Relevant bibliographies by topics / Neuroengineering applications

Academic literature on the topic 'Neuroengineering applications'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Neuroengineering applications"

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Henniquau, D., C. Vanbesien-Mailliot, P. Falez, P. Devienne, A. Vlandas, A. Cappy, and V. Hoel. "Les systèmes neuroinspirés appliqués à la vision artificielle : pédagogie et interdisciplinarité." J3eA 21 (2022): 1023. http://dx.doi.org/10.1051/j3ea/20221023.

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Le traitement neuroinspiré de l’information et le domaine des neurobiosystèmes sont deux pans de la recherche à fort potentiel de développement. Appliquées au domaine de la vision artificielle, elles visent au développement de nouvelles applications comme la conception d’implants rétiniens et/ou de caméras « intelligentes ». Des actions sont menées dans le domaine de la médiation scientifique et de la formation, au travers d’un stand à l’Xpérium et le développement d’une nouvelle unité d’enseignement (UE) appelée « Neuroengineering », intégrée au parcours de formation du Master « Biotechnologies » proposé à l’université de Lille. Le stand présenté à l’Xpérium montre à des jeunes lycéens et étudiants que l’utilisation d’architectures neuroinspirées dans un système de vision artificielle doit conduire à une forte amélioration des performances associée à une réduction de la consommation énergétique. Il s’agit d’une expérience pédagogique innovante auprès des jeunes générations montrant les enjeux des activités de recherche en construction dans les laboratoires. Pour l’UE Neuroengineering, les sujets abordés en séance permettent d’amener les étudiants vers la compréhension des Trends and challenges in neuroengineering (1), notamment en posant la question du développement de neuroprothèses électroniques intelligentes permettant une communication bidirectionnelle entre des neurones vivants et artificiels.
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Tiwari, Ashish, Raj Kumar, Orit Shefi, and Jaspreet Kaur Randhawa. "Fluorescent Mantle Carbon Coated Core–Shell SPIONs for Neuroengineering Applications." ACS Applied Bio Materials 3, no. 7 (June 23, 2020): 4665–73. http://dx.doi.org/10.1021/acsabm.0c00582.

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Monaco, Antonina M., and Michele Giugliano. "Carbon-based smart nanomaterials in biomedicine and neuroengineering." Beilstein Journal of Nanotechnology 5 (October 23, 2014): 1849–63. http://dx.doi.org/10.3762/bjnano.5.196.

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The search for advanced biomimetic materials that are capable of offering a scaffold for biological tissues during regeneration or of electrically connecting artificial devices with cellular structures to restore damaged brain functions is at the forefront of interdisciplinary research in materials science. Bioactive nanoparticles for drug delivery, substrates for nerve regeneration and active guidance, as well as supramolecular architectures mimicking the extracellular environment to reduce inflammatory responses in brain implants, are within reach thanks to the advancements in nanotechnology. In particular, carbon-based nanostructured materials, such as graphene, carbon nanotubes (CNTs) and nanodiamonds (NDs), have demonstrated to be highly promising materials for designing and fabricating nanoelectrodes and substrates for cell growth, by virtue of their peerless optical, electrical, thermal, and mechanical properties. In this review we discuss the state-of-the-art in the applications of nanomaterials in biological and biomedical fields, with a particular emphasis on neuroengineering.
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Morillas, Christian, Samuel Romero, Antonio Martínez, Francisco Pelayo, Leonardo Reyneri, Markus Bongard, and Eduardo Fernández. "A neuroengineering suite of computational tools for visual prostheses." Neurocomputing 70, no. 16-18 (October 2007): 2817–27. http://dx.doi.org/10.1016/j.neucom.2006.04.017.

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Micera, Silvestro, Dominique M. Durand, and Janos Vrs. "Guest Editorial to the Special Letters Issue on Neuroengineering and Neuroprosthetics: Increasing Basic Understanding of the Nervous System to Develop More Effective Neuroengineering Applications." IEEE Transactions on Biomedical Engineering 56, no. 11 (November 2009): 2689–91. http://dx.doi.org/10.1109/tbme.2009.2034485.

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Panuccio, Gabriella, Marianna Semprini, Lorenzo Natale, Stefano Buccelli, Ilaria Colombi, and Michela Chiappalone. "Progress in Neuroengineering for brain repair: New challenges and open issues." Brain and Neuroscience Advances 2 (January 1, 2018): 239821281877647. http://dx.doi.org/10.1177/2398212818776475.

