Hybrid Neuroprosthesis for Lower Limbs

Assistive technologies have been proposed for the locomotion of people with spinal cord injury (SCI). One of them is the neuroprosthesis that arouses the interest of developers and health professionals bearing in mind the beneficial effects promoted in people with SCI. Thus, the first session of this chapter presents the principles of human motility and the impact that spinal cord injury causes on a person’s mobility. The second session presents functional electrical stimulation as a solution for the immobility of paralyzed muscles. It explains the working principles of constituent modules and main stimulatory parameters. The third session introduces the concepts and characteristics of neural prosthesis hybridization. The last two sessions present and discuss examples of hybrid neuroprostheses. Such systems employ hybrid assistive lower limb strategies to evoke functional movements in people with SCI, associating the motor effects of active and/or passive orthoses to a functional electrical stimulation (FES) system. Examples of typical applications of FES in rehabilitation are discussed

Advances and perspectives of mechanomyography

INTRODUCTION: The evaluation of muscular tissue condition can be accomplished with mechanomyography (MMG), a technique that registers intramuscular mechanical waves produced during a fiber's contraction and stretching that are sensed or interfaced on the skin surface. OBJECTIVE: Considering the scope of MMG measurements and recent advances involving the technique, the goal of this paper is to discuss mechanomyography updates and discuss its applications and potential future applications. METHODS: Forty-three MMG studies were published between the years of 1987 and 2013. RESULTS: MMG sensors are developed with different technologies such as condenser microphones, accelerometers, laser-based instruments, etc. Experimental protocols that are described in scientific publications typically investigated the condition of the vastus lateralis muscle and used sensors built with accelerometers, third and fourth order Butterworth filters, 5-100Hz frequency bandpass, signal analysis using Root Mean Square (RMS) (temporal), Median Frequency (MDF) and Mean Power Frequency (MPF) (spectral) features, with epochs of 1 s. CONCLUSION: Mechanomyographic responses obtained in isometric contractions differ from those observed during dynamic contractions in both passive and functional electrical stimulation evoked movements. In the near future, MMG features applied to biofeedback closed-loop systems will help people with disabilities, such as spinal cord injury or limb amputation because they may improve both neural and myoelectric prosthetic control. Muscular tissue assessment is a new application area enabled by MMG; it can be useful in evaluating the muscular tonus in anesthetic blockade or in pathologies such as myotonic dystrophy, chronic obstructive pulmonary disease, and disorders including dysphagia, myalgia and spastic hypertonia. New research becomes necessary to improve the efficiency of MMG systems and increase their application in rehabilitation, clinical and other health areas304384401CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFINANCIADORA DE ESTUDOS E PROJETOS - FINEPsem informaçã

Breathing Monitoring and Pattern Recognition with Wearable Sensors

This chapter introduces the anatomy and physiology of the respiratory system, and the reasons for measuring breathing events, particularly, using wearable sensors. Respiratory monitoring is vital including detection of sleep apnea and measurement of respiratory rate. The automatic detection of breathing patterns is equally important in other respiratory rehabilitation therapies, for example, magnetic resonance exams for respiratory triggered imaging, and synchronized functional electrical stimulation. In this context, the goal of many research groups is to create wearable devices able to monitor breathing activity continuously, under natural physiological conditions in different environments. Therefore, wearable sensors that have been used recently as well as the main signal processing methods for breathing analysis are discussed. The following sensor technologies are presented: acoustic, resistive, inductive, humidity, acceleration, pressure, electromyography, impedance, and infrared. New technologies open the door to future methods of noninvasive breathing analysis using wearable sensors associated with machine learning techniques for pattern detection

Neuromuscular fatigue detection by mechanomyography in people with complete spinal cord injury

Functional electrical stimulation (FES) is a method of activating paralyzed muscles. During FES application, fast muscle fatigue can occur (the inability of stimulated muscles to generate force). Therefore, it is beneficial to estimate the muscle fatigue for FES closed-loop control for walking to prevent unexpected muscle collapse and adapt the FES strategy in real time. Mechanomyography (MMG) is a noninvasive technique for registering myofiber vibrations, representing an ideal candidate for the provision of feedback. The hypothesis was that MMG signals could effectively detect muscle fatigue and, thus, provide feedback

IMPACT OF SKINFOLD THICKNESS ON WAVELET-BASED MECHANOMYOGRAPHIC SIGNAL

Surface mechanography (MMG) is a non-invasive technique that captures signs of low-frequency vibrations of skeletal muscles through the skin. However, subcutaneous structures may interfere with the acquisition of MMG signals. The objective of this study was to verify the influence of skinfold thickness (ST) on the MMG wavelet-based signal in the rectus femoris muscle during maximal voluntary contraction in two groups of individuals: group I (n = 10, ST 20 mm). Negative correlation was observed between the 19 Hz, 28 Hz and 39 Hz frequency bands with ST. There was a statistical difference in almost all frequency bands, especially in the X and Y axes. All MMG axes in group II presented higher magnitudes in frequency bands 2 and 6 Hz (like low-pass filter). Thus, these results can be applied to calibrate MMG responses as biofeedback systems

