The goal of this thesis is to use biomechanical data describing shoulder motion to determine optimal parameters to assist in the design of a 5 DOF active shoulder exoskeleton. This thesis will provide a proof of concept on optimization techniques using motion data using a simplified 3 DOF model to facilitate future work implementing a full 5 DOF model. Optimization will be performed to determine the link lengths and, consequently, the locations of the joints of the exoskeleton by considering the human's workspace to maximize range of motion and promote user safety by minimizing collisions of the exoskeleton with the user and with the exoskeleton itself. The thesis will detail the development of computational models of the human and proposed exoskeleton, the processing of experimental data used to estimate the human's capabilities, optimization, and future work. This work will contribute to a large-scale NSF-funded project of building an upper body exoskeleton emulator. The emulator will promote the widespread adoption of exoskeletons in industry by providing a test-bed to streamline the rapid design of various assistance profiles for various users and tasks. / Master of Science / An exoskeleton is a robotic assistive device used in industrial and rehabilitative settings. This thesis will use data describing how the human shoulder moves during certain tasks to help design an exoskeleton to assist with theses tasks. A model of the human shoulder and a model of the exoskeleton will be developed and used in an optimization to figure out the best dimensions of the exoskeleton links to support the human's movements.

The hands are essential for our ability to complete tasks. Quantifying the many forces acting on the entire hand is important to improve our understanding of hand function and hand-related musculoskeletal disorders. Biomechanical models of the hand used to compute internal tissue loads typically simplify the applied forces into a single point of force applied at the centre of mass of the distal phalanx. Accounting for the distributed loads across the hands and fingers is a needed step in understanding the loads acting on and inside the body. Therefore, the purpose of this thesis was to use a pressure mapping system to examine the effects of distributed loads on net joint moments and muscle activations in the hands during common tasks. Twenty-three right-handed participants completed a series of finger presses, power grips, and pinch tasks. A pressure mapping system measured pressure on 17 regions of the hand. Three- dimensional hand kinematics was collected using a 72-marker setup. Forces were also measured with a six degrees of freedom force transducer to ensure participants matched specified exertion levels. Pressure distribution, kinematics, and kinetics were used to calculate internal net joint moments at the fingers (distal phalangeal flexion, proximal phalangeal flexion, metacarpal flexion, metacarpal abduction) and muscle activations for 22 forearm and hand muscles using an OpenSim model. External loads were represented in three manners: (1) Centre of Mass Model (COM) distributed the forces over segments that contributed to the force production and placed loads at the centre of mass; (2) Centre of Pressure Model (COP) distributed the forces over segments that contributed to the force production and placed loads at the centre of pressure; (3) Single Point Model (SP) placed a single load at the distal phalanx or the centre of mass of the hand. Results of equivalence tests indicate differences in all net joint moments between COM-SP and COP-SP comparisons. There were no differences between COM and COP. COM and COP moments during all tasks were larger in digits with a larger percentage of total force compared to SP. Due to the larger moments in those conditions, COM and COP calculated larger muscle activities compared to SP. Both internal net joint moments and muscle activations were most affected by the pressure distribution and hand posture. Overall, these findings indicate that representing external forces using distributed loads provide increased fidelity of forces at the hand and fingers. Distributed loads provide more information on internal loads of the hand and digits, and in turn, quantify individual differences that can lead to injury in occupational settings. / Thesis / Master of Science in Kinesiology