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Background: In recent years, biomedical devices have proven to be able to target also different neurological disorders. Given the rapid ageing of the population and the increase of invalidating diseases affecting the central nervous system, there is a growing demand for biomedical devices of immediate clinical use. However, to reach useful therapeutic results, these tools need a multidisciplinary approach and a continuous dialogue between neuroscience and engineering, a field that is named neuroengineering. This is because it is fundamental to understand how to read and perturb the neural code in order to produce a significant clinical outcome. Results: In this review, we first highlight the importance of developing novel neurotechnological devices for brain repair and the major challenges expected in the next years. We describe the different types of brain repair strategies being developed in basic and clinical research and provide a brief overview of recent advances in artificial intelligence that have the potential to improve the devices themselves. We conclude by providing our perspective on their implementation to humans and the ethical issues that can arise. Conclusions: Neuroengineering approaches promise to be at the core of future developments for clinical applications in brain repair, where the boundary between biology and artificial intelligence will become increasingly less pronounced.
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Song, Y. K., W. R. Patterson, C. W. Bull, J. Beals, N. Hwang, A. P. Deangelis, C. Lay, et al. "Development of a Chipscale Integrated Microelectrode/Microelectronic Device for Brain Implantable Neuroengineering Applications." IEEE Transactions on Neural Systems and Rehabilitation Engineering 13, no. 2 (June 2005): 220–26. http://dx.doi.org/10.1109/tnsre.2005.848337.

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Curtin, Adrian, and Hasan Ayaz. "Abstract #15: MazeSuite 3: Design, presentation and analysis platform for spatial navigation, cognitive neuroscience and neuroengineering applications." Brain Stimulation 12, no. 2 (March 2019): e6. http://dx.doi.org/10.1016/j.brs.2018.12.022.

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Kim, Sungshin, Thierri Callier, Gregg A. Tabot, Robert A. Gaunt, Francesco V. Tenore, and Sliman J. Bensmaia. "Behavioral assessment of sensitivity to intracortical microstimulation of primate somatosensory cortex." Proceedings of the National Academy of Sciences 112, no. 49 (October 26, 2015): 15202–7. http://dx.doi.org/10.1073/pnas.1509265112.

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Intracortical microstimulation (ICMS) is a powerful tool to investigate the functional role of neural circuits and may provide a means to restore sensation for patients for whom peripheral stimulation is not an option. In a series of psychophysical experiments with nonhuman primates, we investigate how stimulation parameters affect behavioral sensitivity to ICMS. Specifically, we deliver ICMS to primary somatosensory cortex through chronically implanted electrode arrays across a wide range of stimulation regimes. First, we investigate how the detectability of ICMS depends on stimulation parameters, including pulse width, frequency, amplitude, and pulse train duration. Then, we characterize the degree to which ICMS pulse trains that differ in amplitude lead to discriminable percepts across the range of perceptible and safe amplitudes. We also investigate how discriminability of pulse amplitude is modulated by other stimulation parameters—namely, frequency and duration. Perceptual judgments obtained across these various conditions will inform the design of stimulation regimes for neuroscience and neuroengineering applications.
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Kakran, Mitali, and Lin Li. "Carbon Nanomaterials for Drug Delivery." Key Engineering Materials 508 (March 2012): 76–80. http://dx.doi.org/10.4028/www.scientific.net/kem.508.76.

