Made available in DSpace on 2016-06-02T20:19:15Z (GMT). No. of bitstreams: 1 3462.pdf: 1115624 bytes, checksum: 922f1de495cfca273a837f049f67e6f2 (MD5) Previous issue date: 2011-02-28 / Financiadora de Estudos e Projetos / Objective: To assess the six-minute step test (6MST) in terms of its ability to evaluate the aerobic functional capacity of COPD patients. In addition to compare, correlate and verify if there is an agreement between the metabolic (oxygen uptake-VO2), ventilatory (minute ventilation-VE) and cardiovascular variables (heart rate-HR), and perceived exertion of the 6MST and the incremental cardiopulmonary exercise test (ICPET). Methods: Metabolic and ventilatory variables, heart rate, dyspnea and lower limb (LL) fatigue were recorded from 18 COPD patients (five had mild COPD, five moderate, six severe and two very severe) performing the 6MST and the submaximal ICPET on cycle ergometer (work rate was increased by 5-10 watts) on different and not consecutive days. Results: There were no significant differences between VO2, HR, VE, dyspnea and LL fatigue mean values at the peak of both tests. Moderate correlations were found between the 6MST performance and ICPET s VO2 (r=0.49;p=0.05) and performance (r=0.63;p=0.005), high correlations were found between both VO2 (L/min and mL/kg/min) (r=0.76 and r=0.77;p=0.001), and moderate correlations were found between HR (r=0.68;p=0.002) and LL fatigue (r=0.59;p=0.011) between the tests. There was no agreement between VO2, HR and LL fatigue values between the tests. Conclusion: The 6MST has the ability to assess aerobic functional capacity and presents cardiorespiratory responses and perceived exertion similar to the ICPET in magnitude, however it cannot replace the ICPET, since the 6MST assesses and demands greater and more localized work from peripheral muscles, thus not reflecting the same ICPET cardiorespiratory capacity. / Objetivo: Verificar se o teste do degrau de seis minutos (TD6) permite avaliar a capacidade funcional aeróbia de pacientes com doença pulmonar obstrutiva crônica (DPOC) além de comparar, correlacionar e verificar se há concordância entre as variáveis metabólica (consumo de oxigênio-VO2), ventilatória (ventilação minuto-VE), cardiovascular (frequência cardíaca- FC) e de percepção de esforço entre o TD6 e o teste de exercício cardiopulmonar incremental (TECPI). Métodos: 18 pacientes com DPOC (cinco com obstrução leve, cinco moderada, seis grave e dois muito grave) executaram o TD6 e o TECPI submáximo em cicloergômetro (incrementos de 5 a 10W) em dias não coincidentes e não consecutivos. O TD6 foi realizado em um degrau cuja altura media 20cm e durante seis minutos os pacientes foram orientados a subir o mais rápido possível em cadência livre. Durante os testes foram avaliados o VO2, a VE, a FC, a sensação de dispneia (SD) e a sensação de fadiga de membros inferiores (SFMMII), por meio da escala de Borg. Resultados: Não houve diferenças significativas entre as médias dos valores de VO2, FC, VE, SD e SFMMII no pico de ambos os testes. Observaram-se correlações moderadas entre o desempenho no TD6 (número total de subidas no degrau) e o VO2 no TECPI (r=0,49;p=0,05) e entre o desempenho no TD6 com o desempenho no TECPI (r=0,63;p=0,005); correlações fortes entre os VO2 (L/min e mL/kg/min) (r=0,76 e r=0,77;p=0,001) e correlações moderadas das FC (r=0,68;p=0,002) e das SFMMII (r=0,59;p=0,011) entre os testes. Não se observou concordância entre os valores de VO2, FC e SFMMII entre os testes. Conclusão: O TD6 pode avaliar a capacidade funcional aeróbia e apresenta respostas cardiorrespiratórias e de percepção de esforço semelhantes ao TECPI em magnitude, porém não substitui o TECPI, uma vez que o TD6 não reflete a mesma capacidade cardiorrespiratória do TECPI por ser um teste que avalia e exige um trabalho maior e mais localizado da musculatura periférica.

