962 resultados para IMPLANTED LINBO3
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In this paper we present the initial results using an artificial neural network to predict the onset of Parkinson's Disease tremors in a human subject. Data for the network was obtained from implanted deep brain electrodes. A tuned artificial neural network was shown to be able to identify the pattern of the onset tremor from these real time recordings.
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It is now possible to directly link the human nervous system to a computer and thence onto the Internet. From an electronic and mental viewpoint this means that the Internet becomes an extension of the human nervous system (and vice versa). Such a connection on a regular or mass basis will have far reaching effects for society. In this article the authors discuss their own practical implant self-experimentation, especially insofar as it relates to extending the human nervous system. Trials involving an intercontinental link up are described. As well as technical aspects of the work, social, moral and ethical issues, as perceived by the authors, are weighed against potential technical gains. The authors also look at technical limitations inherent in the co-evolution of Internet implanted individuals as well as the future distribution of intelligence between human and machine.
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This paper discusses the RFID implants for identification via a sensor network. Brain-computer implants linked in to a wireless network. Biometric identification via body sensors is also discussed. The use of a network as a means for remote and distance monitoring of humans opens up a range of potential uses. Where implanted identification is concerned this immediately offers high security access to specific areas by means of only an RFID device. If a neural implant is employed then clearly the information exchanged with a network can take on a much richer form, allowing for identification and response to an individual's needs based on the signals apparent on their nervous system.
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Objective: To assess the usefulness, compatibility, and long-term operability of a microelectrode array into the median nerve of the left arm of a healthy volunteer, including perception of feedback stimulation and operation of an instrumented prosthetic hand. Setting: The study was carried out from March 14 through June 18, 2002, in England and the United States. Results: The blindfolded subject received feedback information, obtained from force and slip sensors on the prosthetic hand, and subsequently used the implanted device to control the hand by applying an appropriate force to g rip an unseen object. Operability was also demonstrated remotely via the Internet, with the subject in New York, NY, and the prosthetic hand in Reading, England. Finally, the subject was able to control an electric wheelchair, via decoded signals from the implant device, to select the direction of travel by opening and closing his hand. The implantation did not result in infection or any perceivable loss of hand sensation or motion control. The implant was finally extracted because of mechanical fatigue of the percutaneous connection. Further testing after extraction has not indicated any measurable long-term defects in the subject. Conclusions: This implant may allow recipients to have abilities they would otherwise not possess. The response to stimulation improved considerably during the trial, suggesting that the subject learned to process the incoming information more effectively.
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The possibility of using a radial basis function neural network (RBFNN) to accurately recognise and predict the onset of Parkinson’s disease tremors in human subjects is discussed in this paper. The data for training the RBFNN are obtained by means of deep brain electrodes implanted in a Parkinson disease patient’s brain. The effectiveness of a RBFNN is initially demonstrated by a real case study.
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Deep Brain Stimulation (DBS) has been successfully used throughout the world for the treatment of Parkinson's disease symptoms. To control abnormal spontaneous electrical activity in target brain areas DBS utilizes a continuous stimulation signal. This continuous power draw means that its implanted battery power source needs to be replaced every 18–24 months. To prolong the life span of the battery, a technique to accurately recognize and predict the onset of the Parkinson's disease tremors in human subjects and thus implement an on-demand stimulator is discussed here. The approach is to use a radial basis function neural network (RBFNN) based on particle swarm optimization (PSO) and principal component analysis (PCA) with Local Field Potential (LFP) data recorded via the stimulation electrodes to predict activity related to tremor onset. To test this approach, LFPs from the subthalamic nucleus (STN) obtained through deep brain electrodes implanted in a Parkinson patient are used to train the network. To validate the network's performance, electromyographic (EMG) signals from the patient's forearm are recorded in parallel with the LFPs to accurately determine occurrences of tremor, and these are compared to the performance of the network. It has been found that detection accuracies of up to 89% are possible. Performance comparisons have also been made between a conventional RBFNN and an RBFNN based on PSO which show a marginal decrease in performance but with notable reduction in computational overhead.
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I was born human. But this was an accident of fate - a condition merely of time and place. I believe it's something we have the power to change. I will tell you why. In August 1998, a silicon chip was implanted in my arm, allowing a computer to monitor me as I moved through the halls and offices of the Department of Cybernetics at the University of Reading, just west of London, where I've been a professor since 1988. My implant communicated via radio waves with a network of antennas throughout the department that in turn transmitted the signals to a computer programmed to respond to my actions. At the main entrance, a voice box operated by the computer said "Hello" when I entered; the computer detected my progress through the building, opening the door to my lab for me as I approached it and switching on the lights. For the nine days the implant was in place, I performed seemingly magical acts simply by walking in a particular direction. The aim of this experiment was to determine whether information could be transmitted to and from an implant. Not only did we succeed, but the trial demonstrated how the principles behind cybernetics could perform in real-life applications.