Manual material handling (MMH) tasks are associated with the development of work-related musculoskeletal disorders (WMSDs). Minimizing the frequency and intensity of handling objects is an ideal solution, yet MMH remains an integral part of many industry sectors, including manufacturing, construction, warehousing, and distribution. Physical exposure assessment can help identify high-risk tasks, guide the development and evaluation of ergonomic interventions, and contribute to understanding exposure-risk relationships. Physical exposure can be evaluated using self-assessment, observational methods, and direct measurements. Nevertheless, implementing these methods in situ can be challenging, time consuming, expensive, and infeasible or inaccurate in many cases. Thus, there is a critical need to improve physical exposure assessments to protect workers and save costs. This dissertation assessed the accuracy of a markerless motion capture system (MMC) to quantify physical exposures during MMH tasks using three studies. Specifically, the first study investigated the performance of an MMC system, together with machine learning algorithms, for classifying diverse MMH tasks during a simulated complex job. In the second study, the feasibility of predicting dynamic hand forces was determined, using alternative measures, such as kinematics from MMC and/or in-sole pressure systems, coupled with a machine learning algorithm. Finally, in the third study, we systematically evaluated MMC for assessing biomechanical demands, by comparing outputs from a full-body musculoskeletal model driven by kinematic and kinetics from gold standard input and estimates derived from the MMC and in-sole pressure measurement system. Overall, the findings of these studies demonstrated the potential of using MMC to classify several common occupational tasks and to estimate the associated biomechanical demands for a given worker (automatically and with minimal physical contact). Additionally, the methods developed here can help stakeholders rapidly assess an individual worker's exposure to physical demands during diverse tasks. / Doctor of Philosophy / Manual material handling (MMH) tasks expose workers to known risk factors for work-related musculoskeletal disorders (WMSDs) such as back and shoulder pain. Accurately quantifying workplace exposures to these risk factors is an essential aspect of identifying high-risk working conditions and for developing/evaluating workplace interventions to reduce WMSD risks. Current physical exposure assessment tools are labor-intensive, offer crude measures, and have limited application due to costs or feasibility. Using markerless motion capture (MMC) systems in the workplace could enable full or partial automation for the collection of critical measures such as the tasks a worker performs, the hand forces involved, and their biomechanical demands. New approaches are needed, though, since such automation is challenging due to variations in the type of input data required for different physical exposure assessments. In this dissertation, our goal was to assess the accuracy of MMC as a tool to quantify physical exposures during MMH tasks. In support of our goal, three studies were completed. In the first study, we investigated the accuracy of using data from MMC together with machine learning algorithms to classify diverse MMH tasks, and distinguish among different task conditions. Our results emphasized that classification performance was satisfactory, though it differed between feature sets, MMH tasks, and between males and females. The second study explored combining MMC and IPM data with machine learning algorithms to predict hand forces during MMH tasks. Our results were encouraging overall, but predictions were less accurate in pushing and pulling tasks. In the third study, we evaluated an approach for estimating biomechanical demands on data obtained from MMC and in-sole pressure measurement systems. We compared estimates from a musculoskeletal model driven by kinematics from a whole-body inertial measurement unit and kinetics from direct measures of hand loads, and kinematics from MMC. Our findings support using MMC and kinetics from predicted hand forces as input for estimating biomechanical demands. Overall, findings from these studies show that MMC can automatically classify common occupational tasks, predict dynamic hand forces, and estimate biomechanical demands with minimal physical contact. This new approach could allow stakeholders to assess worker's exposure and the efficiency of ergonomic interventions.

<p>During the last six million years, humans shifted from a primarily arboreal lifestyle to a habitually bipedal, terrestrial lifestyle. Australopithecus had a significant bipedal component to its locomotion; whether suspensory and climbing behavior were also important has remained unclear. Morphological features of the forelimb have been linked to locomotor differences among primates, but the interpretation of human fossils has remained problematic.</p><p>This dissertation examined the total morphological pattern of the forelimb, specifically the functional integration of the musculature and joint systems. This approach employed both geometric morphometrics and a biomechanical modeling approach to studying how and how well the forelimb morphology of living suspensory and quadrupedal primates, as well as humans and fossil hominins, accommodate climbing and suspensory locomotion. Data collected with a microscribe 3-D digitizer on the scapula, humerus, radius, and ulna of Australopithecus sediba, Australopithecus afarensis, and Homo erectus were compared to a sample of Homo sapiens, Pan troglodytes, Pan paniscus, Gorilla gorilla, Pongo pygmaeus, Hylobates lar, and Macaca fuscicularis.