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Carbon Nanotubes (CNTs) and Graphene Have Attracted Tremendous Attention as the Most Promising Carbon Nanomaterials in the 21st Century for a Variety of Applications such as Electronics, Biomedical Engineering, Tissue Engineering, Neuroengineering, Gene Therapy and Biosensor Technology. For the Biomedical Applications, Cnts Have Been Utilized over Existing Drug Delivery Vectors due to their Ability to Cross Cell Membranes Easily and their High Aspect Ratio as Well as High Surface Area, which Provides Multiple Attachment Sites for Drug Targeting. Besides, it Has Also Been Proved that the Functionalization of CNTs May Remarkably Reduce their Cytotoxic Effects and at the Same Time Increase their Biocompatibility. So, the Functionalized CNTs Are Safer than Pristine or Purified CNTs, Thus Offering the Potential Exploitation of Nanotubes for Drug Administration. On the other Hand, More Recently Graphene and its Derivatives Have Been Enormously Investigated in the Biological Applications because of their Biocompatibility, Unique Conjugated Structure, Relatively Low Cost and Availability on both Sides of a Single Sheet for Drug Binding. In Our Study, we Have Covalently Functionalized Multiwalled Carbon Nanotubes (MWCNTs) and Graphene Oxide (GO) with Highly Hydrophilic and Biocompatible Excipients in Order to Increase their Aqueous Solubility and Biocompatibility. Various Excipients Used Were Polyvinyl Alcohol, Pluronic F38, Tween 80 and Maltodextrin. The Poorly Water-Soluble Anticancer Drugs such as, Camptothecin and Ellagic Acid, Were Loaded onto the Functionalized MWCNTs and GO via Non-Covalent Interactions. Furthermore, Drug Loading and Cytotoxic Activity of Drugs Incorporated with the Functionalized MWCNTs and GO as Nanocarriers Were Also Investigated. Drugs Loaded on both Carbon Nanocarriers Exhibited a Higher Cytotoxic Activity than Free Drug. On the other Hand, No Significant Toxicity Was Found even at Higher Concentrations when the Cells Were Incubated with the Functionalized Mwcnts and GO. Therefore, both these Functionalized Carbon Nanomaterials Are Ideal Carriers for Drug Delivery.
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Dissertations / Theses on the topic "Neuroengineering applications"

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McClain, Maxine Alice. "Elastomer-based microcable electrodes for electrophysiological applications." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/39606.

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Compliant microelectrodes have been designed in a microcable geometry that can be used individually or in an array and either as a shank-style electrode or as a string-like electrode that can be threaded around features such as the peripheral nerve. The fabrication process, using spin-cast micromolding (SCuM), is simple and adaptable to different patterns. The microcables were fabricated using polydimethyl siloxane (PDMS) for the insulating substrate and thin-film gold for the conductive element. The thin, metal film and the low tensile modulus of the PDMS substrate created an electrode with a composite tensile modulus lower than other compliant electrodes described in the literature. The gold film increased the composite modulus approximately three-fold compared to the unaltered PDMS. The durability of the electrodes and tolerance for stretch was also tested. The microcables were found to be conductive up to 6% strain and to regain conductivity after release from multiple applications of 200% strain. The tolerance for high-strain shows that the electrodes can be deployed for use and stretched or pulled into place as needed without damaging the conductivity. The microcable electrode recording sites were electrically characterized using frequency-based impedance modeling and were tested for electrophysiological recording using a peripheral nerve preparation. A suitable insertion mechanism was designed to use the microcables as shank-style cortical electrodes. The microcables were coated on one side with fibrin, which, when dry, stiffens the microcables for insertion into cortical tissue. A 28-day implant study testing the inflammatory response to fibrin coated PDMS microcable electrodes showed a positive, but relatively low inflammatory response, as measured by glial fibrillary astrocytic protein (GFAP; indicating activated astrocytes) immediately at the tissue edge of the implant site. The response of the control, silicon shank-style electrodes, was varied, but also trended toward low levels of GFAP expression. The GFAP staining was possibly due to the clearance of the fibrin from the implant site in addition to the presence of the PDMS-based electrode. Implant studies extending beyond 28 days are necessary to determine whether and to what degree the inflammation persists at the implant site of PDMS-based electrodes.
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Guo, Lilin. "A Biologically Plausible Supervised Learning Method for Spiking Neurons with Real-world Applications." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2982.

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Learning is central to infusing intelligence to any biologically inspired system. This study introduces a novel Cross-Correlated Delay Shift (CCDS) learning method for spiking neurons with the ability to learn and reproduce arbitrary spike patterns in a supervised fashion with applicability tospatiotemporalinformation encoded at the precise timing of spikes. By integrating the cross-correlated term,axonaland synapse delays, the CCDS rule is proven to be both biologically plausible and computationally efficient. The proposed learning algorithm is evaluated in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification performance. The results indicate that the proposed CCDS learning rule greatly improves classification accuracy when compared to the standards reached with the Spike Pattern Association Neuron (SPAN) learning rule and the Tempotron learning rule. Network structureis the crucial partforany application domain of Artificial Spiking Neural Network (ASNN). Thus, temporal learning rules in multilayer spiking neural networks are investigated. As extensions of single-layer learning rules, the multilayer CCDS (MutCCDS) is also developed. Correlated neurons are connected through fine-tuned weights and delays. In contrast to the multilayer Remote Supervised Method (MutReSuMe) and multilayertempotronrule (MutTmptr), the newly developed MutCCDS shows better generalization ability and faster convergence. The proposed multilayer rules provide an efficient and biologically plausible mechanism, describing how delays and synapses in the multilayer networks are adjusted to facilitate learning. Interictalspikes (IS) aremorphologicallydefined brief events observed in electroencephalography (EEG) records from patients with epilepsy. The detection of IS remains an essential task for 3D source localization as well as in developing algorithms for seizure prediction and guided therapy. In this work, we present a new IS detection method using the Wavelet Encoding Device (WED) method together with CCDS learning rule and a specially designed Spiking Neural Network (SNN) structure. The results confirm the ability of such SNN to achieve good performance for automatically detecting such events from multichannel EEG records.
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Yaghouby, Farid. "EXPERIMENTAL-COMPUTATIONAL ANALYSIS OF VIGILANCE DYNAMICS FOR APPLICATIONS IN SLEEP AND EPILEPSY." UKnowledge, 2015. http://uknowledge.uky.edu/cbme_etds/32.

