The purpose of this study was to examine the relationships between muscle cross-sectional area (CSA), maximal strength, power output, and maximum potentiation characteristics. The vastus lateralis and biceps femoris CSA, one repetition maximum (1RM) back squat, 1RM concentric-only half-squat (COHS) strength, static jump power output, and maximum potentiation characteristics of 17 resistance-trained men was assessed during several testing sessions. Pearson’s correlation coefficients were used to examine the relationships between CSA, strength, power output, and maximum potentiation measures. Moderate-to-strong relationships existed between CSA and strength measures (r = 0.462–0.643) as well as power output (r = 0.396–0.683). In addition, moderate-to-strong relationships existed between strength and power output (r = 0.407–0.548), while trivial relationships existed between strength and maximum potentiation (r = −0.013–0.149). Finally, small negative relationships existed between CSA and maximum potentiation measures (r = −0.229–−0.239). The results of the current study provide evidence of the interplay between muscle CSA, strength, power, and potentiation. Vastus lateralis and biceps femoris CSA may positively influence an individual’s back squat and COHS maximal strength and squat jump peak power; however, muscle CSA and absolute strength measures may not contribute to an individual’s potentiation capacity. Practitioners may consider implementing resistance training strategies that improve vastus lateralis and biceps femoris size in order to benefit back squat and COHS strength. Furthermore, implementing squatting variations—both full and partial—may benefit jumping performance.

Les systèmes neuromusculaires et musculo-squelettique sont considérés comme un système de systèmes complexe. En effet, le mouvement du corps humain est contrôlé par le système nerveux central par l'activation des cellules musculaires squelettiques. L'activation du muscle produit deux phénomènes différents : mécanique et électrique. Ces deux activités possèdent des propriétés différentes, mais l'activité mécanique ne peut avoir lieu sans l'activité électrique et réciproquement. L'activité mécanique de la contraction du muscle squelettique est responsable du mouvement. Le mouvement étant primordial pour la vie humaine, il est crucial de comprendre son fonctionnement et sa génération qui pourront aider à détecter des déficiences dans les systèmes neuromusculaire et musculo-squelettique. Ce mouvement est décrit par les forces musculaires et les moments agissant sur une articulation particulière. En conséquence, les systèmes neuromusculaires et musculo-squelettique peuvent être évalués avec le diagnostic et le management des maladies neurologiques et orthopédiques à travers l'estimation de la force. Néanmoins, la force produite par un seul muscle ne peut être mesurée que par une technique très invasive. C'est pour cela, que l'estimation de cette force reste l'un des grands challenges de la biomécanique. De plus, comme dit précédemment, l'activation musculaire possède aussi une réponse électrique qui est corrélée à la réponse mécanique. Cette résultante électrique est appelée l'électromyogramme (EMG) et peut être mesurée d'une façon non invasive à l'aide d'électrodes de surface. L'EMG est la somme des trains de potentiel d'action d'unité motrice qui sont responsable de la contraction musculaire et de la génération du mouvement. Ce signal électrique peut être mesuré par des électrodes à la surface de la peau et est appelé I'EMG de surface {sEMG). Pour un muscle unique, en supposant que la relation entre l'amplitude du sEMG et la force est monotone, plusieurs études ont essayé d'estimer cette force en développant des modèles actionnés par ce signal. Toutefois, ces modèles contiennent plusieurs limites à cause des hypothèses irréalistes par rapport à l'activation neurale. Dans cette thèse, nous proposons un nouveau modèle de relation sEMG/force en intégrant ce qu'on appelle le sEMG haute définition (HD-sEMG), qui est une nouvelle technique d'enregistrement des signaux sEMG ayant démontré une meilleure estimation de la force en surmontant le problème de la position de l'électrode sur le muscle. Ce modèle de relation sEMG/force sera développé dans un contexte sans fatigue pour des contractions isométriques, isotoniques et anisotoniques du Biceps Brachii (BB) lors une flexion isométrique de l'articulation du coude à 90°. / The neuromuscular and musculoskeletal systems are complex System of Systems (SoS) that perfectly interact to provide motion. This interaction is illustrated by the muscular force, generated by muscle activation driven by the Central Nervous System (CNS) which pilots joint motion. The knowledge of the force level is highly important in biomechanical and clinical applications. However, the recording of the force produced by a unique muscle is impossible using noninvasive procedures. Therefore, it is necessary to develop a way to estimate it. The muscle activation also generates another electric phenomenon, measured at the skin using electrodes, namely the surface electromyogram (sEMG). ln the biomechanics literature, several models of the sEMG/force relationship are provided. They are principally used to command musculoskeletal models. However, these models suffer from several important limitations such lacks of physiological realism, personalization, and representability when using single sEMG channel input. ln this work, we propose to construct a model of the sEMG/force relationship for the Biceps Brachii (BB) based on the data analysis of a High Density sEMG (HD-sEMG) sensor network. For this purpose, we first have to prepare the data for the processing stage by denoising the sEMG signals and removing the parasite signals. Therefore, we propose a HD-sEMG denoising procedure based on Canonical Correlation Analysis (CCA) that removes two types of noise that degrade the sEMG signals and a source separation method that combines CCA and image segmentation in order to separate the electrical activities of the BB and the Brachialis (BR). Second, we have to extract the information from an 8 X 8 HD-sEMG electrode grid in order to form the input of the sEMG/force model Thusly, we investigated different parameters that describe muscle activation and can affect the relationship shape then we applied data fusion through an image segmentation algorithm. Finally, we proposed a new HDsEMG/force relationship, using simulated data from a realistic HD-sEMG generation model of the BB and a Twitch based model to estimate a specific force profile corresponding to a specific sEMG sensor network and muscle configuration. Then, we tested this new relationship in force estimation using both machine learning and analytical approaches. This study is motivated by the impossibility of obtaining the intrinsic force from one muscle in experimentation.

