Hip impingement is a hip associated abnormality which develops among young and middle-aged individuals. It reduces the activity of those affected and if it is not detected at early stage, it can result in osteoarthritis. In this thesis a reliable framework for studying impingement detection is developed. Current clinical methods in detecting hip impingement involve measuring three angles, first the patient’s leg being flexed until maximum angle, second patient’s leg being flexed until 90° then adducted until maximum angle, and third patient’s leg being flexed until 90° afterwards internally rotated until the maximum angle also known as FADIR (Flexion, adduction in 90° flexion and internal rotation in 90° flexion) test. This is a manual method and relies heavily on surgeons experience and even pain tolerance of the patient and the method is prone to error. The use of computational programmes are known to be more accurate and reliable as the kinematic of contact can easily be studied using the digitised bones of the hip joint assuming that the impingement is determined by bone to bone contact kinematics. Current impingement studies assume that the kinematics of hip joint can be studied by assuming the centre of rotation is fixed for hip joint. For highly conforming joints this assumption is acceptable but for cases where conformity is poor the presence of soft tissue and soft tissue loading becomes very important. The important need in orthopaedics field is to develop a model without too much simplification. In this thesis for the first time the complete computational model of hip with soft tissue has been used to detect the impingement in a specific patient. The effect of centre of rotation and soft tissue are considered on impingement detection. In this study the femur, acetabulum, cartilage and ligaments of specific patients were modelled in MIMICs (Materialise' Interactive Medical Image Control System) using both MRI and CT scan. 3D hip models with and without soft tissues of normal hip, hip with impingement and hip with impingement after reshaping were modelled. The hip models were meshed in 3-Matic. The hip models were imported to Abaqus and boundary conditions were applied. Impingement zone and impingement angle was detected in Abaqus. Different centre of rotation was applied to consider the effect of centre of rotation to detect impingement. Experimental studies were set up to validate the hip models. Mocap, Wiimote, MotionNode and goniometer were used together at the same time to measure the flexion, adduction and internal rotation in 90⁰ of flexion in twenty two healthy volunteers. Validity and reliability of all of the methods were calculated. It is the first time that reliability and validity of Wiimote and MotionNode are considered to be used in medical application. Our results show that the model with soft tissue is closer to the experimental results. It shows that the soft tissue in hip model affects hip impingement angle and hip biomechanics. This finding also shows that, if the boundary condition is closer to the real hip, then the results of computer-aided program will be more reliable.

abstract: This thesis aims to explore the language of different bodies in the field of dance by analyzing the habitual patterns of dancers from different backgrounds and vernaculars. Contextually, the term habitual patterns is defined as the postures or poses that tend to re-appear, often unintentionally, as the dancer performs improvisational dance. The focus lies in exposing the movement vocabulary of a dancer to reveal his/her unique fingerprint. The proposed approach for uncovering these movement patterns is to use a clustering technique; mainly k-means. In addition to a static method of analysis, this paper uses an online method of clustering using a streaming variant of k-means that integrates into the flow of components that can be used in a real-time interactive dance performance. The computational system is trained by the dancer to discover identifying patterns and therefore it enables a feedback loop resulting in a rich exchange between dancer and machine. This can help break a dancer’s tendency to create similar postures, explore larger kinespheric space and invent movement beyond their current capabilities. This paper describes a project that distinguishes itself in that it uses a custom database that is curated for the purpose of highlighting the similarities and differences between various movement forms. It puts particular emphasis on the process of choosing source movement qualitatively, before the technological capture process begins. / Dissertation/Thesis / Masters Thesis Computer Science 2016

Cette thèse porte sur le traitement de données multi-capteurs liées à la locomotion humaine.Son objectif est de concevoir des outils pour la segmentation de la locomotion à partir d'un réseau de capteurs embarqués et appliquée à deux domaines différents: le sport avec l'ultra-marathon et la déficience causée par un symptome de la maladie de Parkinson. Pour ces deux applications, le travail peut atteindre cet objectif concerné. d'une part, les contraintes matérielles liées au réseau de capteurs, et d'autre part, les algorithmes de traitement des données. Dans un premier temps, nous avons recueilli des données multi-capteurs sur un coureur du Marathon des Sables. Le réseau des capteurs étant confronté à des conditions extrêmes, il a fallu s'adapter à des problèmes techniques avant de pouvoir proposer un outil pour segmenter et classer ces grandes quantités de données. Dans un second temps, nous avons travaillé en collaboration avec un médecin, pour comprendre au mieux le ''freezing" (symptôme perturbant la marche de certains malades atteints de la maladie de Parkinson) afin de proposer une nouvelle méthode de détection pour ce symptôme. / This thesis focuses on the treatment of multi-sensor related data locomotion humaine.Son goal is to develop tools for segmentation of locomotion from a network of embedded and applied to two different domains sensors : sport with ultra -marathon and disability caused by a symptom of Parkinson's disease . For both applications, the work can achieve this question. one hand , the physical constraints of the network sensors , and secondly , the data processing algorithms . At first , we collected multi-sensor data on a runner Marathon des Sables. The network of sensors being confronted with extreme conditions, it was necessary to adapt to technical before proposing a tool to segment and classify these large amounts of data problems. In a second step , we worked with a doctor, to understand better the '' freezing " (symptom disrupting the progress of some patients with Parkinson's disease ) to propose a new detection method for this symptom.