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Deep Brain Stimulation (DBS) is a treatment routinely used to alleviate the symptoms of Parkinson's disease (PD). In this type of treatment, electrical pulses are applied through electrodes implanted into the basal ganglia of the patient. As the symptoms are not permanent in most patients, it is desirable to develop an on-demand stimulator, applying pulses only when onset of the symptoms is detected. This study evaluates a feature set created for the detection of tremor - a cardinal symptom of PD. The designed feature set was based on standard signal features and researched properties of the electrical signals recorded from subthalamic nucleus (STN) within the basal ganglia, which together included temporal, spectral, statistical, autocorrelation and fractal properties. The most characterized tremor related features were selected using statistical testing and backward algorithms then used for classification on unseen patient signals. The spectral features were among the most efficient at detecting tremor, notably spectral bands 3.5-5.5 Hz and 0-1 Hz proved to be highly significant. The classification results for determination of tremor achieved 94% sensitivity with specificity equaling one.
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Interdigestive intestinal motility, and especially phase III of the migrating myoelectric/motor complex (MMC), is responsible for intestinal clearance and plays an important role in prevention of bacterial overgrowth and translocation in the gut. Yet previous results from gnotobiotic rats have shown that intestinal microflora can themselves affect the characteristics of the myoelectric activity of the gut during the interdigestive state. Given that the composition of the intestinal microflora can be altered by dietary manipulations, we investigated the effect of supplementation of the diet with synbiotics on intestinal microflora structure and the duodenojejunal myoelectric activity in the rat. To reduce animal distress caused by restraint and handling, which can itself affect GI motility, we applied radiotelemetry for duodenojejunal EMG recordings in conscious, freely moving rats. Thirty 16-month-old Spraque-Dawley rats were used. The diet for 15 rats (E group) was supplemented with chicory inulin, Lactobacillus rhamnosus and Bifidobacterium lactis. The remaining 15 rats were fed control diet without supplements (C group). Three rats from each group were implanted with three bipolar electrodes positioned at 2, 14 and 28 cm distal to the pylorus. After recovery, two 6 h recordings of duodenojejunal EMG were carried out on each operated rat. Subsequently, group C rats received feed supplements and group E rats received only control diet for 1 week, and an additional two 6 h recordings were carried out on each of these rats. Non-operated C and E rats were killed and samples of GI tract were collected for microbiological analyses. Supplementation of the diet with the pro- and prebiotics mixture increased the number of bifidobacteria, whereas it decreased the number of enterobacteria in jejunum, ileum, caecum and colon. In both caecum and colon, the dietary supplementation increased the number of total anaerobes and lactobacilli. Treatment with synbiotics increased occurrence of phase III of the MMC at all three levels of the small intestine. The propagation velocity of phase III in the whole recording segment was also increased from 3.7 +/- 0.2 to 4.4 +/- 0.2 cm min(-1) by dietary treatment. Treatment with synbiotics increased the frequency of response potentials of the propagated phase III of the MMC at both levels of the jejunum, but not in the duodenum. In both parts of the jejunum, the supplementation of the diet significantly decreased the duration of phase II of the MMC, while it did not change the duration of phase I and phase III. Using the telemetry technique it was demonstrated that changes in the gastrointestinal microflora exhibited an intestinal motility response and, more importantly, that such changes can be initiated by the addition of synbiotics to the diet.
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Experiments demonstrating human enhancement through the implantation of technology in healthy humans have been performed for over a decade by some academic research groups. More recently, technology enthusiasts have begun to realize the potential of implantable technology such as glass capsule RFID transponders. In this paper it is argued that implantable RFID devices have evolved to the point whereby we should consider the devices themselves as simple computers. Presented here is the infection with a computer virus of an RFID device implanted in a human. Coupled with our developing concept of what constitutes the human body and its boundaries, it is argued that this study has given rise to the world’s first human infected with a computer virus. It has taken the wider academic community some time to agree that meaningful discourse on the topic of implantable technology is of value. As developments in medical technologies point to greater possibilities for enhancement, this shift in thinking is not too soon in coming.
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This paper explores the development of multi-feature classification techniques used to identify tremor-related characteristics in the Parkinsonian patient. Local field potentials were recorded from the subthalamic nucleus and the globus pallidus internus of eight Parkinsonian patients through the implanted electrodes of a Deep brain stimulation (DBS) device prior to device internalization. A range of signal processing techniques were evaluated with respect to their tremor detection capability and used as inputs in a multi-feature neural network classifier to identify the activity of Parkinsonian tremor. The results of this study show that a trained multi-feature neural network is able, under certain conditions, to achieve excellent detection accuracy on patients unseen during training. Overall the tremor detection accuracy was mixed, although an accuracy of over 86% was achieved in four out of the eight patients.