Fundação de Amparo a Pesquisa do Estado de Minas Gerais / The muscle fatigue can be caused by multiple factors, and the most common one is bodywork. As a result, the muscle stress signal becomes part of atlets life. However, this phenom may show injuries incident, neuromuscular diseases, and it is related to the general human being health, as well as with its nutrition. To determine the fatigue level from a muscle or from a person is not that simple, because multiple subjective factors are envolved, including psychological and hormonal matters, thus maybe is not possible to determine an universal method for quantification of muscle fatigue. The electromyographic signal (EMG) is well known and studied for reflecting the musculature condition from which it was generated. The electromyography is an important tool for the health muscle assessment, and counts on various studies and advances in its formation and interpretation understanding.Thus, it is expected that the muscle fatigue that affects the natural muscle behavior, affects also the EMG signal. This work aims to understand how the fatigue action appears in the signal, through the study of different EMG signal characteristics. From literature, several studies analyzed isometric contractions, thus it was decided to make a dynamic contractions evaluation, which are more natural in the daily life. For the sake of simplicity, the biceps braquii was chosen. This muscle was estimulated by a scott biceps curl exercise, an exercise known to well isolate the working muscle, so that the weight lifting is almost all done by the biceps action. Pilot trial was done, collecting EMG signals from both biceps braquii, and also measuring the force applied to the bar. For the EMG signal analysis, three software packages were developed. One of them was a programm for the electromyographer control, and for the signals record- ing in text files without header. For this development were used C Sharp and .NET. One library for signals processing was developed using Matlab, including fil- ter functions, muscle activity detection and features extraction, such as amplitude, frequency, entropy, and stationarity. Finally, was developed a programm for feature analysis that uses the previous mentioned library, and that also applies the Kohonen algorithm of self-organizing maps.This programm was also developed using Matlab. All created programms are open source, and they are available for download on GitHub platform. A temporal analysis of the features was performed in order to cluster the results of the features extracted from the signals of 21 volunteers. This analysis showed that signal s amplitude increases as the fatigue occurs while there is a spectral shift for the left. This shift indicates that the main frequencies have decreased. The trends observed for amplitude and frequency are the same reported in the literature. The results also show decreasing in the entropy as effect of the fatigue progres- sion. Two stationarity features indicate decreasing in the stationarity, these were influenced by the amplitude raise, though. A third stationarity feature, which is not dependent on amplitude, show that there is not significant modification on the stationarity. The data clustering attempt using the Kohonen algorithm was frustrated, gener- ating inconclusive results. It can be concluded that the features related to amplitude, frequency and entropy are somehow related to the muscular fatigue. So that it is possible, during future work, the development of a fatigue classifier based on these features. / A fadiga muscular pode ser causada por diversos fatores, e o mais comum deles e o exercício físico. Isso faz com que esse sinal de estresse muscular faça parte da vida de atletas. No entanto, esse fenômeno pode indicar a ocorrência de lesões, doenças neuro-musculares e está ligado à saúde geral do indivíduo, bem como com a alimentação. Determinar o nível de fadiga de um músculo ou de um indivíduo em geral não é simples, pois vários aspectos subjetivos estão envolvidos, incluindo questões psicológicas e hormonais, e talvez não seja possível a determinação de um método universal de quanticação da fadiga muscular. O sinal eletromiográfico (EMG) é conhecido e estudado por refletir o estado da musculatura que o gerou. A eletromiografia é uma ferramenta importante para a avaliação da saúde muscular e conta com diversos estudos e avanços tanto no entendimento de sua formação quanto na sua interpretação. Assim, de antemão, espera-se que a fadiga muscular, que