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / O objetivo do presente trabalho foi avaliar comparativamente parâmetros biomecânicos (tanto antropométricos, quanto cinemáticos) de dados obtidos a partir do console Microsoft Kinect (2010). A avaliação destes parâmetros foi realizada para validar seu uso para obter informações complementares à Análise Ergonomica do Trabalho (AET) e em outras pesquisas, cujos objetivos envolvem o diagnóstico de uso de produtos ou ambientes de trabalho a partir da análises posturais e interações da população que o utiliza. A pesquisa com este console em particular é justificada uma vez que seu lançamento modificou o cenário da biomecânica, já que se trata de um equipamento acessível e portátil. Porém, sua precisão em relação à outros equipamentos ainda está em aberto, sendo inclusive, objeto de estudo de muitas pesquisas em andamento. Os dados obtidos por meio de sistemas de captura de movimentos tridimensionais permitem a avaliação de produtos, atividades e análises de interações homem-objeto. No campo do Design, é uma importante realização, uma vez que permite que profissionais tenham acesso à ferramenta que, anteriormente, era limitada à nichos especializados. O console foi comparado com o sistema de captura de movimentos inercial MVN Biomech (XSENS TECHNOLOGIES) e com o tradicional registro por meio de vídeo. Para obter dados do console Kinect, um software disponível no mercado foi selecionado a partir de critérios predefinidos para obter dados cinemáticos do console. Dois experimentos laboratoriais foram realizados: o primeiro, teve como objetivo obter dados operacionais dos equipamentos e suas limitações de uso; e o segundo foi realizado de forma a obter dados biomecânicos e compará-los a partir de três parâmetros estáticos e um dinâmico. Os parâmetros estáticos envolveram ângulos articulares e segmentares em posturas selecionadas e dimensões segmentares, onde a proposta foi avaliar dados antropométricos e as características do modelo biomecânico referente à manter os corpos rígidos durante a movimentação. O parâmetro dinâmico foi realizado de forma a obter dados de deslocamento global das articulações em movimentações selecionadas. Para possibilitar esta análise, uma plataforma digital foi desenvolvida, constituindo um campo neutro para o tratamento dos dados. A plataforma mantém os dados originais dos sistemas, permitindo a distinção entre os modelos biomecânicos e a retirada de dados que possam ser comparados. Os experimentos realizados permitiram avaliar a usabilidade do console, fornecendo diretrizes para seu uso. Para avaliar a utilização do console em ambientes reais de trabalho, foram realizados registros preliminares em laboratórios químicos, os quais se mostraram viáveis se as limitações, semelhantes às de sistemas baseados em tecnologia ótica, sejam consideradas. Futuras análises devem ser conduzidas para validar estatisticamente os resultados obtidos. Porém, considerando o objetivo do trabalho, pode-se concluir que o sistema avaliado é uma alternativa confiável no contexto proposto. / The aim of the present study was to evaluate biomechanical parameters (both, anthropometric and kinematic) from data acquired through Microsoft Kinect (2010). The validation of its biomechanical characteristics will allow its use in gathering information to complement Ergonomic Work Analysis (EWA) and other user researches that provide product and work environment diagnosis through postural and dynamic assessment. The use of MS Kinect in this research is justified by the fact that is it has changed biomechanical scenario due to the fact that it is an inexpensive and portable alternative to the available motion capture systems available in the market. However, its accuracy has been the subject of many ongoing researches Data acquired from 3D motion capture systems provide means for evaluating products, activities and human-object interactions. In Design, its an important achievement, since it allows professionals to use the tool, considering that most motion capture systems available in the market are not accessible. The Microsoft console was compared to MVN Biomech inertial system (XSENS TECHNOLOGIES) and traditional 2D video data. In order to acquire kinematic data form MS Kinect, a software was chosen, following a few criteria. Two laboratorial experiments were held, where the first aimed to acquire operational details and limitations from the equipments, as for the second aimed to compare biomechanical data through three static parameters and one dynamic. The static parameters involved joint and segment angles, as well as a segments dimensional comparison, whereas the proposals were to assess anthropometric features and to understand if the biomechanical model considers the segments as rigid bodies. The dynamic comparison was based on joints global displacement in selected movements. In order to analyze data from different systems, a digital platform based on a game engine was developed, constituting an even ground for evaluation. The platform maintains original data from the biomechanical models and extracts kinematic parameters, which can be compared. The experiments have provided understanding on the consoles operations, providing guidelines for its usage. In order to also evaluate its usage in real work environments, trial recordings were held in chemical laboratories. These trials have shown the alternative to be viable if the limitations, similar to optical systems, are considered. Future analyses should be conducted in order to statistically validate the results. However, given the goals and context of this research, it can be concluded that the evaluated system is a reliable motion capture alternative.

