning was similar in 400- and 100-phosphene tasks. The final chapter presents the statistical effects of sampling and rendering jitter on the phosphene image. These results may generalise to low-resolution imaging systems involving loosely packed pixels.
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Books on the topic "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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Book chapters on the topic "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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Conference papers on the topic "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 system as a reference. The IMUs were found to accurately represent the amplitude of the gait cycle components and generally track the motion. However, there are some differences in phase, with the IMUs lagging the actual motion. Phase lagged by about 10 degrees in the ankle and by about 5 degrees in the knee. Error of the neural prosthesis varied over the gait cycle. The average error for the ankle, knee and hip were 6°, 8°, and 9°, respectively. Testing showed that the neural prosthesis was able to capture the general shape of the joint angle curves when compared to a commercial camera motion capture system. In the future, measures will be taken to reduce lag in the gyroscope and reduce jitter in the accelerometer so that data from both sensors can be combination to obtain more accurate readings.
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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 user’s intention. However, deployment of these algorithms for real-time classification in a prosthesis has not been widely explored. This paper addresses this problem by deploying and testing in real-time an Artificial Neural Network (ANN). The ANN was trained to classify three different motions: no grasp, precision grasp and power grasp in order to control a two DOF trans-radial prosthetic hand with electromyographic signals acquired from two channels. Static and dynamic tests were made to evaluate the ANN under those conditions, 95% and 81% accuracy scores were reached respectively. Our work shows the potential of pattern recognition algorithms to be deployed in microcontrollers that can fit inside myoelectric prostheses.
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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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Reports on the topic "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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