afeta o comportamento natural dos músculos, afete também o sinal eletromiográfico. Nesse trabalho, procurou-se entender, por meio do estudo de diferentes características do sinal EMG, como a ação da fadiga se manifesta no sinal. Na literatura, vários estudos analisam as contrações isométricas, assim decidiu-se por fazer uma avaliação de contrações dinâmicas, as quais são mais naturais no cotidiano. Por uma questão de simplicidade, o músculo escolhido foi o bíceps braquial. Esse músculo foi estimulado por um exercício de rosca em banco scott, um exercício conhecido por isolar bem o músculo trabalhado, de forma que o levantamento do peso é quase todo feito por ação do bíceps. Coletas piloto foram realizadas, nas quais o sinal EMG dos dois bíceps foi registrado em conjunto com a medida de força aplicada na barra. Para a análise dos sinais EMG, três pacotes de software foram desenvolvidos. Um deles foi um programa para controle do eletromiógrafo e registro dos sinais em arquivos texto com cabecalho. Para esse desenvolvimento, utilizou-se C Sharp e .NET. Uma biblioteca para processamento de sinais biológicos foi desenvolvida em Matlab, na qual encontram-se funções de filtragem, detecção de atividade muscular e extração de características tais como amplitude, frequência, entropia e estacionaridade. Por fim, desenvolveu-se um programa para análise de características que usa a biblioteca mencionada e também aplica o algortimo de mapas auto-organizáveis de Kohonnen. Esse programa também foi desenvolvido em Matlab. Todos os programas criados sâo de código aberto e estão disponíveis para download na plataforma GitHub. Uma analise temporal das características foi realizada de forma a agrupar os resultados das características extraídas dos sinais dos 21 voluntários. Essa análise mostrou que a amplitude do sinal aumentou com o avanço da fadiga muscular enquanto a frequência dos sinais se deslocou para esquerda no espectro. Isso indica que as frequências principais diminuiram. Essas tendências para amplitude e frequência são as mesmas registradas na literatura. O estudo mostrou ainda que a entropia diminui com a progressão da fadiga. Duas características de estacionaridade indicaram diminuição, no entanto foram influenciadas pela amplitude. Uma terceira característica, indepentende da amplitude, mostrou que não há alteração signicativa na estacionaridade. A tentativa de agrupamento dos dados com o algortimo de Kohonnen foi frustrada, ja que gerou resultados inconclusivos. Concluiu-se que as características de amplitude, frequência e entropia estão relacionadas com a fadiga muscular. Assim acredita-se ser possível desenvolver, em estudos futuros, um classificador de sinais EMG que faca inferência do nível de fadiga baseado nessas características. / Mestre em Ciências

Le conflit fémoro-acétabulaire (femoroacetabular impingement, FAI) est une pathologie mécanique de la hanche qui peut causer des douleurs et limitations fonctionnelles. Le but de cette thèse était d’étudier la fonction musculaire au niveau de la hanche chez des patients présentant un FAI symptomatique. La fonction musculaire de la hanche a été évaluée, dans un premier temps, chez des patients avant qu’ils ne subissent une opération. Ces patients démontraient un déficit de force qui pourrait être expliqué par de l’inhibition musculaire. Cependant, ce déficit de force n’était pas associé à une plus grande fatigabilité musculaire. Dans un deuxième temps, les altérations de force musculaire ont été évaluées chez des patients ayant subi une arthroscopie de la hanche. Après l’opération, les patients récupéraient un niveau de force normal au niveau de tous les groupes musculaires de la hanche excepté les fléchisseurs. Le cas d’un joueur de hockey sur glace ayant subi une chirurgie ouverte aux deux hanches pour traiter un FAI bilatéral a aussi été décrit. On a démontré que la déhiscence de la bandelette iléo-tibiale pouvait survenir après chirurgie, empêcher l’augmentation de force musculaire des abducteurs de la hanche, et retarder la reprise du sport. Enfin, un protocole d’évaluation du taux de développement de la force normalisé, variable permettant d’estimer l’inhibition musculaire de la hanche, a été proposé chez des sujets sains. La fiabilité et reproductibilité des résultats ont été montrées au niveau des adducteurs, rotateurs externes, et fléchisseurs de la hanche. Ces résultats montrent que ces patients ont une fonction musculaire altérée au niveau de la hanche, qui est toutefois récupéré après une opération. / Femoroacetabular