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Epilepsy is a neurological disorder characterized by recurrent seizures. Sleep problems can cooccur with epilepsy, and adversely affect seizure diagnosis and treatment. In fact, the relationship between sleep and seizures in individuals with epilepsy is a complex one. Seizures disturb sleep and sleep deprivation aggravates seizures. Antiepileptic drugs may also impair sleep quality at the cost of controlling seizures. In general, particular vigilance states may inhibit or facilitate seizure generation, and changes in vigilance state can affect the predictability of seizures. A clear understanding of sleep-seizure interactions will therefore benefit epilepsy care providers and improve quality of life in patients. Notable progress in neuroscience research—and particularly sleep and epilepsy—has been achieved through experimentation on animals. Experimental models of epilepsy provide us with the opportunity to explore or even manipulate the sleep-seizure relationship in order to decipher different aspects of their interactions. Important in this process is the development of techniques for modeling and tracking sleep dynamics using electrophysiological measurements. In this dissertation experimental and computational approaches are proposed for modeling vigilance dynamics and their utility demonstrated in nonepileptic control mice. The general framework of hidden Markov models is used to automatically model and track sleep state and dynamics from electrophysiological as well as novel motion measurements. In addition, a closed-loop sensory stimulation technique is proposed that, in conjunction with this model, provides the means to concurrently track and modulate 3 vigilance dynamics in animals. The feasibility of the proposed techniques for modeling and altering sleep are demonstrated for experimental applications related to epilepsy. Finally, preliminary data from a mouse model of temporal lobe epilepsy are employed to suggest applications of these techniques and directions for future research. The methodologies developed here have clear implications the design of intelligent neuromodulation strategies for clinical epilepsy therapy.
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Guduru, Rakesh. "Bionano Electronics: Magneto-Electric Nanoparticles for Drug Delivery, Brain Stimulation and Imaging Applications." FIU Digital Commons, 2013. http://digitalcommons.fiu.edu/etd/979.

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Nanoparticles are often considered as efficient drug delivery vehicles for precisely dispensing the therapeutic payloads specifically to the diseased sites in the patient’s body, thereby minimizing the toxic side effects of the payloads on the healthy tissue. However, the fundamental physics that underlies the nanoparticles’ intrinsic interaction with the surrounding cells is inadequately elucidated. The ability of the nanoparticles to precisely control the release of its payloads externally (on-demand) without depending on the physiological conditions of the target sites has the potential to enable patient- and disease-specific nanomedicine, also known as Personalized NanoMedicine (PNM). In this dissertation, magneto-electric nanoparticles (MENs) were utilized for the first time to enable important functions, such as (i) field-controlled high-efficacy dissipation-free targeted drug delivery system and on-demand release at the sub-cellular level, (ii) non-invasive energy-efficient stimulation of deep brain tissue at body temperature, and (iii) a high-sensitivity contrasting agent to map the neuronal activity in the brain non-invasively. First, this dissertation specifically focuses on using MENs as energy-efficient and dissipation-free field-controlled nano-vehicle for targeted delivery and on-demand release of a anti-cancer Paclitaxel (Taxol) drug and a anti-HIV AZT 5’-triphosphate (AZTTP) drug from 30-nm MENs (CoFe2O4-BaTiO3) by applying low-energy DC and low-frequency (below 1000 Hz) AC fields to separate the functions of delivery and release, respectively. Second, this dissertation focuses on the use of MENs to non-invasively stimulate the deep brain neuronal activity via application of a low energy and low frequency external magnetic field to activate intrinsic electric dipoles at the cellular level through numerical simulations. Third, this dissertation describes the use of MENs to track the neuronal activities in the brain (non-invasively) using a magnetic resonance and a magnetic nanoparticle imaging by monitoring the changes in the magnetization of the MENs surrounding the neuronal tissue under different states. The potential therapeutic and diagnostic impact of this innovative and novel study is highly significant not only in HIV-AIDS, Cancer, Parkinson’s and Alzheimer’s disease but also in many CNS and other diseases, where the ability to remotely control targeted drug delivery/release, and diagnostics is the key.
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Butler, Nickolas Andrew. "Development of a Myoelectric Detection Circuit Platform for Computer Interface Applications." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/1981.

