1,161 research outputs found

    Neuro-electronic technology in medicine and beyond

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    This dissertation looks at the technology and social issues involved with interfacing electronics directly to the human nervous system, in particular the methods for both reading and stimulating nerves. The development and use of cochlea implants is discussed, and is compared with recent developments in artificial vision. The final sections consider a future for non-medicinal applications of neuro-electronic technology. Social attitudes towards use for both medicinal and non-medicinal purposes are discussed, and the viability of use in the latter case assessed

    Neuromorphic hardware for somatosensory neuroprostheses

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    In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies

    Feasibility study of a permanently implanted prosthetic hand

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    The feasibility of a permanently implanted prosthetic hand was evaluated from both an internal biocompatibility and exterior mechanics point of view. A literature review of the issues involved in permanent implantation of a percutanious device was performed in the areas of bone interaction and fixation and neural interface control. A theoretical implant was designed for a 90th percentile male, using an HA-G-Ti composite material to provide a permanent base to which the hand could attach. Using a radial implant length of 1.87 inches and an ulna implant length of 1.32 inches, the simulated implant could withstand a push out force of 10,260 pounds. Using nerve guidance channels and micro-electrode arrays, a Regenerative Neural Interface was postulated to control the implant. The use of Laminin-5 was suggested as a method of preventing the lack of wound closure observed in percutaneous devices. The exterior portion of a permanent artificial hand was analyzed by the construction of a robotic hand optimized for weight, size, grip force and wrist torque, power consumption and range of motion. Using a novel dual drive system, each finger was equipped with both joint position servos as well as a tendon. Fine grip shape was formed using the servos, while the tendon was pulled taunt when grasping an object. Control of the prosthetic was performed using a distributed network of micro-controllers. Each finger\u27s behavior was governed by a master/slave system where input from a control glove was processed by a master controller with joint servo and tendon instructions passed to lower-level controllers for management of hand actuators. The final weight of the prototype was 3.85 pounds and was approximately 25% larger than the 90th percentile male hand it was based on. Grip force was between 1.25 and 2 pounds per finger, depending on amount of finger flexion with a wrist lifting capacity of 1.2 pounds at the center of the palm. The device had an average current draw of 3 amps in both normal operation and tight grasping. Range of motion was similar to that of the human model. Overall feasibility is examined and factors involved in industrial implementation are also discussed

    Low-Power Circuits for Brain–Machine Interfaces

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    This paper presents work on ultra-low-power circuits for brain–machine interfaces with applications for paralysis prosthetics, stroke, Parkinson’s disease, epilepsy, prosthetics for the blind, and experimental neuroscience systems. The circuits include a micropower neural amplifier with adaptive power biasing for use in multi-electrode arrays; an analog linear decoding and learning architecture for data compression; low-power radio-frequency (RF) impedance-modulation circuits for data telemetry that minimize power consumption of implanted systems in the body; a wireless link for efficient power transfer; mixed-signal system integration for efficiency, robustness, and programmability; and circuits for wireless stimulation of neurons with power-conserving sleep modes and awake modes. Experimental results from chips that have stimulated and recorded from neurons in the zebra finch brain and results from RF power-link, RF data-link, electrode- recording and electrode-stimulating systems are presented. Simulations of analog learning circuits that have successfully decoded prerecorded neural signals from a monkey brain are also presented

    Index to NASA Tech Briefs, 1975

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    This index contains abstracts and four indexes--subject, personal author, originating Center, and Tech Brief number--for 1975 Tech Briefs