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Detailed understanding of the haemodynamic changes that underlie non-invasive neuroimaging techniques such as blood oxygen level dependent functional magnetic resonance imaging is essential if we are to continue to extend the use of these methods for understanding brain function and dysfunction. The use of animal and in particular rodent research models has been central to these endeavours as they allow in-vivo experimental techniques that provide measurements of the haemodynamic response function at high temporal and spatial resolution. A limitation of most of this research is the use of anaesthetic agents which may disrupt or mask important features of neurovascular coupling or the haemodynamic response function. In this study we therefore measured spatiotemporal cortical haemodynamic responses to somatosensory stimulation in awake rats using optical imaging spectroscopy. Trained, restrained animals received non-noxious stimulation of the whisker pad via chronically implanted stimulating microwires whilst optical recordings were made from the contralateral somatosensory cortex through a thin cranial window. The responses we measure from un-anaesthetised animals are substantially different from those reported in previous studies which have used anaesthetised animals. These differences include biphasic response regions (initial increases in blood volume and oxygenation followed by subsequent decreases) as well as oscillations in the response time series of awake animals. These haemodynamic response features do not reflect concomitant changes in the underlying neuronal activity and therefore reflect neurovascular or cerebrovascular processes. These hitherto unreported hyperemic response dynamics may have important implications for the use of anaesthetised animal models for research into the haemodynamic response function.
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The experiments were designed to evaluate the biocompatibility of a plastically compressed collagen scaffold (PCCS). The ultrastructure of the PCCS was observed via scanning electron microscopy. Twenty New Zealand white rabbits were randomly divided into experimental and control groups that received corneal pocket transplantation with PCCS and an amniotic membrane, respectively. And the contralateral eye of the implanted rabbit served as the normal group. On the 1st, 7th, 14th, 21st, 30th, 60th, 90th, and 120th postoperative day, the eyes were observed via a slit lamp. On the 120th postoperative day, the rabbit eyes were enucleated to examine the tissue compatibility of the implanted stroma. The PCCS was white and translucent. The scanning electron microscopy results showed that fibers within the PCCS were densely packed and evenly arranged. No edema, inflammation, or neovascularization was observed on ocular surface under a slit lamp and few lymphocytes were observed in the stroma of rabbit cornea after histological study. In conclusion, the PCCS has extremely high biocompatibility and is a promising corneal scaffold for an artificial cornea. (c) 2013 Wiley Periodicals, Inc. J Biomed Mater Res Part A, 2013.
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A severe complication of spinal cord injury is loss of bladder function (neurogenic bladder), which is characterized by loss of bladder sensation and voluntary control of micturition (urination), and spontaneous hyperreflexive voiding against a closed sphincter (detrusor-sphincter dyssynergia). A sacral anterior root stimulator at low frequency can drive volitional bladder voiding, but surgical rhizotomy of the lumbosacral dorsal roots is needed to prevent spontaneous voiding and dyssynergia. However, rhizotomy is irreversible and eliminates sexual function, and the stimulator gives no information on bladder fullness. We designed a closed-loop neuroprosthetic interface that measures bladder fullness and prevents spontaneous voiding episodes without the need for dorsal rhizotomy in a rat model. To obtain bladder sensory information, we implanted teased dorsal roots (rootlets) within the rat vertebral column into microchannel electrodes, which provided signal amplification and noise suppression. As long as they were attached to the spinal cord, these rootlets survived for up to 3 months and contained axons and blood vessels. Electrophysiological recordings showed that half of the rootlets propagated action potentials, with firing frequency correlated to bladder fullness. When the bladder became full enough to initiate spontaneous voiding, high-frequency/amplitude sensory activity was detected. Voiding was abolished using a high-frequency depolarizing block to the ventral roots. A ventral root stimulator initiated bladder emptying at low frequency and prevented unwanted contraction at high frequency. These data suggest that sensory information from the dorsal root together with a ventral root stimulator could form the basis for a closed-loop bladder neuroprosthetic. Copyright © 2013, American Association for the Advancement of Science
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Human ICT implants, such as RFID implants, cochlear implants, cardiac pacemakers, Deep Brain Stimulation, bionic limbs connected to the nervous system, and networked cognitive prostheses, are becoming increasingly complex. With ever-growing data processing functionalities in these implants, privacy and security become vital concerns. Electronic attacks on human ICT implants can cause significant harm, both to implant subjects and to their environment. This paper explores the vulnerabilities which human implants pose to crime victimisation in light of recent technological developments, and analyses how the law can deal with emerging challenges of what may well become the next generation of cybercrime: attacks targeted at technology implanted in the human body. After a state-of-the-art description of relevant types of human implants and a discussion how these implants challenge existing perceptions of the human body, we describe how various modes of attacks, such as sniffing, hacking, data interference, and denial of service, can be committed against implants. Subsequently, we analyse how these attacks can be assessed under current substantive and procedural criminal law, drawing on examples from UK and Dutch law. The possibilities and limitations of cybercrime provisions (eg, unlawful access, system interference) and bodily integrity provisions (eg, battery, assault, causing bodily harm) to deal with human-implant attacks are analysed. Based on this assessment, the paper concludes that attacks on human implants are not only a new generation in the evolution of cybercrime, but also raise fundamental questions on how criminal law conceives of attacks. Traditional distinctions between physical and non-physical modes of attack, between human bodies and things, between exterior and interior of the body need to be re-interpreted in light of developments in human implants. As the human body and technology become increasingly intertwined, cybercrime legislation and body-integrity crime legislation will also become intertwined, posing a new puzzle that legislators and practitioners will sooner or later have to solve.