No description available.

No description available.

Every year, 250,000 people worldwide suffer a spinal cord injury (SCI) that leaves them with chronic paraplegia - permanent loss of ability to move their legs. SCI interrupts axons passing along the spinal cord, thereby isolating motor neurons from brain inputs. To date, there are no effective treatments that can reconnect these interrupted axons. In a recent breakthrough, .NeuroRestore developed the STIMO neuroprosthesis that can restore walking after paralyzing SCI using Epidural Electrical Stimulation (EES) of the lumbar spinal cord. Yet, the calibration of EES requires highly trained personnel and a vast amount of time, and the mechanism by which EES restores movement is not fully understood. In this master thesis, we propose to address this issue using modeling combined with Artificial Neural Networks (ANNs). To do so, we introduce the CyberSpine model to predict EES-induced motor response. The implementation of the model relies on the construction of a multipolar basis of solution of the Poisson equation which is then coupled to an ANN trained against actual data of an implanted STIMO user. Furthermore, we show that our CyberSpine model is particularly well adapted to extract biologically relevant information regarding the efficient connectivity of the patient’s spine. Finally, a user-friendly interactive visualization software is built. / Varje år drabbas 250 000 människor i hela världen av en ryggmärgsskada som ger dem kronisk paraplegi - permanent förlust av förmågan att röra benen. Vid en ryggmärgsskada bryts axonerna som passerar längs ryggmärgen, vilket isolerar de motoriska neuronpoolerna från hjärnans ingångar. Hittills finns det inga effektiva behandlingar som kan återansluta dessa avbrutna axoner. NeuroRestore utvecklade nyligen neuroprotesen STIMO som kan återställa gångförmågan efter förlamande ryggmärgsskada med hjälp av epidural elektrisk stimulering (EES) av ländryggmärgen. Kalibreringen av EES-stimuleringar kräver dock högutbildad personal och mycket tid, och den mekanism genom vilken EES återställer rörelse är inte helt klarlagd. I denna masteruppsats föreslår vi att vi tar itu med denna fråga med hjälp av modellering i kombination med artificiell intelligens. För att göra detta introducerar vi CyberSpine-modellen, en modell som kan förutsäga EES-inducerad motorisk respons. Implementeringen av modellen bygger på konstruktionen av en multipolär bas för lösning av Poisson-ekvationen som sedan kopplas till ett artificiellt neuralt nätverk som tränas mot faktiska data från en implanterad STIMO-deltagare. Dessutom visar vi att vår CyberSpine-modell är särskilt väl anpassad för att extrahera biologiskt relevant information om den effektiva anslutningen av patientens ryggrad. Slutligen bygger vi en användarvänlig interaktiv visualiseringsprogramvara.

This report presents the development, implementation, and testing of a current monitor system that is specifically developed for testing a neuromuscular electrical stimulation system (NMES). The NMES system, developed by KTH and its academic and industrial partners Karolinska institute and Matrix Muscle Support, incorporates advanced features aimed at preventing cardiovascular diseases. The problem statement revolves around the necessity of developing a system capable of detecting any instances of overcurrent or leakage current in the neuromuscular electrical stimulation system. The purpose of this current monitoring system is to offer real-time monitoring of current levels within the electrical stimulation system. The project’s goal is to design and implement a comprehensive software and hardware solution that allows users to simultaneously monitor voltage levels across multiple channels and detect any abnormalities. The project was executed using a top-down approach. Each subtask is processed separately and finally tested to be verified and approved according to the expectations set. Test-driven development (TDD) methodology was employed to ensure the reliability and accuracy of the software and hardware implementation. The project has produced several significant results, the most important of which include the successful implementation of a real-time monitoring system for the multi-channel NMES system. A dedicated circuit board design has been prepared according to the specified requirements described in the report. The software interface has been designed to provide the user with real-time readings of voltage levels as well as visual identification of normal and abnormal values. The measurements carried out during all the tests gave clear answers to the set question, with the exception of some displacement (offset) which can be investigated more closely in future research. Furthermore, the reference images showed that the system was functioning in accordance with its original intended purpose. / Denna rapport presenterar utvecklingen, implementeringen och testningen av ett strömmätningssystem som är speciellt utvecklat för att testa ett neuromuskulärt elektriskt stimuleringssystem (NMES). NMES-systemet, utvecklat av KTH och dess akademiska och industriella partners Karolinska institutet och Matrix Muscle Support, innehåller avancerade funktioner som syftar till att förebygga hjärt-kärlsjukdomar. Problemformuleringen kretsar kring nödvändigheten av att utveckla ett system som kan detektera fall av överström eller läckström i det neuromuskulära elektriska stimuleringssystemet. Syftet med detta strömmätningssystem är att erbjuda realtidsövervakning av strömnivåer inom det elektriska stimuleringssystemet. Projektets mål är att designa och implementera en omfattande mjukvaru- och hårdvarulösning som tillåter användare att samtidigt övervaka spänningsnivåer över flera kanaler och upptäcka eventuella avvikelser. Projektet genomfördes med en top-down-metod. Varje deluppgift bearbetas separat och testas slutligen för att verifieras och godkännas enligt de förväntningar som satts. Testdriven utvecklingsmetod (TDD) användes för att säkerställa tillförlitligheten och noggrannheten hos implementeringen av mjukvara och hårdvara. Projektet har gett flera betydande resultat, av vilka de viktigaste inkluderar framgångsrik implementering av ett realtidsövervakningssystem för flerkanals NMES-systemet. En dedikerad kretskortsdesign har utarbetats enligt de specificerade kraven som beskrivs i rapporten. Mjukvarugränssnittet har utformats för att ge användaren realtidsavläsningar av spänningsnivåer samt visuell identifiering av normala och onormala värden. De mätningar som genomfördes under samtliga tester gav tydliga svar på frågeställningen, med undantag för viss förskjutning (offset) som kan undersökas närmare i framtida forskning. Vidare visade referensbilderna att systemet fungerade i enlighet med det ursprungliga syftet.

