Influence of the robotic exoskeleton Lokomat on the control of human gait: an electromyographic and kinematic analysis

Dissertação de mestrado integrado em Engenharia BiomédicaNowadays there is an increasing percentage of elderly people and it is expected that this percentage will continue increasing. This aging of the population carries huge costs to the government, especially in the provision of health care. Among those health care, there is the motor rehabilitation after a stroke. The recent robotic devices for gait training are pointed out as an excellent solution to solve this problem, because besides the cost savings they can provide longer and more innovative trainings. All the advantages presented by such devices can trigger more research in this area as well as more government investments. There are already some control strategies implemented in these devices, which should be improved to create new motor rehabilitation interventions. One strategy that can be used in the future is to provide the amount of motor assistance as the patient really needs to achieve certain goals. Lokomat is one of these rehabilitation devices, which allows changing the percentage of assistance provided to the user. However, it is necessary to study the effects of such strategy in the physiological response of the users. There is more and more consensus about the need to obtain muscular activation patterns and kinematic patterns during walking in devices as Lokomat very similar to those obtained by healthy subjects during non-assisted walking. Recent scientific investigations make us to believe that the nervous system controls human gait via a simple modular structure. It is important to understand how this structure works when the walking is assisted by robotic devices. Thus, this work had three main objectives: to study the muscular electric activity during walking in Lokomat, by varying the total assistance provided by the device, as well as the walking speed; to analyze kinematic changes obtained during Lokomat-assisted walking, as well as the interaction forces between each user and the robotic device; to understand how this modular organization of the nervous system involved in synchronization of the muscular activity works during walking assisted by robotic devices. Only healthy subjects participated in our study. Therefore, our work generated a basis of comparison for future control strategies to be implemented in motor rehabilitation. We obtained quite encouraging results, which allow us to formulate new strategies for motor rehabilitation. In the future, these strategies will be implemented and it expected that post-stroke people can restore their normal gait more quickly.Actualmente verifica-se um aumento crescente da percentagem de pessoas idosas e prevê-se que essa percentagem continue a aumentar. Este envelhecimento da população acarreta enormes custos para o estado, sobretudo na prestação dos cuidados de saúde. Entre esses cuidados, está a reabilitação motora após um AVC (acidente vascular cerebral). Os novos dispositivos robóticos de treino da marcha são apontados como uma excelente solução para este problema, pois além da poupança de custos poderão proporcionar treinos de maior duração e mais inovadores. Todas as vantagens apresentadas por este tipo de dispositivos podem servir para o despoletar de cada vez mais investigação nesta área e investimentos governamentais. Existem já algumas estratégias de controlo implementadas nestes dispositivos, que devem ser melhoradas para se criarem novas intervenções de reabilitação motora. Uma estratégia que se poderá utilizar futuramente nesses dispositivos consiste em providenciar somente a ajuda motora necessária para que o paciente atinja determinados objectivos. O Lokomat é um destes dispositivos, que permite variar a percentagem de ajuda providenciada. É no entanto necessário estudar os efeitos de tal estratégia na resposta fisiológica dos utilizadores. Cada vez se verifica maior consenso acerca da necessidade de se obterem padrões de activação muscular e padrões cinemáticos durante a marcha em dispositivos como o Lokomat muito similares aos obtidos por indivíduos saudáveis em marcha não assistida. Recentes investigações científicas levam-nos a crer que o sistema nervoso controla a marcha humana através de uma estrutura modular simples. É importante saber como actua essa estrutura quando a marcha é assistida por dispositivos robóticos. Assim, este trabalho teve três objectivos principais: estudar a actividade eléctrica muscular durante a marcha em Lokomat, variando a ajuda total providenciada pelo dispositivo, bem como a velocidade da marcha; analisar as diferenças cinemáticas obtidas durante a marcha em Lokomat, bem como as forças de interacção entre cada usuário e o dispositivo robótico; perceber como actua a organização modular do sistema nervoso envolvida na sincronização da actividade muscular durante a marcha em dispositivos robóticos. Apenas indivíduos saudáveis participaram neste estudo. Assim, este estudo gerou uma base de comparação para futuras estratégias de controlo utilizadas em reabilitação motora. Os resultados foram bastante animadores e permitam-nos formular novas estratégias de reabilitação motora. No futuro, estas estratégias serão levadas a cabo de modo a que pessoas afectadas por AVCs possam restabelecer mais rapidamente a sua marcha normal

Influence of the robotic exoskeleton Lokomat on the control of human gait : an electromyographic and kinematic analysis