</p><p>The hominin upper limb is a rich mosaic of primitive and derived traits. The blade of Australopithecus sediba, although appearing most similar to extant orangutans, is in fact functionally most similar to chimpanzees. The overall morphology of the australopith elbow joint appears most similar to Pan, as does the elbow joint of Homo erectus, suggesting that the modern human configuration happened more recently than 1.5 million years ago. </p><p>Au. afarensis and Au. sediba share important similarities, but are clearly distinct species. While their overall elbow joint shape is strikingly similar, the articular surface is not identical. Au. afarensis is more similar in this respect to Pan and Homo, while Au. sediba is more similar to extant taxa that spend substantially more time engaging in vertical climbing and suspensory behavior.</p><p>The results from this study support previous interpretations that not all australopiths across time were employing the same locomotor repertoire. While this study does not present unambiguous conclusions regarding early hominin arboreal locomotion, this study suggests that the morphology of the upper limb is varied, and caution must be taken when interpreting single skeletal elements in the hominin fossil record.</p> / Dissertation

La préhension manuelle est une des habilités de l’homme la plus développée et la plus utilisée dans la vie de tous les jours. Cette capacité nous permet de saisir et de manipuler des objets dans des configurations aussi nombreuses que complexes. Malheureusement, la main est aussi le siège de nombreuses blessures qui, de par l’importance de la préhension, sont fortement handicapantes. Face à ce constat, comprendre les contraintes mécaniques qui sont exercées dans les muscles, les tendons, les articulations et les ligaments lors de gestes de la vie quotidienne apparaît comme un enjeu majeur pour la prévention, la réhabilitation et l’ergonomie. L’objectif de ce travail doctoral était de développer un modèle biomécanique de la préhension permettant une estimation de ces variables non mesurables. A titre d’exemple,le paradigme de la pince pouce-index a été utilisé. Dans une première étude, les modèles biomécaniques de la pince disponibles dans la littérature ont été développés et comparés.Suite à cette évaluation, il a été constaté que ces modèles, en particulier le pouce,nécessitaient des améliorations pour permettre une évaluation physiologiquement réaliste lors de la préhension. Dès lors, plusieurs améliorations ont été proposées. Premièrement, une procédure expérimentale a été développée afin d’évaluer et d’inclure les participations mécaniques passives (ligaments, tissus mous, butées osseuses) de l'articulation trapèzométacarpienne. Deuxièmement, des mesures effectuées par IRM ont été utilisées afin d’intégrer l’action mécanique du muscle First Dorsale Interosseous dans l’équilibre du pouce,ce muscle étant alors négligé malgré son importance dans les tâches de préhension.Troisièmement, une méthode expérimentale permettant d’évaluer plus facilement et plus précisément, in situ, les axes de flexion/extension et d’adduction/abduction de l’articulation trapèzométacarpienne a été proposée et évaluée. Enfin, le modèle biomécanique incluant ces améliorations a été mis en œuvre dans une dernière étude ergonomique visant à étudier l’effet de la taille de l’objet manipulé sur les forces musculaires et articulaires. / Manual precision grip is one of man's most developed and most used ability in everyday lifeactivities. The negative outcome is the high exposure of the hand to repetitive stress injurieswhich are often very disabling. Thus, the understanding of the mechanical stress exerted inmuscles, tendons, joints and ligaments during gripping tasks appears as a major issue forinjury prevention, rehabilitation and ergonomic considerations. This doctoral work aimed atdeveloping a biomechanical model of the grip to estimate the unmeasurable internal loads. Asan example, the classical paradigm of the thumb - index finger grip was used. In a first study,the biomechanical models of the thumb available in the literature were compared and severalimprovements proposed in order to obtain more physiologically realistic predictions. First, anexperimental method was developed to evaluate and include passive structures moment intothe equilibrium of the trapeziometacarpal joint (TMC). Secondly, MRI was used to integratethe mechanical action of the First Dorsal Interosseous muscle at the TMC, since this musclehas commonly been neglected in thumb models but seems essential during pinch grip.Thirdly, the kinematic model which has to be used with the anthropometric data of tendonmoment arms was evaluated and compared to our proposition of a functional method toassess, in situ, the axes of rotation of the TMC. Finally, the biomechanical model includingthese improvements was implemented in an ergonomic study. We investigated the effect ofobject width on grip forces and muscles/joints loads. This doctoral work finds its consistencyin its desire to develop and apply the biomechanical modelling of the hand in the fields ofclinical and ergonomics.