impingement (FAI) is a pathomechanical process of the hip joint, which could lead to hip pain and functional disability. Aim of this thesis was to investigate hip muscle function in patients with a symptomatic FAI. Hip muscle function was first investigated before patients underwent any surgical treatment for managing FAI. It was shown that they present with reduced hip muscle strength (i.e., muscle weakness), probably due to hip muscle inhibition. Nevertheless, hip muscle weakness was not associated with exaggerated hip muscle fatigue. Hip muscle strength recovery was then evaluated in a series of patients after hip arthroscopy to treat FAI. These patients demonstrated a good recovery for all hip muscle groups, except for hip flexors. The case of a professional ice hockey player who underwent bilateral hip open surgeries for treating bilateral FAI was also documented. This report showed that iliotibial band dehiscence could occur after hip open surgery, thereby preventing hip abductor strength increase during rehabilitation and delaying the return to sport. In addition, the assessment of the rate of force development scaling factor for the hip muscles was evaluated in a group of healthy adults. This parameter seems to be promising for the evaluation of hip muscle inhibition. The testing protocol was feasible and reproducible for hip adductors, external rotators and flexors. Taken as a whole, these findings show that patients with symptomatic FAI demonstrate an impaired hip muscle function, which is however mainly resolved after surgical treatment.

La stimulation électrique fonctionnelle (SEF) a le potentiel de fournir une amélioration active aux blessés médullaires en termes de mobilité, de stabilité et de prévention des effets secondaires.Dans le domaine des système SEF pour les membres inférieurs, le couple articulaire adéquat doit être fournie de façon appropriée pour effectuer le mouvement prévu et maintenir l'équilibre postural. Toutefois, les changements d'état du muscle tels que la fatigue musculaire est une cause majeure qui dégrade ses performances. En outre, la plupart des patients, dont la blessure médullaire est complète, n'ont pas le retour sensorielle qui permet de détecter la fatigue et les capteurs de couples in-vivo ne sont pas disponible à l'heure actuelle. Les systèmes conventionnels de commande SEF sont soit en boucle ouverte ou pas assez robustes aux changements d'état du muscle. L'objectif de cette thèse est le développement de la prédiction du couple articulaire et la commande en boucle fermée afin d'améliorer les performances de la commande SEF en termes de précision, de robustesse et de sécurité pour les patients.Afin de prédire le couple articulaire induit de la SEF, l'électromyographie (EMG) induit est utilisé pour corréler l'activité musculaire électrique et mécanique. Bien que la fatigue musculaire représente une variation dans le temps, une dépendance aux sujets et aux protocoles, la méthode proposée d'identification adaptative, basée sur le filtre de Kalman, est capable de prédire le couple articulaire variant dans le temps de manière systématique. La robustesse de la prédiction du couple articulaire a été évaluée lors d'une tâche de suivi de la fatigue en expérimentation chez des sujets blessés médulaires.Les résultats montrent une bonne performance de suivi des variations d'état des muscles en présence de fatigue et face à d'autres perturbations. Basé sur les performances de précision de la méthode prédictive proposée, une nouvelle stratégie de commande basée sur le retour EMG, «EMG-Feedback Predictive Control» (EFPC), est proposée afin de contrôler de manière adaptative les séquences de stimulation en compensant la variation dans le temps de l'état du muscle. De plus, cette stratégie de commande permet explicitement d'éviter d'appliquer une stimulation excessive aux patients, et de générer les séquences de stimulation appropriées pour obtenir la trajectoire désirée des couples articulaires. / Functional electrical stimulation (FES) has the potential to provide active improvement to spinal cord injured (SCI) patients in terms of mobility, stability and side-effect prevention. In the domain of lower limb FES system, elicited muscle force must be provided appropriately to perform intended movement and the torque generation by FES should be accurate not to lose the posture balance. However, muscle state changes such as muscle fatigue is a major cause which degrades its performance. In addition, most of the complete SCI patients don't