Nowadays there is an increasing percentage of elderly people and it is expected that this percentage will continue increasing, carrying huge organizational costs in rehabilitation services. Recent robotic devices for gait training are more and more regarded as alternatives to solve cost-efficiency issues and provide novel approaches for training. Nevertheless, there is a need to address how to target muscular activation and kinematic patterns for optimal recovery after a neurological damage. The main objective of this work was to understand the underlying principles that the human nervous system employs to synchronize muscular activity during walking assisted by Lokomat. A basic low-dimensional locomotor program can explain the synergistic activation of muscles during assisted gait. As a main contribution, we generated a detailed description of the electro myographic and biomechanical response to variations in robotic assistance in intact humans, which can be used for future control strategies to be implemented in motor rehabilitation

Effects of robotic guidance on the coordination of locomotion

Functional integration of motor activity patterns enables the production of coordinated movements, such as walking. The activation of muscles by weightened summation of activation signals has been demonstrated to represent the spatiotemporal components that determine motor behavior during walking. Exoskeleton robotic devices are now often used in the rehabilitation practice to assist physical therapy of individuals with neurological disorders. These devices are used to promote motor recovery by providing guidance force to the patients. The guidance should in principle lead to a muscle coordination similar to physiological human walking. However, the influence of robotic devices on locomotor patterns needs still to be characterized. The aim of this study was to analyze the effect of force guidance and gait speed on the modular organization of walking in a group of eight healthy subjects.This project is funded by the European Commission, project "BETTER" (contract number 247935) and Spanish Consolider-Ingenio Programme, project "HYPER" (contract number CSD2009-00067) and Universita Degli Studi di Roma "Foro Italico", research project "Dynamic sensorimotor interaction during locomotion: influences of perturbations and/or body unloading"

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Combining neuromuscular and biomechanical features to assess sensorimotor impairments after spinal cord injury or stroke