Rörelseigenkänning (motion capture) med optiska mätsystem används i flera applikationer för översättning av positioner i det fysiska rummet till det virtuella. I det här arbetet approximeras den snittvolym som motsvarar vad två eller fler kameror ser i ett sådant optiskt mätsystem. Volymen approximeras med en octree-datastruktur som lagrar information om kvalitet för individuella delar i volymen. Datastrukturens associerade kvalitetsmått används i kombination med ett vinkelmått i ett senare delsteg för att optimera fram en kamerauppsättning med en genetisk algoritm. Volymapproximeringens konstruktion implementerades i C++ och den genetiska algoritmen använder specialiserad överkorsning och initiering. Genomet är utformat så att problemdomänen begränsas till det aktuella problemet. Resultatet av optimeringen visar att vidareutveckling är nödvändig och lösningarna som optimerats fram var inte tillräckliga. Potentiella framtida arbeten innefattar fortsatt utveckling av nuvarande kvalitetsmått, samt vidare jämförande studier av volymapproximeringen.

Denna studie presenterar en artefakt som med hjälp av Microsoft Kinect, samlar in och beräknar biomekanisk data från golfsvingar för att identifiera nyckelpositioner på ett automatiserat sätt. Den övergripande metoden som används är design-science research. Kinect sensorn är egentligen gjord för tv-spel, men kan även användas allmänt för att fånga och samla in kvantitativ biomekanisk data. Sensorn är inte specifikt utformad för golfsvingar, och saknar dessutom förmågan att spåra externa objekt som golfklubbor. Dessa problem var grunden för denna studies övergripande syfte, nämligen att utveckla en mjukvara med förmågan att identifiera de fem viktigaste nyckelpositionerna i golfsvingen. Nyckelpositionerna definieras utifrån mätbara egenskaper vilket för nyckelpositionen impact, krävde att man utnyttjade sensorns förmåga att spela in ljud. I empirin som genomfördes på en driving range samlades data från sammanlagt 20 svingar in. Varje identifierad nyckelposition analyserades på ett kvalitativt sätt utifrån ett antal sammanställda kriterier. Kinectsensorn hade problem att identifiera vissa positioner, men sammantaget bedömdes 87 % av de insamlade nyckelpositionerna som korrekt identifierade. För nyckelpositionen impact, där insamlad ljuddata användes för identifiering, bedömdes 85 % av de insamlade nyckelpositionerna som korrekt identifierade. Studien begränsar sig till utvalda nyckelpositioner men visar potential för automatiserad insamling av kvalitativ golfsvingdata, och ger uppenbara möjligheter för vidare forskning. / This study presents an artifact that is using Microsoft Kinect for motion capturing of golf swings, in order to identify key positions in an automatic fashion. The main method used is design science research. The Kinect sensor, which is developed for the Xbox video game console, can be used for general motion capture. It is, however, not tailored for golf swings and it also lacks the ability to track external objects such as the golf club. These problems were the main motivation for the purpose of this study, i.e. to develop an application to identify the five most important positions in the golf swing. The key positions were defined based on measurable traits, making it necessary to use the audio recording ability of the sensor for the impact position. The empirical investigation was performed at a driving range, and data from a total of 20 golf swings were gathered. In the next step, every key position was analyzed in a quantitative manner based on a number of criteria. The results show that the Kinect sensor may have some troubles recognizing certain positions, but still 87 % of the key positions captured were considered to be successfully identified. Specifically, 85 % of all impact positions were successfully identified. The study was limited to the chosen key positions, but shows good potential for automatic capturing of quantitative golf swing data, thus suggesting several possible directions for future research.