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

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Pertinence. Compléter des tests d’endurance cardiorespiratoire maximaux basés sur la performance chez les utilisateurs de fauteuils roulants manuels est très pertinent pour développer des programmes d'entraînement cardiorespiratoire personnalisés et pour évaluer leurs impacts au fil du temps. Cependant, ces tests augmentent potentiellement l’exposition au risque de développement de troubles musculosquelettiques secondaires aux membres supérieurs, particulièrement aux épaules. Par conséquent, il est fondamental de trouver un équilibre entre la nécessité de mesurer la capacité aérobie et le risque accru de développer des troubles musculosquelettiques secondaires lors de la réalisation d'un test basé sur les performances. Objectif. Caractériser les effets de la performance d’un test de propulsion progressif par paliers sur tapis roulant sur l'intégrité des tendons de la longue portion du biceps et du supra-épineux en utilisant des biomarqueurs obtenus via l'imagerie musculosquelettique par ultrasonographie. Méthode. Quinze utilisateurs de fauteuils roulants manuels vivant avec une lésion chronique de la moelle épinière ont complété le test de propulsion progressif par paliers sur tapis roulant. Des images des tendons de la longue portion du biceps et du supra- épineux ont été enregistrées avec un appareil d’imagerie musculosquelettique par ultrasonographie dans les plans transversal et longitudinal avant, immédiatement après et 48 heures après la fin du test en suivant un protocole standardisé. Des biomarqueurs ultrasonographiques liés à la géométrie, à la luminosité et à la texture d’une région d’intérêt ont permis de caractériser l'intégrité des tendons. Résultats. Les participants ont propulsé en moyenne pendant 10,2 ± 2,9 minutes alors que la majorité d’entre eux (N = 13/15) a atteint au moins le huitième stade du test (vitesse = 0,8 m / s; pente = 3,6 ̊). Aucun des biomarqueurs géométriques, de luminosité et de texture caractérisant l'intégrité des deux tendons, mesurés dans les plans longitudinal et transverse, n’a changé de façon significative (p = 0,063 à 1 000) entre les trois temps de mesure. Conclusion. La performance du test de propulsion progressif par paliers sur tapis roulant motorisé pour évaluer la capacité aérobie n'amène aucun changement délétère observable immédiatement après et 48 heures après la réalisation du test. / Relevance. The completion of performance-based maximal cardiorespiratory fitness tests among manual wheelchair user is highly relevant to develop personalized cardiorespiratory fitness training programs and to assess their impacts over time. However, these tests could potentially increase risk exposure for the development of upper limb secondary musculoskeletal impairments specifically to the shoulder. Hence, finding an equilibrium between the need to measure aerobic fitness and the increased risk of developing secondary musculoskeletal impairments when completing performance-based test is fundamental. Objective. To characterize the effect of the completion of a recently- developed treadmill-based progressive workload incremental test on the integrity of the long head of the biceps and supraspinatus tendons using musculoskeletal ultrasound imaging biomarkers. Method. Fifteen manual wheelchair users living with a spinal cord injury completed the treadmill-based progressive workload incremental test. Ultrasound images of the long head of the biceps and supraspinatus tendons were recorded with a musculoskeletal ultrasound imaging device in the transversal and longitudinal planes before, immediately after, and 48 hours after the completion of the test using a standardized protocol. Geometric, luminosity, and texture-related ultrasound biomarkers of a region of interest have characterized tendon integrity. Results. The participants propelled an average of 10.2 ± 2.9 minutes with the majority (N = 13/15) reached at least the eighth stage of the test (speed = 0.8 m/s; slope = 3.6 ̊). None of the geometric, luminosity and texture biomarkers characterizing the integrity of the two tendons, measured in the longitudinal and transversal planes, changed significantly (p=0.063 to 1.000) between the three measurement times. Conclusion. The performance of the treadmill-based progressive workload propulsion test to assess aerobic capacity does not result in any observable deleterious change immediately after and 48 hrs after the performance of the test.

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The purpose of this experiment was to investigate skeletal muscle blood flow and glucose uptake in m. biceps (BF) and m. quadriceps femoris (QF) 1) during recovery from high intensity cycle exercise, and 2) while wearing a compression short applying ~37 mmHg to the thigh muscles. Blood flow and glucose uptake were measured in the compressed and non-compressed leg of 6 healthy men by using positron emission tomography. At baseline blood flow in QF (P = 0.79) and BF (P = 0.90) did not differ between the compressed and the non-compressed leg. During recovery muscle blood flow was higher compared to baseline in both compressed (P&lt;0.01) and non-compressed QF (P&lt;0.001) but not in compressed (P = 0.41) and non-compressed BF (P = 0.05; effect size = 2.74). During recovery blood flow was lower in compressed QF (P&lt;0.01) but not in BF (P = 0.26) compared to the non-compressed muscles. During baseline and recovery no differences in blood flow were detected between the superficial and deep parts of QF in both, compressed (baseline P = 0.79; recovery P = 0.68) and non-compressed leg (baseline P = 0.64; recovery P = 0.06). During recovery glucose uptake was higher in QF compared to BF in both conditions (P&lt;0.01) with no difference between the compressed and non-compressed thigh. Glucose uptake was higher in the deep compared to the superficial parts of QF (compression leg P = 0.02). These results demonstrate that wearing compression shorts with ~37 mmHg of external pressure reduces blood flow both in the deep and superficial regions of muscle tissue during recovery from high intensity exercise but does not affect glucose uptake in BF and QF. © 2013 Sperlich et al. / <p>:doi 10.1371/journal.pone.0060923</p>