No description available.

L'ectrostimulation dite conventionnelle (CONV) est délivrée par des impulsions électriques de basse fréquence (≤ 50 Hz), de courte durée (< 400 μs) et de haute intensité. Ce type d'ESNM permet ainsi d'évoquer une contraction musculaire grâce à l'activation directe des axones moteurs et est associé à une fatigue musculaire exagérée par rapport aux contractions volontaires (VOL). Au contraire, lors de l'utilisation d'impulsions de longues durées (1 ms), de hautes fréquences (≥ 80 Hz) et de faibles intensités (i.e. protocole « Wide-Pulse, High-Frequency » (WPHF)), une partie de la force musculaire évoquée aurait pour origine des mécanismes centraux. En effet, une augmentation de la force produite en réponse à WPHF a été rapportée alors que l'intensité de stimulation était constante. Cette « extra force » (EF) refléterait le recrutement par voie réflexe des motoneurones spinaux. L'objectif de ce travail de thèse était de mieux appréhender les mécanismes neurophysiologiques à l'origine de l'EF et d'évaluer les conséquences métaboliques et corticales du protocole WPHF (1 ms - 100 Hz) par rapport à des protocoles d'exercices VOL et de type CONV (50 μs - 25 Hz). Les réponses musculaires des fléchisseurs plantaires et les réponses cérébrales ont été évalué par résonance magnétique nucléaire (la spectroscopie par résonance magnétique du phosphore 31 du muscle et l'imagerie par résonance magnétique fonctionnelle du cerveau) et électrophysiologie (EMG). Ces résultats constituent une première étape importante vers une meilleure prise en charge des pathologies liées à des atteintes du neuromusculaire. / Conventional neuromuscular electrical stimulation (CONV) is delivered via surface electrodes at short pulse duration (< 400 μs), low frequencies (≤ 50 Hz) and high current intensities. The motor unit recruitment pattern of CONV, however, is different from the pattern of voluntary contractions (VOL) and leads to a hastened onset of muscle fatigue. The use of wide-pulses (1ms), high frequencies (100 Hz) (WPHF) and low current intensities might approach the natural activation pattern of VOL by enhancing the neural contribution to force production. Previous studies investigating WPHF reported progressive and unexpected force increments ("Extra Forces") despite a constant stimulation intensity which might reflect the more pronounced activation of sensory pathways within the central nervous system. The objective of this thesis was to investigate this "Extra Force" (EF) phenomenon and to evaluate the efficiency of WPHF (1 ms pulse duration at 100 Hz) in terms of metabolic demand and neural contribution to force production in comparison to CONV NMES (0.05 ms pulse duration at 25 Hz) and VOL. Our experiments comprised electrophysiological (EMG) and nuclear magnetic resonance techniques (31P spectroscopy of the muscle, functional imaging of the brain). The findings should be considered in future studies investigating the potential of NMES in a clinical context as a treatment for neuromuscular pathologies.