    Nanochips and medical applications

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    Ο όρος «νανοτσιπ» αναφέρεται σε ένα ολοκληρωμένο κύκλωμα (τσιπ) με νανοϋλικά και δομές στη νανοκλίμακα (1-100nm). Ένα ολοκληρωμένο κύκλωμα είναι μια συλλογή ηλεκτρονικών εξαρτημάτων, όπως τρανζίστορ, δίοδοι, πυκνωτές και αντιστάσεις. Τα σημερινά τρανζίστορ είναι στη νανοκλίμακα, αλλά μπορούν να τροποποιηθούν με νανοδομές για την κατασκευή βιοαισθητήρων που μπορούν να πραγματοποιούν ανίχνευση βιομορίων, όπως ιόντα, μόρια DNA, αντισώματα και αντιγόνα με μεγάλη ευαισθησία. Υλικά και Μέθοδοι: Πραγματοποιήθηκε συστηματική αναζήτηση βιβλιογραφίας με χρήση των ηλεκτρονικών βάσεων δεδομένων PubMed, Google Scholar και Scopus για την ανάπτυξη και χρήση νανοτσίπ σε ιατρικές εφαρμογές. Για τον προσδιορισμό των σχετικών εργασιών, τα κριτήρια συμπερίληψης αναφέρονται σε άρθρα στην αγγλική γλώσσα, άρθρα βιβλιογραφικού περιεχομένου ή/και έρευνών. Τα κριτήρια αποκλεισμού ήταν άρθρα εφημερίδων, περιλήψεις συνεδρίων και επιστολές. Αποτελέσματα: Τεχνικές in-vivo και in-vitro έχουν χρησιμοποιηθεί για την ανίχνευση μορίων DNA, ιόντων, αντισωμάτων, σημαντικών πρωτεϊνών και καρκινικών δεικτών, όχι μόνο από δείγματα αίματος αλλά και από ιδρώτα, σάλιο και άλλα βιολογικά υγρά. Διαγνωστική εφαρμογή των νανοτσίπ αποτελεί και η ανίχνευση πτητικών οργανικών ενώσεων μέσω τεστ εκπνεόμενης αναπνοής. Υπάρχουν και αρκετές θεραπευτικές εφαρμογές αυτών των συσκευών ημιαγωγών όπως τσιπ διασύνδεσης εγκεφάλου-υπολογιστή για παραλυτικές ή επιληπτικές καταστάσεις, κατασκευή «βιονικών» οργάνων όπως τεχνητός αμφιβληστροειδής, τεχνητό δέρμα και ρομποτικά προθετικά άκρα για ακρωτηριασμένους ή ρομποτική χειρουργική. Συμπέρασμα: Η χρήση των νανοτσίπ στην ιατρική είναι ένας αναδυόμενος τομέας με αρκετές θεραπευτικές εφαρμογές όπως η διάγνωση, η παρακολούθηση της υγείας και της φυσικής κατάστασης και η κατασκευή «βιονικών» οργάνων.Background: The term “nanochip” pertains to an integrated circuit (chip) with nanomaterials and components in the nano-dimension (1-100nm). An integrated circuit is essentially a collection of electronic components, like transistors, diodes, capacitors, and resistors. Current transistors are in the nanoscale but can also be modified with nanostructures like nanoribbons and nanowires to manufacture biosensors that can perform label-free, ultrasensitive detection of biomolecules like ions, DNA molecules, antibodies and antigens. Materials and Methods: A systematic literature search was conducted using the electronic databases PubMed, Google Scholar and Scopus for the development and use of nanochips in medical applications. For the identification of relevant papers, the inclusion criteria referred to articles in the English language, review and/or research articles. The exclusion criteria were newspaper articles, conference abstracts and letters. Results: In-vivo and In-vitro techniques have been used for detection of DNA molecules, ions, antibodies, important proteins, and tumor markers, not only from blood samples but also from sweat, saliva and other biological fluids. Another diagnostic application of nanochips is detection of volatile organic compounds via a breath test. There are also several therapeutic applications of these semiconductor devices like brain-computer interface chips for paralytic or epileptic conditions, manufacture of “bionic” organs like artificial retinas, artificial skin and robotic prostheses for amputees or robotic surgery. Conclusion: The use of nanochips in medicine is an emerging field with several therapeutic applications like diagnostics, health and fitness monitoring, and manufacture of “bionic” organs

    Feature extraction using extrema sampling of discrete derivatives for spike sorting in implantable upper-limb neural prostheses

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    Next generation neural interfaces for upper-limb (and other) prostheses aim to develop implantable interfaces for one or more nerves, each interface having many neural signal channels that work reliably in the stump without harming the nerves. To achieve real-time multi-channel processing it is important to integrate spike sorting on-chip to overcome limitations in transmission bandwidth. This requires computationally efficient algorithms for feature extraction and clustering suitable for low-power hardware implementation. This paper describes a new feature extraction method for real-time spike sorting based on extrema analysis (namely positive peaks and negative peaks) of spike shapes and their discrete derivatives at different frequency bands. Employing simulation across different datasets, the accuracy and computational complexity of the proposed method are assessed and compared with other methods. The average classification accuracy of the proposed method in conjunction with online sorting (O-Sort) is 91.6%, outperforming all the other methods tested with the O-Sort clustering algorithm. The proposed method offers a better tradeoff between classification error and computational complexity, making it a particularly strong choice for on-chip spike sorting
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