have sensory feedback to detect the fatigue and in-vivo joint torque sensor is not available yet. Conventional FES control systems are either in open-loop or not robust to muscle state changes. This thesis aims at a development of joint torque prediction and feedback control in order to enhance the FES performance in terms of accuracy, robustness, and safety to the patients.In order to predict FES-induced joint torque, evoked-Electromyography (eEMG) has been applied to correlate muscle electrical activity and mechanical activity. Although muscle fatigue represents time-variant, subject-specific and protocol-specific characteristics, the proposed Kalman filter-based adaptive identification was able to predict the time-variant torque systematically. The robustness of the torque prediction has been investigated in a fatigue tracking task in experiment with SCI subjects. The results demonstrated good tracking performance for muscle variations and against some disturbances.Based on accurate predictive performance of the proposed method, a new control strategy, EMG-Feedback Predictive Control (EFPC), was proposed to adaptively control stimulation pattern compensating to time-varying muscle state changes. In addition, this control strategy was able to explicitly avoid overstimulation to the patients, and conveniently generate appropriate stimulation pattern for desired torque trajectory.

Les travaux présentés dans cette mémoire visent à développer de nouvelles méthodes qui exploitent les propriétés de cyclostationnarité pour traiter des signaux de force de réaction du sol enregistrées au cours de la marche et la course à pied. Nous nous intéressons à l’analyse de la locomotion humaine dans trois domaines d´études: une étude liée à la pathologie, une deuxième liée directement à l’âge et une troisième relative à la fatigue. En effet, la détection du risque de chute chez les personnes âgées pour fin de prévention contre la chute constitue un enjeu majeur, car cette chute entraine d’une part un nombre de décès important et d’autres part se traduit par un cout élevée de la santé publique. Par ailleurs, l’étude de la fatigue musculaire en particulier pour l’amélioration des performances des sportifs de haut niveau a fait l’objet de nombreux travaux de recherche & développement. La recherche et le développement de nouvelles méthodes et d’indicateurs dans le domaine de traitement de signal dans le but de caractériser la locomotive humaine, permettrait des avancées intéressantes dans les enjeux évoqués ci-dessus. La complexité des signaux GRF est définie par le système neuromusculaire qui génère ce signal. Une meilleure connaissance de ce système nécessite le développement des méthodes de séparation de sources et des outils avancés de traitement du signal pour mieux décrire le système considéré. En effet, nous montrons dans cette thèse que les signaux GRF peuvent être modélisés dans un cadre cyclostationnaire élargi. Les composantes de signal GRF (contribution active et passive) sont séparées par de nouvelles techniques de séparation de sources. Cette modélisation ouvre de nouvelles perspectives pour la décomposition et identification des sources individuelles. D'autre part, on exploite les caractères cyclostationnaire des signaux dans le cadre de la méthode d'analyse en composantes morphologique (MCA). Cet algorithme nous permet de séparer avec succès les composantes d’ordre 1 et d’ordre 2 des signaux considérés. Finalement, nous nous proposons un nouveau modèle utile pour l'étude et la caractérisation de cyclostationnarité. Il présente l'effet de la variation aléatoire de la pente sur le spectre du signal cyclique. Nous appelons ce modèle (modèle cyclostationnaire à pente aléatoire). Nous appliquons ce modèle pour l'étude des signaux biomécaniques où nous considérons la pente comme une mesure spécifique extraite des forces de réaction du sol. Les résultats montrent que la pente et les polynômes à coefficients aléatoires du pic passive peuvent jouer un rôle important et fournir des informations intéressantes concernant la fatigue et concernant la performance de marche et course à pied / The research work presented in this dissertation, involves the development of novel methodologies and methods, for the exploitation of cyclostationarity properties and for the treatment of ground reaction force signals, recorded during walking and running. We are especially interested in the analysis of human locomotion in three fields of interest: a study relating to pathology, a study directly related