Esta Dissertação irá apresentar a utilização de técnicas de controle nãolinear, tais como o controle adaptativo e robusto, de modo a controlar um sistema de Eletroestimulação Funcional desenvolvido pelo laboratório de Engenharia Biomédica da COPPE/UFRJ. Basicamente um Eletroestimulador Funcional (Functional Electrical Stimulation FES) se baseia na estimulação dos nervos motores via eletrodos cutâneos de modo a movimentar (contrair ou distender) os músculos, visando o fortalecimento muscular, a ativação de vias nervosas (reinervação), manutenção da amplitude de movimento, controle de espasticidade muscular, retardo de atrofias e manutenção de tonicidade muscular. O sistema utilizado tem por objetivo movimentar os membros superiores através do estímulo elétrico de modo a atingir ângulos-alvo pré-determinados para a articulação do cotovelo. Devido ao fato de não termos conhecimento pleno do funcionamento neuro-motor humano e do mesmo ser variante no tempo, não-linear, com parâmetros incertos, sujeito a perturbações e completamente diferente para cada indivíduo, se faz necessário o uso de técnicas de controle avançadas na tentativa de se estabilizar e controlar esse tipo de sistema. O objetivo principal é verificar experimentalmente a eficácia dessas técnicas de controle não-linear e adaptativo em comparação às técnicas clássicas, de modo a alcançar um controle mais rápido, robusto e que tenha um desempenho satisfatório. Em face disso, espera-se ampliar o campo de utilização de técnicas de controle adaptativo e robusto, além de outras técnicas de sistemas inteligentes, tais como os algoritmos genéticos, provando que sua aplicação pode ser efetiva no campo de sistemas biológicos e biomédicos, auxiliando assim na melhoria do tratamento de pacientes envolvidos nas pesquisas desenvolvidas no Laboratório de Engenharia Biomédica da COPPE/UFRJ. / This dissertation will present the use of nonlinear control techniques, such as adaptive and robust control in order to design a Functional Electrical Stimulation (FES) system developed by Biomedical Engineering Laboratory at COPPE/UFRJ. Basically, a FES on the stimulation of motor nerves via skin electrodes in order to contract or stretch the muscles such that the amplitude and quality of the limbs movement can be maintained, reducing muscular atrophy as well. Consequently, the muscle strength can be improved and new neural pathways may be activated. Here, the goals of the proposed control system is to move the arm of the patient via electrical stimulation to achieve some desired trajectory related to the elbow angles of reference. Since we have a priori no deep knowledge of human neuro-motor model, the use of advanced and robust control schemes seems to be useful to stabilize this kind of systems which may be completely different for each individual, being time-varying, nonlinear, uncertain and subject to disturbances. The main objective is to experimentally verify the effectiveness of the proposed nonlinear and adaptive controllers when compared to classical ones in order to achieve faster, robust and better control performance. It is expected to spread the application of adaptive and robust controllers and other intelligent system tools, such as genetic algorithms, to the field of biological and biomedical engineering. Thus, we believe that the developed control system may help the improvement of the patients treatment involved in the research carried out by Biomedical Engineering Laboratory at COPPE/UFRJ.

Esta Dissertação irá apresentar a utilização de técnicas de controle nãolinear, tais como o controle adaptativo e robusto, de modo a controlar um sistema de Eletroestimulação Funcional desenvolvido pelo laboratório de Engenharia Biomédica da COPPE/UFRJ. Basicamente um Eletroestimulador Funcional (Functional Electrical Stimulation FES) se baseia na estimulação dos nervos motores via eletrodos cutâneos de modo a movimentar (contrair ou distender) os músculos, visando o fortalecimento muscular, a ativação de vias nervosas (reinervação), manutenção da amplitude de movimento, controle de espasticidade muscular, retardo de atrofias e manutenção de tonicidade muscular. O sistema utilizado tem por objetivo movimentar os membros superiores através do estímulo elétrico de modo a atingir ângulos-alvo pré-determinados para a articulação do cotovelo. Devido ao fato de não termos conhecimento pleno do funcionamento neuro-motor humano e do mesmo ser variante no tempo, não-linear, com parâmetros incertos, sujeito a perturbações e completamente diferente para cada indivíduo, se faz necessário o uso de técnicas de controle avançadas na tentativa de se estabilizar e controlar esse tipo de sistema. O objetivo principal é verificar experimentalmente a eficácia dessas técnicas de controle não-linear e adaptativo em comparação às técnicas clássicas, de modo a alcançar um controle mais rápido, robusto e que tenha um desempenho satisfatório. Em face disso, espera-se ampliar o campo de utilização de técnicas de controle adaptativo e robusto, além de outras técnicas de sistemas inteligentes, tais como os algoritmos genéticos, provando que sua aplicação pode ser efetiva no campo de sistemas biológicos e biomédicos, auxiliando assim na melhoria do tratamento de pacientes envolvidos nas pesquisas desenvolvidas no Laboratório de Engenharia Biomédica da COPPE/UFRJ. / This dissertation will present the use of nonlinear control techniques, such as adaptive and robust control in order to design a Functional Electrical Stimulation (FES) system developed by Biomedical Engineering Laboratory at COPPE/UFRJ. Basically, a FES on the stimulation of motor nerves via skin electrodes in order to contract or stretch the muscles such that the amplitude and quality of the limbs movement can be maintained, reducing muscular atrophy as well. Consequently, the muscle strength can be improved and new neural pathways may be activated. Here, the goals of the proposed control system is to move the arm of the patient via electrical stimulation to achieve some desired trajectory related to the elbow angles of reference. Since we have a priori no deep knowledge of human neuro-motor model, the use of advanced and robust control schemes seems to be useful to stabilize this kind of systems which may be completely different for each individual, being time-varying, nonlinear, uncertain and subject to disturbances. The main objective is to experimentally verify the effectiveness of the proposed nonlinear and adaptive controllers when compared to classical ones in order to achieve faster, robust and better control performance. It is expected to spread the application of adaptive and robust controllers and other intelligent system tools, such as genetic algorithms, to the field of biological and biomedical engineering. Thus, we believe that the developed control system may help the improvement of the patients treatment involved in the research carried out by Biomedical Engineering Laboratory at COPPE/UFRJ.