Action potential: from excitation to neural adaptation

INTRODUCTION: The action potential (AP) arises due to a disturbance of the resting state of the cell membrane with consequent flow of ions across the membrane and ion concentration changes in intra and extra cellular space. OBJECTIVES: This article aims to summarize the scientific knowledge accumulated to date on the action potential and neural adaptation in the process of applying a constant stimulus. MATERIALS AND METHODS: This is a literature review on the bases Springer, ScienceDirect, PubMed, IEEE Xplore, Google Scholar, Capes Periodicals Portal as well as books on the topic. The selected preferred language was English with the keywords: action potential; adaptation, accommodation; rheobase; chronaxy; nerve impulse. We conducted a search of articles with a wide time window from 1931 to 2010 and books from 1791 to 2007. RESULTS: In the selected studies was extracted information about the following topics: action potential and its stages; nerve conduction; rheobase; chronaxie, accommodation, and adaptation. CONCLUSION: A stimulus that creates AP, if applied consistently, can reduce the frequency of depolarization as a function of time and, consequently, to adapt the cell. The time it takes the cell in the absence of stimuli, to recover its original frequency, is defined as a disadaptation.INTRODUÇÃO: O potencial de ação (PA) origina-se graças a uma perturbação do estado de repouso da membrana celular, com consequente fluxo de íons, por meio da membrana e alteração da concentração iônica nos meios intra e extracelular. OBJETIVOS: Sintetizar o conhecimento científico acumulado até o presente sobre o potencial de ação neural e o seu processo de adaptação sob aplicação de um estímulo constante. MATERIAIS E MÉTODOS: Busca realizada nas bases Springer, ScienceDirect, PubMed, IEEE Xplore, Google Acadêmico, Portal de Periódicos da Capes, além de livros referentes ao assunto. O idioma de preferência selecionado foi o inglês, com as keywords: action potential; adaptation; accommodation; rheobase; chronaxy; nerve impulse. Efetuou-se a procura de artigos com uma janela de tempo de 1931 a 2010 e livros de 1791 a 2007. RESULTADOS: Dos trabalhos selecionados, foram extraídas informações a respeito dos seguintes tópicos: potencial de ação e suas fases; condução nervosa; reobase; cronaxia; acomodação; e adaptação neuronal. CONCLUSÃO: Um estímulo que crie PA, se aplicado de maneira constante, pode reduzir a frequência de despolarizações em função do tempo e, consequentemente, adaptar a célula. O tempo que a célula demora, na ausência de estímulos, para recuperar sua frequência original é definido como desadaptação.535547Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

Teste e Reteste da avaliação da espasticidade e sinais mecanomiográficos de flexores e extensores de cotovelo em atleta de Bocha Paralímpica com Paralisia Cerebral

Objetivo: Avaliar a eficácia da mecanomiografia (MMG) para classificação de atletas na bocha paralímpica. Método: Neste estudo piloto, o voluntário selecionado com Paralisia Cerebral, foi avaliado empregando o teste de espasticidade (ASAS) nos braços direito e esquerdo, coletados os dados de mecanomiografia durante esse teste, por meio de dois sensores de MMG. O sensor 1 foi fixado na superfície da pele, no ponto motor dos flexores do cotovelo e o sensor 2, no ponto motor dos extensores do cotovelo. Os sinais de MMG foram processados utilizando o software MATLAB®, no qual o desvio padrão foi determinado para cada eixo de cada sensor, como também a média dos desvios entre sessões para os lados direito e esquerdo dos músculos flexores e extensores dispostos para cada avaliador. Resultados: Constataram-se diferenças numéricas entre as médias dos desvios para cada avaliador do mesmo grupo muscular do mesmo braço; porém, estas diferenças são sutis e mostram um padrão para o sinal mecanomiográficos mesmo quando diferentes avaliadores utilizam realizam o teste. Conclusão: Conclui-se que a MMG é viável na utilização de identificação espasticidade e os valores da média de todas as avaliações dos avaliadores 1 e 2 no grupo de flexores (MSD) foi mantida entre 0,1723 mV (Y) e 0,1225 mV (Z), 0,1904 (Y) mV a 0,1601mV (Z), não havendo divergência entre os avaliadores, mas caso houvesse o MMG seria fundamental na avaliação de espasticidade

Avaliação do deslocamento angular de cabeça e tronco de pacientes durante a equoterapia com actímetro

Introdução: A equoterapia vem sendo utilizada como uma ferramenta terapêutica no tratamento diferentes distúrbios neuromusculares, cujos progressos posturais observados antes e após o tratamento foram demonstrados, mas nunca analisados durante as seções de tratamento. Muitos processos como Time Up and Go (TUG), marcha, centro de pressão, entre outros, foram analisados de forma qualitativa, afirmando apenas uma melhora no controle motor. Objetivo: Para avaliar a evolução do paciente durante a terapia sobre o cavalo, objetivou-se quantificar seu desempenho utilizando um instrumento biomédico portátil (actímetro) desenvolvido para a análise cinemática do deslocamento da cabeça e tronco utilizando um sensor de aceleração 3D. Método: Nove voluntários foram avaliados durante duas sessões de equoterapia em ritmo de passo do cavalo. Os eixos x, y e z do sensor foram condicionados e processados para obter valores médios e desvios padrões, bem como a média dos grupos de voluntários com ou sem deficiência. Resultados: Foi possível observar uma diferença significativa entre os voluntários com deficiência e os voluntários sem deficiência, que apresentaram resultados quantificados numericamente maiores em todas as comparações realizadas. Conclusão: Os voluntários com deficiência possuem menor estabilidade que os voluntários sem deficiência

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