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Personal computers and portable electronics continue to rapidly advance and integrate into our lives as tools that facilitate efficient communication and interaction with the outside world. Now with a multitude of different devices available, personal computers are accessible to a wider audience than ever before. To continue to expand and reach new users, novel user interface technologies have been developed, such as touch input and gyroscopic motion, in which enhanced control fidelity can be achieved. For users with limited-to-no use of their hands, or for those who seek additional means to intuitively use and command a computer, novel sensory systems can be employed that interpret the natural electric signals produced by the human body as command inputs. One of these novel sensor systems is the myoelectric detection circuit, which can measure electromyographic (EMG) signals produced by contracting muscles through specialized electrodes, and convert the signals into a usable form through an analog circuit. With the goal of making a general-purpose myoelectric detection circuit platform for computer interface applications, several electrical circuit designs were iterated using OrCAD software, manufactured using PCB fabrication techniques, and tested with electrical measurement equipment and in a computer simulation. The analog circuit design culminated in a 1.35” x 0.8” manufactured analog myoelectric detection circuit unit that successfully converts a measured EMG input signal from surface skin electrodes to a clean and usable 0-5 V DC output that seamlessly interfaces with an Arduino Leonardo microcontroller for further signal processing and logic operations. Multiple input channels were combined with a microcontroller to create an EMG interface device that was used to interface with a PC, where simulated mouse cursor movement was controlled through the voluntary EMG signals provided by a user. Functional testing of the interface device was performed, which showed a long battery life of 44.6 hours, and effectiveness in using a PC to type with an on-screen keyboard.
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Book chapters on the topic "Neuroengineering applications"

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Liu, Yu-Hang, Yu Xu, and Nitish Thakor. "Photoacoustic Imaging Tools for Neurological Applications." In Handbook of Neuroengineering, 1–47. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-15-2848-4_82-1.

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Shoorangiz, Reza, Stephen J. Weddell, and Richard D. Jones. "EEG-Based Machine Learning: Theory and Applications." In Handbook of Neuroengineering, 1–39. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-2848-4_70-1.

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Seet, Manuel Stephen, and Anastasios Bezerianos. "Neuroscience of Cognitive Functions: From Theory to Applications." In Handbook of Neuroengineering, 1–29. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-15-2848-4_73-2.

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Saponati, M., G. Ceccarelli, E. Cataldo, and A. Mazzoni. "A Simple and Complete Model of Thalamocortical Interactions for Neuroengineering Applications." In Converging Clinical and Engineering Research on Neurorehabilitation III, 58–63. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01845-0_12.

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Reichenbach, Tobias. "Neuroengineering approaches for cognitive hearing technology." In Sensory Systems for Robotic Applications, 201–12. Institution of Engineering and Technology, 2022. http://dx.doi.org/10.1049/pbce097e_ch8.

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Smith, Peter, Richard Sanger, and Mark Messerli. "Principles, Development and Applications of Self-Referencing Electrochemical Microelectrodes to the Determination of Fluxes at Cell Membranes." In Frontiers in Neuroengineering Series, 373–406. CRC Press, 2006. http://dx.doi.org/10.1201/9781420005868.ch18.

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Sabel, Bernhard, Sandra Jobke, Imelda Pasley, and Julia Gudlin. "Application of Neural Plasticity for Vision Restoration after Brain Damage." In Neuroengineering. CRC Press, 2007. http://dx.doi.org/10.1201/9780849381850.ch23.

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"Application of Neural Plasticity for Vision Restoration after Brain Damage." In Neuroengineering, 377–416. CRC Press, 2007. http://dx.doi.org/10.1201/9780849381850-29.

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Angurala, Mohit. "Latest Advancements in Wearable Devices." In Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering, 58–64. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-7433-1.ch003.