Existing neurocomputational and empirical data link deficient neuromodulation of the fronto-parietal and hippocampal-striatal circuitries with aging-related increase in processing noise and declines in various cognitive functions. Specifically, the theory of aging neuronal gain control postulates that aging-related suboptimal neuromodulation may attenuate neuronal gain control, which yields computational consequences on reducing the signal-to-noise-ratio of synaptic signal transmission and hampering information processing within and between cortical networks. Intervention methods such as cognitive training and non-invasive brain stimulation, e.g., transcranial direct current stimulation (tDCS), have been considered as means to buffer cognitive functions or delay cognitive decline in old age. However, to date the reported effect sizes of immediate training gains and maintenance effects of a variety of cognitive trainings are small to moderate at best; moreover, training-related transfer effects to non-trained but closely related (i.e., near-transfer) or other (i.e., far-transfer) cognitive functions are inconsistent or lacking. Similarly, although applying different tDCS protocols to reduce aging-related cognitive impairments by inducing temporary changes in cortical excitability seem somewhat promising, evidence of effects on short- and long-term plasticity is still equivocal. In this article, we will review and critically discuss existing findings of cognitive training- and stimulation-related behavioral and neural plasticity effects in the context of cognitive aging, focusing specifically on working memory and episodic memory functions, which are subserved by the fronto-parietal and hippocampal-striatal networks, respectively. Furthermore, in line with the theory of aging neuronal gain control we will highlight that developing age-specific brain stimulation protocols and the concurrent applications of tDCS during cognitive training may potentially facilitate short- and long-term cognitive and brain plasticity in old age.

Existing neurocomputational and empirical data link deficient neuromodulation of the fronto-parietal and hippocampal-striatal circuitries with aging-related increase in processing noise and declines in various cognitive functions. Specifically, the theory of aging neuronal gain control postulates that aging-related suboptimal neuromodulation may attenuate neuronal gain control, which yields computational consequences on reducing the signal-to-noise-ratio of synaptic signal transmission and hampering information processing within and between cortical networks. Intervention methods such as cognitive training and non-invasive brain stimulation, e.g., transcranial direct current stimulation (tDCS), have been considered as means to buffer cognitive functions or delay cognitive decline in old age. However, to date the reported effect sizes of immediate training gains and maintenance effects of a variety of cognitive trainings are small to moderate at best; moreover, training-related transfer effects to non-trained but closely related (i.e., near-transfer) or other (i.e., far-transfer) cognitive functions are inconsistent or lacking. Similarly, although applying different tDCS protocols to reduce aging-related cognitive impairments by inducing temporary changes in cortical excitability seem somewhat promising, evidence of effects on short- and long-term plasticity is still equivocal. In this article, we will review and critically discuss existing findings of cognitive training- and stimulation-related behavioral and neural plasticity effects in the context of cognitive aging, focusing specifically on working memory and episodic memory functions, which are subserved by the fronto-parietal and hippocampal-striatal networks, respectively. Furthermore, in line with the theory of aging neuronal gain control we will highlight that developing age-specific brain stimulation protocols and the concurrent applications of tDCS during cognitive training may potentially facilitate short- and long-term cognitive and brain plasticity in old age.