Le prolapsus génital est une pathologie fonctionnelle féminine fréquente dont le retentissement sur la qualité de vie des femmes peut être important et constitue aujourd'hui un véritable enjeu de santé publique. / Genital prolapse is a frequent female functional pathology that can have strong impact on quality of life; it is today a real public health issue. Surgical treatment of the various stages of cystocele is a current challenge. We developed an innovative 3D numerical model using the Finite Elements method, to enable simulation of the various surgical techniques. The model also allowed validation of our surgical hypotheses and provided some answers to outstanding questions in cystocele surgery. The first of my PhD studies allowed me to make a complete review of the anatomical pelvic organ support structures involved in prolapse, and to distinguish certain anatomic theories relating clinical expression to specific anatomic lesions. The various theories are actually quite close and complementary, but differ in terms of the mechanism implicated. The second study involved designing a 3D numerical biomechanical model of the pelvic floor, based on Finite Elements analysis coupled to dynamic MRI. The model allowed me to assess the various theories of pelvic organ suspension, and to design simulations of cystocele mobility. The model provided better understanding of the anatomic structures involved in prolapse. The third study involved designing a 3D numerical pathologic model based on data for patients with grade ≥ 3 cystocele. The model enabled analysis and assessment of the impact of the various surgical correction techniques and fixation zones on organ mobility. Although the results have not been validated clinically, the study contributed to the scientific literature on the importance of mesh reinforcement in the management of cystocele. Comparison between the various techniques (sacrocolpopexy, vaginal mesh suspension, sacrospinous fixation) using the POP-Q points found that point Ba was better corrected by sacrocolpopexy than sacrospinous fixation or vaginal mesh suspension. For sacrospinous fixation, the further it is performed from the sciatic spine, the better the apical correction of point C but the poorer the correction of point Ba. These findings could be used to improve surgical correction techniques and standardize practice. Thus, our 3D numerical cystocele model could contribute to selecting the surgical technique for correction of the cervix and anterior vaginal wall. The Finite Elements model of the pelvic system provides better understanding of the mechanisms underlying surgical correction of cystocele and the vaginal apex. It could also enable the results of prolapse surgery to be predicted, adapting technique to the individual patient by preoperative simulation. Simulation provides original and interesting information on mobility in prolapse. The present simulation results obviously need future assessment in comparison with clinical practice. In conclusion, simulation and the implementation of a 3D numerical model of pelvic mobility now allows better understanding of the mechanisms underlying pelvic statics disorder, with simulation of pathological pelvic mobility and of prolapse surgery procedures.

Modeling the liver deformation forms the basis for the development of new clinical applications that improve the diagnosis, planning and guidance in liver surgery. However, the patient-specific modeling of this organ and its validation are still a challenge in Biomechanics. The reason is the difficulty to measure the mechanical response of the in vivo liver tissue. The current approach consist of performing minimally invasive or open surgery aimed at estimating the elastic constant of the proposed biomechanical models. This dissertation presents how the use of medical image analysis and evolutionary computation allows the characterization of the biomechanical behavior of the liver, avoiding the use of these minimally invasive techniques. In particular, the use of similarity coefficients commonly used in medical image analysis has permitted, on one hand, to estimate the patient-specific biomechanical model of the liver avoiding the invasive measurement of its mechanical response. On the other hand, these coefficients have also permitted to validate the proposed biomechanical models. Jaccard coefficient and Hausdorff distance have been used to validate the models proposed to simulate the behavior of ex vivo lamb livers, calculating the error between the volume of the experimentally deformed samples of the livers and the volume from biomechanical simulations of these deformations. These coefficients has provided information, such as the shape of the samples and the error distribution along their volume. For this reason, both coefficients have also been used to formulate a novel function, the Geometric Similarity Function (GSF). This function has permitted to establish a methodology to estimate the elastic constants of the models proposed for the human liver using evolutionary computation. Several optimization strategies, using GSF as cost function, have been developed aimed at estimating the patient-specific elastic constants of the biomechanical models proposed for the human liver. Finally, this methodology has been used to define and validate a biomechanical model proposed for an in vitro human liver. / Martínez Martínez, F. (2014). Determining the Biomechanical Behavior of the Liver Using Medical Image Analysis and Evolutionary Computation [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39337 / TESIS