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Wearable devices have impacted the daily life of every individual. These devices come with the embedded feature that fits almost within clothes, accessories, or even watches. One of the wearables named “wrist-worn devices” has gained acceptance by the masses among other wearables. Vital information can be easily gathered with the help of such wearables. These are also suitable for myriad applications such as sports, agriculture, medical, and several more. This chapter gives a comprehensive review of wearable computing electronic devices being used in various fields and provides the latest trends in wearables. The main objective of this review is to discuss various challenges that are faced by individuals in using wearables and the latest methods that can overcome these issues. In the modern epoch, wireless wearable devices have gained a lot of importance in various fields such as sports, agriculture, medical, and many more.
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Gulley, Joshua. "Using High-Speed Chronoamperometry with Local Dopamine Application to Assess Dopamine Transporter Function." In Frontiers in Neuroengineering Series, 83–102. CRC Press, 2006. http://dx.doi.org/10.1201/9781420005868.ch6.

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Conference papers on the topic "Neuroengineering applications"

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Wróbel, A., C. Radzewicz, L. Mankiewicz, P. Hottowy, E. Knapska, W. Konopka, E. Kublik, K. Radwańska, W. J. Waleszczyk, and D. K. Wójcik. "Neuroengineering control and regulation of behavior." In Symposium on Photonics Applications in Astronomy, Communications, Industry and High-Energy Physics Experiments, edited by Ryszard S. Romaniuk. SPIE, 2014. http://dx.doi.org/10.1117/12.2075158.

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"SELF-ORGANIZING MAPS AS DATA CLASSIFIERS IN MEDICAL APPLICATIONS." In Special Session on Challenges in Neuroengineering. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003722604220429.

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Di Florio, M., V. Iyer, A. Rajhans, S. Buccelli, and M. Chiappalone. "Model-based online implementation of spike detection algorithms for neuroengineering applications." In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2022. http://dx.doi.org/10.1109/embc48229.2022.9871444.

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Song, Yoon-Kyu, William R. Patterson, Christopher W. Bull, David A. Borton, Yanqiu Li, Arto V. Nurmikko, John D. Simeral, and John P. Donoghue. "A Brain Implantable Microsystem with Hybrid RF/IR Telemetry for Advanced Neuroengineering Applications." In 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2007. http://dx.doi.org/10.1109/iembs.2007.4352319.

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"APPLICATION OF MULTIVARIATE EMPIRICAL MODE DECOMPOSITION FOR CLEANING EYE BLINKS ARTIFACTS FROM EEG SIGNALS." In Special Session on Challenges in Neuroengineering. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003722004550460.

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Yoon-Kyu Song, William R. Patterson, Christopher W. Bull, David A. Borton, Arto V. Nurmikko, John D. Simeral, and John P. Donoghue. "A neural interface microsystem with all optical telemetry for brain implantable neuroengineering application." In 2008 Conference on Lasers and Electro-Optics (CLEO). IEEE, 2008. http://dx.doi.org/10.1109/cleo.2008.4551410.

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Reports on the topic "Neuroengineering applications"

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Semerikov, Serhiy O., Illia O. Teplytskyi, Yuliia V. Yechkalo, and Arnold E. Kiv. Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot. [б. в.], November 2018. http://dx.doi.org/10.31812/123456789/2648.

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The article substantiates the necessity to develop training methods of computer simulation of neural networks in the spreadsheet environment. The systematic review of their application to simulating artificial neural networks is performed. The authors distinguish basic approaches to solving the problem of network computer simulation training in the spreadsheet environment, joint application of spreadsheets and tools of neural network simulation, application of third-party add-ins to spreadsheets, development of macros using the embedded languages of spreadsheets; use of standard spreadsheet add-ins for non-linear optimization, creation of neural networks in the spreadsheet environment without add-ins and macros. After analyzing a collection of writings of 1890-1950, the research determines the role of the scientific journal “Bulletin of Mathematical Biophysics”, its founder Nicolas Rashevsky and the scientific community around the journal in creating and developing models and methods of computational neuroscience. There are identified psychophysical basics of creating neural networks, mathematical foundations of neural computing and methods of neuroengineering (image recognition, in particular). The role of Walter Pitts in combining the descriptive and quantitative theories of training is discussed. It is shown that to acquire neural simulation competences in the spreadsheet environment, one should master the models based on the historical and genetic approach. It is indicated that there are three groups of models, which are promising in terms of developing corresponding methods – the continuous two-factor model of Rashevsky, the discrete model of McCulloch and Pitts, and the discrete-continuous models of Householder and Landahl.
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