This thesis was carried out at Imagination Studios in Uppsala. IMS is a motion capture studio that alsodoes animation. Motion capture is the capturing of (generally) human motions to make 3Danimations look more realistic. In motion capture, the actors have to imagine the scene. The goal ofthis thesis is to help the motion capture actor by creating a tool that lets the actor interact with avirtual agent that represents his acting partner. Scenarios and a video sketch were created todescribe how the interaction can work. The Microsoft Kinect is used to capture the motions of theactor and recognize gestures. These gestures are then responded to by a virtual agent that isdisplayed in a 3D environment created in the Unreal Development Kit. Programming was done in C++and UnrealScript to make this solution work. Motions were recorded and applied to the virtual agentto create realistic animations that are played in response to the actor's gestures. The final product isan interactive application that can be used to immerse a person in an acting scenario.

La main est l’organe de préhension chez l’homme qui lui permet de manipuler des objets de tailles et de formes diverses et variées. Elle lui permet également d’effectuer des tâches, parfois d’une grande complexité, avec force ou avec une grande finesse. Il s’agit d’un outil d’une importance cruciale au quotidien, tant sur le plan domestique que sur le plan professionnel, et la perte de fonctionnalité de la main peut rapidement devenir un handicap pour certaines personnes. Bien qu’il existe encore peu d’études sur la capture et l’analyse des mouvements de la main dans la littérature scientifique, de nombreux domaines comme la médecine, l’ergonomie, le sport, la robotique, la réalité virtuelle ou les jeux vidéo s’y intéressent de plus en plus, afin de permettre aux personnes d’exploiter au mieux les fonctionnalités de la main tout en la préservant, ou de créer des interfaces homme-machine afin que celui-ci puisse interagir avec des robots ou en environnement virtuel. L’objectif de cette thèse a été de développer une méthode d’analyse cinématique in vivo et personnalisée afin de contribuer à une meilleure compréhension des mouvements de la main de l’homme. Une première partie du travail consiste à mettre en place un protocole de capture du mouvement de la main sur des sujets masculins et féminins de différentes tranches d’âges, allant de 20 à 50 ans. Les captures de mouvement ont été effectuées à l’aide d’un système optoélectronique et de 56 marqueurs passifs collés sur la peau de la main du sujet. Deux types de mouvements ont été capturés : les mouvements fonctionnels en flexion-extension et en abduction-adduction de la main, et les mouvements de prise d’objets cylindriques et sphériques. Les captures de mouvement sont ensuite labellisées afin d’identifier les différents marqueurs et de pouvoir en extraire les trajectoires. La deuxième partie du travail consiste à développer une méthode d’analyse cinématique des mouvements externes de la main à partir des trajectoires des marqueurs et de la valider à l’aide d’un modèle in silico. En plus d’estimer les paramètres cinématiques avec précision dans le cas où les trajectoires des marqueurs sont parfaites, l’évaluation des méthodes fonctionnelles montre que les mouvements de la main sont assimilables à des mouvements plans, circulaires ou sphériques en fonction de l’articulation étudiée. La construction des repères fonctionnels à partir des paramètres cinématiques pour chaque segment de la main permet ensuite de décrire les mouvements de rotation des articulations à l’aide des angles de Cardan. Les courbes des angles de Cardan obtenues à partir des trajectoires des marqueurs du modèle in silico permettent de valider la méthode de décomposition développée pour l’ensemble des articulations, à l’exception des articulations trapézo-métacarpienne (TMC) et métacarpo-phalangienne (MCP1) du pouce qui sont plus difficiles à analyser. La dernière partie de ce travail de thèse consiste à analyser les mouvements fonctionnels et les mouvements de prise d’objets à partir des captures expérimentales. Les courbes des angles de Cardan obtenues à partir des mouvements fonctionnels correspondent globalement à celles obtenues dans la littérature, sauf dans le cas de l’articulation TMC. De plus, ces courbes montrent que les rotations articulaires ne s’effectuent pas uniquement autour d’un axe, mais autour d’un axe de rotation dominant et d’un ou deux axes de rotation secondaires. Toutefois, les courbes des angles de Cardan des rotations autour des axes secondaires ne correspondent pas toujours à celles présentées dans la littérature. Bien que peu de mouvements de prise d’objets aient pu être analysés, certaines corrélations intéressantes ont pu être trouvées entre les postures de la main et la géométrie des objets manipulés, notamment au niveau des articulations MCP et IPD. / The human hand is a prehensile organ which allows people to handle objects with various sizes and shapes. It is wonderful tool that can be used to perform different simple or complex tasks with strength or great dexterity. It is also a crucial tool in the daily life, both at home and in the workspace, and loss of hand functionality may quickly become disabling for some people. There are few studies in the literature. However, motion capture and kinematic analysis of the hand is becoming more and more of an interest in different areas such as medicine, ergonomics, sport, robotics, virtual reality and video games. Results from these studies have improved knowledge about skills of the hand and how to preserve them. The studies have also improved interactions between