Doctoral Program in Biomedical EngineeringStroke and spinal cord injury (SCI) are the most common causes of paresis and paralysis. Disabilities that follow stroke (hemiparesis, hemiplegia) or SCI (paraplegia, tetraplegia) are the result of an inappropriate muscle coordination and activation, leading to impaired motor functions (e.g., walking, cycling) and, thereby, preventing affected people from healthy-like participation in daily activities. The assessment of sensorimotor impairments has been mainly performed with qualitative methods (classical clinical scales) or subjective assessment from clinical personnel (based on visual observation). These techniques may lead to low inter-rater reliability and, as a consequence, to inadequate interventions. Gait training must have the ability to adapt to individual progression of each patient. Therefore, it is necessary to quantitatively assess locomotor responses after neurological diseases. The main goal of this Ph.D. Thesis is to generate meaningful quantitative metrics to assess sensorimotor impairments of patients that suffered a stroke or an incomplete spinal cord injury (iSCI). To achieve this main goal, it is necessary to advance neurophysiological and biomechanical conceptual foundations underlying gait function. Further design of appropriate protocols and the generation of these metrics may improve future rehabilitation treatments tailored to each of the aforementioned patients. Recent researches on pathological conditions strongly recommend gait analysis to adequately assess and follow-up patients and to support clinical decision on the best treatment. Measures derived from gait analysis provide detailed and quantitative description of motor impairments. On the other hand, a technique called analysis of muscle synergies (groups of co-activated muscles responsible for the control of motor tasks), which is based on statistical analysis of electromyographic (EMG) features, has emerged as a promising tool that can a better the clinician a better view of the neural structure underlying motor behaviors and how they change during the rehabilitation process. Thus, a combination of metrics informing about biomechanical and neuromuscular performance in realistic conditions should lead to a better assessment of motor impairments. To achieve the main goal of this Ph.D. Thesis, four distinct and complementary studies were performed. The first study investigated similar features of walking and cycling under the muscle synergies hypothesis. This study was motivated by the need for novel tools to measure and predict motor performance of neural injured patients. This need has emerged because some patients who suffered neural injuries do not have sufficient muscle force to walk during the early stage of rehabilitation and, as a consequence, cannot be assessed properly during walking tasks. Due to similarities in kinematics and muscle control, cycling might be explored as a possible framework. Results of this study provided evidences for common neuromuscular mechanisms of the two motor tasks. The results of study 1 supported the hypothesis of using cycling to assess gait-related motor performance. Thus, the second study of this research aimed to test this hypothesis on subjects affected by iSCI. First of all, results showed that iSCI patients preserved a synergistic control of muscles during cycling and the similarity of synergies with respect to healthy controls correlated with the degree of impairment. Second, muscle synergies outcomes extracted during cycling correlated with clinical measurements of gait performance and/or spasticity caused by abnormal spatiotemporal muscle co-activation. After iSCI, both body sides may be affected differently, resulting in asymmetric motor control and functional behavior. The third study of this Thesis used some biomechanical features, as well as the analysis of muscle synergies to differentiate most and less affected sides. Results showed that biomechanical analysis was more effective than the analysis of muscle synergies to detect differences between the most and the less affected sides of iSCI patients. Based on the findings of studies 2 and 3, which showed the usefulness of muscle synergies and biomechanical features to assess iSCI patients, the fourth and last study of this Thesis tested whether the combination of a small set of gait features and the analysis of muscle synergies could better predict walking function poststroke than the gold-standard scale (Fugl-Meyer Assessment, FMA). It was possible to find some variables (from both the most and the less affected side) that correlated better with walking function than FMA. In conclusion, this Thesis presented novel methodologies and metrics that allow for a quantitative assessment of sensorimotor impairments in patients that suffered an iSCI or a stroke. In particular, the use of metrics based on EMG and biomechanical features gave a new insight into the motor recovery mechanisms as well as the performance after neural damage. These metrics may be explored in the future as a complement to the current clinical assessment procedures.Os acidentes vasculares cerebrais (AVCs) e as lesões medulares são a causa mais comum de paresia e paralisia. As incapacidades resultantes de um AVC (hemiparesia, hemiplegia) ou de uma lesão medular (paraplegia, tetraplegia) são o resultado de uma coordenação e ativação muscular inadequadas, conduzindo a funções motoras (marcha, ciclismo, por exemplo) inadequadas e, desse modo, impedindo as pessoas afetadas de terem uma participação saudável em atividades diárias. A avaliação das de ciências sensoriais e motoras tem sido efetuada sobretudo com base em métodos qualitativos (escalas clínicas clássicas) ou avaliações subjetivas de pessoal clínico (com base na observação visual). Estas técnicas podem resultar numa baixa contabilidade entre avaliadores e, como consequência, a intervenções inadequadas. O treino da marcha deve ter a capacidade de se adaptar a progressão individual de cada paciente. Portanto, e necessário avaliar quantitativamente as respostas locomotoras após doenças neurológicas. O principal objetivo desta Tese de Doutoramento e gerar métricas quantitativas para avaliar de ciências sensoriais e motoras de pacientes que sofreram um AVC ou uma lesão medular incompleta. Para atingir este objetivo principal, e necessário desenvolver os princípios neurofisiológicos e biomecânicos subjacentes a marcha. A conceção adicional de protocolos adequados e a geração destas métricas pode melhorar os futuros tratamentos de reabilitação. As investigações mais recentes sobre condições patológicas aconselham vivamente a análise da marcha para poder avaliar e acompanhar adequadamente os pacientes e também para apoiar decisões clínicas sobre o melhor tratamento a executar. As medidas auferidas através da análise da marcha fornecem uma descrição detalhada e quantitativa de ciências motoras. Por outro lado, uma técnica chamada análise de sinergias musculares (grupos de músculos co-ativados responsáveis pelo controlo de tarefas motoras), que se baseia na análise estatística das características eletromiográficas (EMG), tem emergido como um instrumento promissor que pode oferecer ao pessoal clínico uma melhor visão das estruturas neuronais subjacentes às tarefas motoras e como estas mudam durante o processo de reabilitação. Sendo assim, uma combinação de métricas que forneçam informação sobre o desempenho biomecânico e neuromuscular em condições reais poder a levar a uma melhor avaliação de ciências motoras. Para atingir o objetivo principal desta Tese de Doutoramento, foram realizados quatro estudos distintos e complementares. O primeiro estudo investigou características semelhantes da marcha e do ciclismo sob a hipótese das sinergias musculares. Este estudo foi motivado pela necessidade de novos instrumentos de medida e predição do desempenho motor de pacientes que sofreram lesões neuronais. Esta necessidade surgiu visto que alguns pacientes que sofreram lesões neuronais não têm a for ca muscular suficiente para caminhar durante a fase inicial de reabilitação e, por conseguinte, não pode ser avaliados adequadamente durante tarefas de marcha. Devido às semelhanças cinemáticas e de controlo muscular, o ciclismo pode ser explorado como uma possível solução. Os resultados deste estudo forneceram evidências de que estas duas tarefas motoras apresentam mecanismos neuromusculares comuns. Os resultados do estudo 1 sustentaram a hipótese de utilizar o ciclismo para avaliar o desempenho motor relacionado com a marcha. Assim, o segundo estudo desta investigação teve como objetivo testar essa hipótese em pacientes afetados por uma lesão medular incompleta. Em primeiro lugar, os resultados mostraram que estes pacientes preservam um controlo sinérgico dos músculos durante o ciclismo e também que que a similaridade destas mesmas sinergias com as sinergias apresentadas por sujeitos controlo saudáveis se correlaciona com o grau de debilidade apresentado pelo paciente. Em segundo lugar, alguns valores da analise de sinergias correlacionaram-se com medidas clínicas de desempenho da marcha e/ou espasticidade causada pela ativação espaciotemporal anormal. Apos uma lesão medular incompleta, ambos os lados do corpo podem ser afetados de forma distinta, o que resulta num controlo motor e comportamento funcional distinto. O terceiro estudo desta Tese utilizou algumas variáveis biomecânicas, bem como a análise das sinergias musculares para diferenciar os lados mais e menos afetados. Os resultados mostraram que a análise biomecânica foi mais eficaz que a análise das sinergias musculares para detetar diferenças os lados mais e menos afetados destes pacientes. Baseado nas descobertas apresentadas nos estudos 2 e 3, o quarto e ultimo estudo desta Tese testou se a combinação de um pequeno conjunto de variáveis da marcha e da analise das sinergias musculares poderia predizer melhor a função de marcha apos um AVC do que utilizando a escala clínica padrão (Avaliação de Fugl-Meyer). Foi possível encontrar algumas variáveis (tanto do lado mais afetado como do lado menos afetado) que se correlacionaram melhor com a função de marcha do que os resultados de predição apresentados pela Avaliação de Fugl-Meyer. Em conclusão, esta Tese apresenta novas metodologias e métricas que permitem uma avaliação quantitativa de danos sensoriais e motores em pacientes que sofreram uma lesão medular ou um AVC. A utilização de métricas baseadas em EMG e variáveis biomecânicas possibilitaram a avaliação dos mecanismos de recuperação motora, bem como o desempenho após danos neuronais. Estas métricas podem ser exploradas no futuro como um complemento para os procedimentos atuais de avaliação clínica

