O objetivo deste estudo foi analisar e comparar os efeitos de 12 semanas do treinamento de força (TF) com o treinamento de força com instabilidade (TFI) nos desfechos clínicos, na capacidade de produção de força muscular, nos mecanismos inibitórios espinhais e no volume total de treinamento (VTT) de indivíduos entre os estágios 2 e 3 da doença de Parkinson (DP). Para tanto, 39 indivíduos (testados e treinados no estado \"on\" da medicação) atenderam aos critérios de inclusão e foram randomizados em três grupos: grupo controle nenhum exercício (GC), grupo TF (GTF) e grupo TFI (GTFI). O GTF e o GTFI realizaram 12 semanas de TF orientado à hipertrofia, duas vezes por semana, em dias não consecutivos. Apenas o GTFI adicionou acessórios de instabilidade (e.g., BOSU®) ao TF que progrediram dos menos para os mais instáveis. Antes e após as 12 semanas foram avaliados os seguintes desfechos: a) clínicos - mobilidade (desfecho primário), sintomas motores, comprometimento cognitivo, medo de cair, equilíbrio, desempenho da marcha (distância, cadência e velocidade) em condições de dupla tarefa e qualidade de vida; b) capacidade de produção de força muscular - raiz quadrada média (RMS), mean spike frequency (MSF) e retardo eletromecânico (REM) dos músculos vasto lateral, vasto medial e gastrocnêmio medial; pico de torque, taxa de desenvolvimento de torque (TDT) e tempo de meio relaxamento (TMR) dos músculos extensores do joelho e flexores plantares; uma repetição máxima (1RM) dos membros inferiores e área de secção transversa do músculo quadríceps femoral (ASTQ) e; c) mecanismos inibitórios espinhais - inibições pré-sináptica e recíproca do músculo sóleus. O VTT foi avaliado durante o protocolo experimental para os exercícios agachamento, flexão plantar e leg-press. Do pré ao pós-treinamento, somente o GTFI melhorou todos os desfechos clínicos (P<0,05), os desfechos da capacidade de produção de força muscular (P<0,05) com exceção do TMR dos músculos extensores de joelho (P=0.068) e melhorou os desfechos dos mecanismos inibitórios espinhais (P<0,05). Houve diferenças significantes entre o GTFI e o GC no pós-treinamento para os seguintes desfechos: mobilidade, comprometimento cognitivo, equilíbrio, desempenho na marcha em condições de dupla tarefa (distância, cadência e velocidade), RMS de todos os músculos avaliados, MSF do músculo gastrocnêmio medial, pico de torque e TDT dos flexores plantares, pico de torque dos extensores de joelho, 1RM dos membros inferiores e inibições pré-sináptica e recíproca (P<0,05). Além disso, o GTFI apresentou melhores valores do que o GTF para os seguintes desfechos: desempenho na marcha em condições de dupla tarefa (distância e velocidade), RMS do músculo vasto medial, MSF do músculo gastrocnêmio medial, TDT dos flexores plantares e inibições pré-sináptica e recíproca (P<0,05). O GTFI apresentou um menor VTT comparado ao GTF (P<0,05). Por fim, nenhum efeito adverso foi observado. Em conclusão, somente o TFI melhorou os desfechos clínicos e foi mais efetivo do que o TF em promover adaptações neuromusculares mesmo com um menor VTT. Assim, o TFI é recomendado como uma inovadora intervenção terapêutica para minimizar os declínios na mobilidade e em um amplo espectro de deficiências, sem causar efeitos adversos em indivíduos com DP / The aim of this study was to analyze and to compare the effects of 12 weeks of strength training (ST) with strength training with instability (STI) on clinical outcomes, muscle-force-production capacity, spinal inhibitory mechanisms and the total training volume (TTV) of individuals between stages 2 and 3 of Parkinson\'s disease (PD). For this, 39 individuals (assessed and trained in the clinically defined \"on\" state) met the inclusion criteria and were randomized into three groups: non-exercising control group (CG), ST group (STG) and STI group (STIG). The STG and STIG performed 12 weeks hypertrophy-oriented ST, twice a week, on non-consecutive days. Only STIG added unstable devices (e.g., BOSU®) to ST that progressed from the less to the more unstable devices. Before and after 12 weeks were assessed the following outcomes: a) clinical - mobility (primary outcome), motor symptoms, cognitive impairment, fear of falling, balance, dual-task gait performance (distance, cadence, and, velocity), and quality of life; b) muscle-force-production capacity - root mean square (RMS), mean spike frequency (MSF), and electromechanical delay (EMD) of the vastus lateralis, vastus medialis, and gastrocnemius medialis; peak torque, rate of torque development (RTD) and half-relaxation time (HRT) of the knee-extensors and plantar flexors; one repetition maximum (1-RM) of the lower limbs and quadriceps cross sectional area (QCSA) and; c) spinal inhibitory mechanisms - presynaptic inhibition and reciprocal inhibition of the soleus muscle. The TTV for each lower limb exercise (half-squat, plantar flexion, and leg-press) was determined during the experimental protocol. From pre- to post-training, only the STIG improved all of the clinical outcomes (P <0.05), the muscle-force-production capacity outcomes (P <0.05) with exception of the HRT of the knee-extensors (P = 0.068) and, improved the spinal inhibitory mechanisms outcomes (P <0.05). There were differences between the STIG and the CG for the following outcomes: mobility, cognitive impairment, balance, dual-task gait performance (distance, cadence, and speed), RMS all of the muscles assessed, MSF of the gastrocnemius medialis, peak torque and RTD of the plantar flexor, peak torque of the knee-extensors, 1RM of the lower limbs, presynaptic inhibition, and reciprocal inhibition at post-training (P <0.05). Moreover, the STIG showed better values than the STG for the following outcomes: dual-task gait performance (distance and speed), RMS of the vastus medialis, MSF of the gastrocnemius medialis, RTD of the plantar flexors, presynaptic inhibition, and reciprocal inhibition at post-training (P <0.05). The STIG showed a lower TTV than the STG (P <0.05). Finally, no adverse effects were observed. In conclusion, only the STIG improved all of the clinical outcomes and it was more effective than the STG to promote neuromuscular adaptations even the STIG has had a lower TTV than the STG. Thus, STI is recommended as a novel therapeutic intervention to minimize declines in mobility and in a wide spectrum of impairments without causing adverse effects in individuals with PD

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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.