people and computers in order to command robots or to progress in virtual reality. The aim of the thesis was to develop methods for an in vivo and subject-specific kinematic analysis in order to contribute to the improvement of knowledge about the human hand motion. A first part of this thesis was to develop a protocol for the motion capture of the hand for male and female subjects aged from 20 to 50 years old. The motion capture was performed using an optoelectronic system with passive markers glued on the skin of the hand. Two sorts of movements were captured. Firstly, functional movements like flexion-extension and abduction-adduction. Secondly, prehensile movements of cylindrical and spherical objects. Then, markers on the motion captures were identified in order to extract their trajectories. The second part of this thesis consisted in the development of a method for the kinematic analysis of external hand movements from the marker trajectories. Validation of this method was achieved using a model of the hand developed in silico. Since no noise was added to the marker trajectories in the silico model; kinematic parameters were estimated with precision. Moreover, assessment of the functional methods showed that the hand motions can be approximated by a plane, a circular arc or a spherical cap depending on the joint studied. After constructing the functional coordinate systems for each segment of the hand using the joint kinematic parameters, it was possible to decompose any joint rotation into three Cardan angles. This decomposition method was validated using the marker trajectories of the hand model, except for the trapeziometacarpal (TMC) and the metacarpophalangeal (MCP1) joints of the thumb which are more difficult to study. The last part of this thesis consisted in the analysis of the functional and the prehensile movements from the motion captures. The curves of the Cardan angles obtained from the functional movements are similar to those presented in the literature for all of the joints, except for the TMC joint. It was also noticed that the joint rotations do not occur around only one axis, but around one dominant axis and one or two secondary axes. However, some differences between the curves of the Cardan angles around the secondary axes obtained in this thesis and those presented in the literature were noticed for some joints. Despite only few prehensile grasps were analyzed, some interesting correlations were also found between the hand shape and the objects grasped, more particularly at the metacarpophalangeal (MCP) and the distal interphalangeal (DIP) joints.

Motion capture technology has been applied in many fields such as animation, medicine, military, etc. since it was first proposed in the 1970s. Based on the principles applied, motion capture technology is generally classified into six categories: 1) Optical; 2) Inertial; 3) Magnetic; 4) Mechanical; 5) Acoustic and 6) Markerless. Different from the other five kinds of motion capture technologies which try to track path of specific points with different equipment, markerless systems recognize human or non-human body's motion with vision-based technology which focuses on analyzing and processing the captured images for motion capture. The user doed not need to wear any equipment and is free to do any action in an extensible measurement area while a markerless motion capture system is working. Though this kind of system is considered as the preferred solution for motion capture, the difficulty for realizing an effective and high accuracy markerless system is much higher than the other technologies mentioned, which makes markerless motion capture development a popular research direction. Microsoft Kinect sensor has attracted lots of attention since the launch of its first version with its depth sensing feature which gives the sensor the ability to do motion capture without any extra devices. Recently, Microsoft released a new version of Kinect sensor with improved hardware and and targeted at the consumer market. However, to the best of our knowlege, the accuracy assessment of the sensor remains to be answered since it was released. In this thesis, we measure the depth accuracy of the newly released Kinect v2 depth sensor from different aspects and propose a trilateration method to improve the depth accuracy with multiple Kinects simultaneously. Based on the trilateration method, a low-cost, no wearable equipment requirement and easy setup human gait tracking system is realized.

The Feldenkrais Method of somatic education has become popular with pianists for improving ease of motion and musculoskeletal health. This thesis contains three studies investigating motion-tracking technologies as means to objectively assess the impact of Feldenkrais training on pianist posture. The first study investigates the accuracy and reliability of Dartfish 2D motion tracking software. Results indicate that Dartfish tracking error is within +/- 0.25 centimeters. The second study uses Dartfish to track head, shoulder, and spine positions of 15 pianists during performance before and after receiving a Feldenkrais Functional Integration Lesson. Comparisons of pre- and post-test measurements indicate no group trends in posture change. However, intriguing changes to movement quality in the head and torso were observable for two participants. The third study compares tracking quality of Dartfish and the Microsoft Kinect for the head, shoulders, and arms of four pianists attending a weeklong Feldenkrais workshop. Results reveal frequent tracking errors with the Kinect sensor, making it unsuitable to measure the impact of somatic training on pianist posture.