Control method for a neuroprosthetic device for the reduction of a pathological tremors

The invention relates to a control method for a neuroprosthetic device, allowing to monitor and reduce pathological tremors in users via the stimulation of the peripheral muscles and modulation of the afferent pathways.Peer reviewedConsejo Superior de Investigaciones Científicas (CSIC), Imperial College Innovations Limited (ICIL). Fundación para la investigación biomédica del Hospital Gregorio Marañón (FIBHGM)A1 Solicitud de patente con informe sobre el estado de la técnic

Testing COI primers for ichthyoplankton metabarcoding and their capability to assess local mesozooplankton communities

DNA metabarcoding is particularly helpful for monitoring taxonomically complex communities and hard to identify morphologically, such as several zoo and ichthyoplankton, which contain eggs and larval stages of unknown species. However, the efficiency of metabarcoding in diversity recovery is dependent on the targeted genetic markers and primers employed. In this work, we compared the performance of three different primer pairs from cytochrome oxidase subunit I (COI) genetic marker in species detection from marine mesozooplankton samples and its potential to be implemented in biomonitoring programs. We employed the mlCOIintF/LoboR1 primer combination targeting marine metazoans, and two newly designed fish-specific primer cocktails for targeting the ichthyoplankton. Mesozooplankton samples were collected at 4 locations on the Portuguese coast – 1 in the northwest (Viana do Castelo) and 3 in the south (coastal lagoons of Ria de Alvor and Ria Formosa, and in the river Guadiana estuary). Bulk community DNA was extracted using a non-destructive protocol and amplicon libraries produced for the 3 primers combinations. After quality-filtering bioinformatic steps, we obtained 3.04 x 105 usable sequences, of which 76.26% were clustered into OTUs (operational taxonomic units) and 46.30% were identified at species level - corresponding to 103 taxa from 8 different metazoan Phyla. The most diverse classes were Malacostraca, Actinopterygii, and Copepoda. As expected, the generic primer pair for marine metazoa (mlCOIintF/LoboR1) retrieved a higher number of species (94) compared with the fish-specific primer cocktails (30). Nevertheless, 9 % of the total species were identified exclusively by the cocktails, of which 42% were fish. These results confirmed the potential of metabarcoding as a tool for profiling zooplankton communities and to assess ichthyoplankton diversity. Multiple primers pairs increased species detection from different taxonomic groups, being the protocol optimization for fish-specific primer cocktails, the next step for its implementation in fish stock assessments.