to age, and a study of muscle fatigue. Indeed, the detection of risk of falling among the elderly for the prevention of falls is of major concern. This is because falling on the one hand leads to a large number of deaths and secondly, resulting in higher costs of public health.Study the muscle fatigue in particular has occupied taken a big share out of this research due to the importance of such events like strenuous level of sports. Research and development of new methods and indicators in the field of signal processing for better characterizing the human locomotion, would allow interesting advances in the aforementioned issues. The complexity of GRF signals is defined by the neuromuscular system which generates this signal. Improved knowledge of this system requires developing source separation methods and advanced signal processing tools to better describe the system under consideration. Indeed, we will endeavor to show in this dissertation that GRF signals can be modeled within an enlarged cyclostationary framework. The GRF signal components (active and passive contribution) are separated by means of new source separation techniques. This modeling opens new perspectives for the decomposition and identification of individual sources. On the other hand, we exploit the cyclostationary characters of signals in the context of Morphological component analysis (MCA) method. Such algorithm enables us to successfully separate the first and second order components of the signals under consideration. Finally, we provide a new model useful for studying and characterizing cyclostationarity. It presents the impact of random slope variation on the cyclic spectrum of the signal. We call this model the random slope modulation (RSM). We apply this model for studying biomechanical signals where we consider the slope as a specic measure extracted from the vertical ground reaction forces. The results show that the slope and polynomial random coefficients of passive peaks can play important role and provide interesting information concerning fatigue and concerning running / walking performance

Muscle fatigue is a severe problem for elite athletes, and this is due to the long resting times, which can vary. Various mechanisms can cause muscle fatigue which signifies that the specific muscle has reached its maximum force and cannot continue the task. This thesis was about surveying and exploring state-of-the-art methods and systematically, theoretically, and practically testing the applicability and performance of more recent machine learning methods on an existing EMG to muscle fatigue pipeline. Several challenges within the EMG domain exist, such as inadequate data, finding the most suitable model, and how they should be addressed to achieve reliable prediction. This required approaches for addressing these problems by combining and comparing various state-of-the-art methodologies, such as data augmentation techniques for upsampling, spectrogram methods for signal processing, and transfer learning to gain a reliable prediction by various pre-trained CNN models. The approach during this study was to conduct seven experiments consisting of a classification task that aims to predict muscle fatigue in various stages. These stages are divided into 7 classes from 0-6, and higher classes represent a fatigued muscle. In the tabular part of the experiments, the Decision Tree, Random Forest, and Support Vector Machine (SVM) were trained, and the accuracy was determined. A similar approach was made for the spectrogram part, where the signals were converted to spectrogram images, and with a combination of traditional- and intelligent data augmentation techniques, such as noise and DCGAN, the limited dataset was increased. A comparison between the performance of AlexNet, VGG16, DenseNet, and InceptionV3 pre-trained CNN models was made to predict differences in jump heights. The result was evaluated by implementing baseline classifiers on tabular data and pre-trained CNN model classifiers for CWT and STFT spectrograms with and without data augmentation. The evaluation of various state-of-the-art methodologies for a classification problem showed that DenseNet and VGG16 gave a reliable accuracy of 89.8 % on intelligent data augmented CWT images. The intelligent data augmentation applied on CWT images allows the pre-trained CNN models to learn features that can generalize unseen data. Proving that the combination of state-of-the-art methods can be introduced and address the challenges within the EMG domain.