Les signaux électromyographiques de surface (sEMG) correspondent aux signaux électriques composés par les potentiels d’action produits par les unités motrices d’un muscle actif et enregistrés par des électrodes de surface. Les signaux sEMG sont largement utilisés dans la médicine, le contrôle des prothèses et plus généralement dans les études biomécaniques portant sur l’analyse du mouvement humain. Les signaux sEMG sont très souvent utilisés comme un indicateur d’activation musculaire.Bien que présentant un intérêt évident, l’utilisation de ces signaux reste difficile compte tenu qu’ils sont souvent susceptibles d’interférence (diaphonie, ou plus communément « crosstalk ») entre les muscles contigus, parfois même éloignés. Cette contamination croisée est particulièrement présente pour des muscles présents dans un volume restreint, ce qui est le cas des muscles extenseur de l’index et du petit doigt, extensor indicis et extensor digiti minimi. L’interférence induit la réduction de la précision de l’estimation des activations musculaires et reste, à ce titre, un problème important et récurrent de la biomécanique. Afin que les signaux sEMG puissent être utilisés de manière plus robuste en biomécanique, il convient de réduire cette interférence avant de procéder à l’estimation des activations musculaires. Les activations individuelles des muscles participant au mouvement correctement estimées peuvent être utilisées comme données d’entrées d’un modèle biomécanique. Cette démarche, nommée dynamique directe, permet notamment d’estimer la force externe produite par le système et dans un second temps de comparer cette dernière avec la mesure réalisée grâce à un système dynamométrique. En ce sens cette démarche permet une validation indirecte des estimations réalisées à partir des signaux sEMG. Dans le cadre de cette thèse, nous avons modélisé le doigt et plus particulièrement le mécanisme extenseur qui est une structure qui transmet les forces des muscles-extenseurs aux articulations digitales. Cette structure est très mal connue du point de vue biomécanique et le plus souvent représentée par un ensemble des coefficients établis sur l’analyse de mains de cadavres dans des situations très particulières et standardisées (doigts en extension). Ainsi, l’objectif de ce travail de thèse était double : (1) améliorer l’estimation de la force au bout du doigt à partir des mélanges des sEMG sur la base d’extraction des activations des signaux sEMG des muscles extensor indicis et extensor digiti minimi, et (2) modélisation biomécanique du mécanisme extenseur du doigt. Pour cela, les signaux sEMG ont été enregistrés avec une matrice d’électrodes de surface haute densité à 64 capteurs. Ensuite, l’extraction des activations musculaires a été réalisée sur la base d’une procédure de classification des potentiels détectés en utilisant les invariants musculaires que sont la direction de propagation et la profondeur de l’unité motrice à l’origine du signal.Dans un deuxième temps, un modèle biomécanique précis du mécanisme extenseur du doigt a été créé, qui contient les tendons et les principaux ligaments représentés par des bandes et des surfaces élastiques. Un algorithme de paramétrage du modèle a été proposé. Ce type d ‘approche est nécessaire pour mieux décrire les déformations du système anatomique dans des situations de mouvement sain ou pathologique.Cette démarche a montré qu’elle était pertinente pour l’étude biomécanique du doigt. Elle présente des utilisations judicieuses pour les études biomécaniques portant sur l’évaluation clinique, la réhabilitation et le contrôle des prothèses myoélectriques. / The surface electromyographic signals (SEMG) are the electric signals, composed of electric potentials. These potentials are produced by the recruited motor units of an active muscle and captured by the surface electrodes. The SEMG signals are widely used in medicine, prosthesis control and biomechanical studies as an indicator of muscle activity.However, SEMG measurements are usually subjects of crosstalk or interference from nearby muscles. It appears when two or more muscles situated close to each other are active during a SEMG recording. An example of such muscles are the extensors of index and little finger, extensor indicis and extensor digiti minimi, situated close to each other and creating a significant amount of mutual crosstalk when simultaneously active. The crosstalk causes precision decrease of SEMG-based estimation of muscle activations. Hence, the crosstalk-reducing problem must be preliminary solved before muscle activation evaluation.Once the activations of individual muscles are estimated from the mixture, they may be used as an input of a finger biomechanical model to calculate a fingertip force. These models usually contain an extensor mechanism of the finger, which is a structure, transmitting the force from the extensor muscles to the finger joints. This structure is often taken into account as a set of coefficients. However, there is a lack of study about how these coefficients vary with posture, applied force, and subject variability.The purpose of this work is to improve the finger force estimation from the crosstalk-contaminated signals for isometric tasks by extracting the activations of individual muscles and improving the finger biomechanical model.Firstly, the SEMG signals were recorded with high-density surface electromyographic (HD-EMG) electrode matrix. The extraction was based on classifying the detected potentials according their propagation direction and depth of originating motor unit.Secondly, a precise biomechanical model of the finger extensor mechanism was created, containing the principal tendons and ligaments. The algorithm of the model parametrization was proposed as well.The proposed methods of muscle activation estimation along with the created extensor mechanism model may be used for calculating the fingertip force and internal tissues deformations for normal or pathological fingers.

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