La répétition d’efforts de faible intensité provoque de la fatigue musculaire et représente un facteur de risque de développement des troubles musculosquelettiques (TMS) à l’épaule. La détection de la fatigue musculaire permettrait de meilleures interventions de prévention de TMS liés au travail répétitif. L’objectif de ce mémoire est de développer de nouveaux indicateurs permettant d’évaluer le mouvement des travailleurs à l’aide de capteurs inertiels portatifs afin d’offrir un outil d’évaluation du niveau de fatigue employable sur le terrain. Pour ce faire, vingt-quatre travailleurs ont réalisé une tâche de travail avant et après une tâche de pointage répétitif (RPT) générant de la fatigue musculaire. La fatigue était évaluée à l’aide de l'échelle CR10 de Borg toutes les 30s et d’une contraction maximale réalisée toutes les 2 minutes. Des données de capteurs inertiels, positionnés sur le tronc et les membres supérieurs des travailleurs, ont été analysées en temps-fréquence et leur coordination inter-segment calculée afin d’extraire des indicateurs de fatigue. Les résultats montrent une augmentation du spectre de puissance et de la variabilité de la coordination sur les segments proximaux du haut du corps (tête, sternum, bassin, épaule, bras, avant-bras et main) pendant la RPT. Aussi, une augmentation du spectre de puissance moyen a été observée sur les segments du bras (main, avant-bras et bras supérieur) pendant la tâche de travail réalisée immédiatement après la RPT. En conclusion, il semblerait possible, en observant de tels changements cinématiques, de détecter la fatigue musculaire des travailleurs en industrie à l’aide de capteurs inertiels. / The repetition of low-intensity efforts causes muscle fatigue and represents a risk factor for the development of musculoskeletal disorders (MSD) in the shoulder. The detection of muscle fatigue would allow for better interventions to prevent MSDs related to repetitive work. The objective of this dissertation is to develop new indicators to evaluate the movement of workers using portable inertial sensors to provide a tool for evaluating the level of fatigue that can be used in the field. To do this, twenty-four workers performed a work task before and after a repetitive pointing task (RPT) generating muscle fatigue. Fatigue was assessed using the Borg CR10 scale every 30s and a maximal contraction performed every 2 minutes. Data from inertial sensors, positioned on the trunk and upper limbs of the workers, were analyzed in time-frequency and their inter-segment coordination calculated to extract indicators of fatigue. The results show an increase in the power spectrum and coordination variability on the proximal upper body segments (head, sternum, pelvis, shoulder, arm, forearm and hand) during RPT. Also, an increase in the average power spectrum was observed over the arm segments (hand, forearm, and upper arm) during the work task performed immediately after RPT. In conclusion, it would seem possible, by observing such changes in kinematics, to detect muscle fatigue in industrial workers using inertial sensors.

Early detection of unilateral muscle fatigue and muscular imbalances is important to prevent injury. This study aimed to evaluate the potential of near-infrared thermography (IRT) and raster-stereography (RS) in detecting asymmetries. After unilateral trunk muscle fatigue, IRT detected changes in the skin surface temperature only immediately after exercise, while RS data showed no statistically significant changes. / Die frühzeitige Erkennung von einseitiger Muskelermüdung und muskulären Ungleichgewichten ist wichtig, um Verletzungen vorzubeugen. Ziel dieser Studie war es, das Potenzial der Nahinfrarot-Thermografie (IRT) und der Rasterstereografie (RS) bei der Erkennung von Asymmetrien zu bewerten. Nach einseitiger Ermüdung der Rumpfmuskulatur wurden mit der IRT Veränderungen der Hautoberflächentemperatur nur unmittelbar nach der Belastung festgestellt, während die RS-Daten keine statistisch signifikanten Veränderungen zeigten.