Background: Three dimensional motion analysis systems and goniometer measurement are often analyzed in relation to each other in biomechanical science, although the correlation between the methods are not well researched.  Aim and purpose: To investigate the criterion validity between physical examination of lower extremity using a goniometer with a three dimensional motion analysis system. Method: Six healthy participants (12 lower limbs) were recruited. The variables of interest were passive hip internal and external rotation, knee joint extension, static knee valgus, internal and external tibia rotation, bimalleor angle and ankle dorsal flexion range of motion. Measurements were collected with goniometer and a three dimensional motion analysis system. A modified Helen Hayes marker set was used and the physical examination was made by two physiotherapists using conventional testing positions. Spearman’s rank correlation coefficient and Bland Altman plot were used to describe correlation and level of agreement, respectively. Results: Hip external rotation (rs=0.97), BMA (rs=0.96) and hip internal rotation (rs=0.89) showed acceptable and significant correlation (p<0.01). Tibia internal rotation (0.60, significant p<0.05), ankle dorsiflexion (rs=0.56 p>0.05) tibia external rotation (rs=0.50 p>0.05) knee valgus (rs=-0.16 p>0.05), knee extension (rs=-0.20 p>0.05) did not correlate. Conclusion: The criterion validity were good between the measurements for hip external and internal rotation and BMA. Criterion validity could not be described for the other measurements.

abstract: Motion capture using cost-effective sensing technology is challenging and the huge success of Microsoft Kinect has been attracting researchers to uncover the potential of using this technology into computer vision applications. In this thesis, an upper-body motion analysis in a home-based system for stroke rehabilitation using novel RGB-D camera - Kinect is presented. We address this problem by first conducting a systematic analysis of the usability of Kinect for motion analysis in stroke rehabilitation. Then a hybrid upper body tracking approach is proposed which combines off-the-shelf skeleton tracking with a novel depth-fused mean shift tracking method. We proposed several kinematic features reliably extracted from the proposed inexpensive and portable motion capture system and classifiers that correlate torso movement to clinical measures of unimpaired and impaired. Experiment results show that the proposed sensing and analysis works reliably on measuring torso movement quality and is promising for end-point tracking. The system is currently being deployed for large-scale evaluations. / Dissertation/Thesis / M.S. Electrical Engineering 2012

abstract: Many learning models have been proposed for various tasks in visual computing. Popular examples include hidden Markov models and support vector machines. Recently, sparse-representation-based learning methods have attracted a lot of attention in the computer vision field, largely because of their impressive performance in many applications. In the literature, many of such sparse learning methods focus on designing or application of some learning techniques for certain feature space without much explicit consideration on possible interaction between the underlying semantics of the visual data and the employed learning technique. Rich semantic information in most visual data, if properly incorporated into algorithm design, should help achieving improved performance while delivering intuitive interpretation of the algorithmic outcomes. My study addresses the problem of how to explicitly consider the semantic information of the visual data in the sparse learning algorithms. In this work, we identify four problems which are of great importance and broad interest to the community. Specifically, a novel approach is proposed to incorporate label information to learn a dictionary which is not only reconstructive but also discriminative; considering the formation process of face images, a novel image decomposition approach for an ensemble of correlated images is proposed, where a subspace is built from the decomposition and applied to face recognition; based on the observation that, the foreground (or salient) objects are sparse in input domain and the background is sparse in frequency domain, a novel and efficient spatio-temporal saliency detection algorithm is proposed to identify the salient regions in video; and a novel hidden Markov model learning approach is proposed by utilizing a sparse set of pairwise comparisons among the data, which is easier to obtain and more meaningful, consistent than tradition labels, in many scenarios, e.g., evaluating motion skills in surgical simulations. In those four problems, different types of semantic information are modeled and incorporated in designing sparse learning algorithms for the corresponding visual computing tasks. Several real world applications are selected to demonstrate the effectiveness of the proposed methods, including, face recognition, spatio-temporal saliency detection, abnormality detection, spatio-temporal interest point detection, motion analysis and emotion recognition. In those applications, data of different modalities are involved, ranging from audio signal, image to video. Experiments on large scale real world data with comparisons to state-of-art methods confirm the proposed approaches deliver salient advantages, showing adding those semantic information dramatically improve the performances of the general sparse learning methods. / Dissertation/Thesis / Ph.D. Computer Science 2014

Ce travail de thèse vise à comprendre les effets des paramètres de conception de l'habitacle automobile tels que la hauteur de toit et la largeur du bavolet sur le mouvement d'entrée et de sortie et sur l'inconfort perçu. La méthode consiste à comparer expérimentalement des mouvements de moindre inconfort avec d'autres plus contraignants en modifiant la géométrie de l'habitacle. Grâce à un conformateur à géométrie variable, 5 configurations de postes de conduite sont définies sur 3 hauteurs d'assise représentant une sportive, une berline et un monospace. Le système optoélectronique Vicon et des capteurs d'efforts sont utilisés pour mesurer le mouvement et toutes les forces de contact, permettant une analyse fine des interactions entre les sujets et le conformateur. 26 sujets ont participé à l'expérimentation, dont la taille varie du 5ème percentile femme au 95ème homme. A l'aide d'un mannequin numérique, la cinématique (angles articulaires) et la dynamique (couples articulaires) du mouvement sont reconstruites. Les résultats montrent que l'exigence en hauteur de toit dépend peu de la stature et de la hauteur de siège. L'analyse biomécanique du mouvement révèle que les grandes statures présentent une plus forte flexion du tronc que les petites statures. Ceci peut s'expliquer par le fait que l'espace autour du siège est plus réduit pour les petites statures en raison de la position plus avancée du siège dans l'habitacle. Un abaissement de seulement 45mm du toit fait qu'un véhicule devient inacceptable pour le conducteur. Le volant joue un rôle essentiel pour l'accessibilité, pour produire le couple d'extension nécessaire au genou gauche pour s'extraire du véhicule / This PhD thesis aims at understanding the effects of the roof height and the sill width on the car ingress/egress motion and the perceived discomfort. The method consists in comparing experimentally the less constrained motion with more constrained ones by controlling design parameters. Thanks to an adjustable car mock-up, 3 configurations of roof height and sill width were tested by volunteers on three seat heights representing a small car, a medium-size car and a minivan. A Vicon motion capture system and 6-axes force sensors were used in order to measure the motion and all external contact forces and to allow an accurate analysis of the interactions between the driver and the car. 26 volunteers participated in the experiment, selected according to their stature in order to cover a large range of the French driver (from 5th percentile female to 95th percentile male). Using a Digital Human Model, the kinematics (joint angles) and the dynamics (joint torques) of the motion were reconstructed. The results show that the demand for the roof height is not influenced by the car configuration nor the volunteer‟s stature. A biomechanical analysis highlights that the short volunteers adopt a more upright trunk than the tall ones due to smaller space available between the seat and the steering wheel for short persons. In addition, a small change of 45 mm in roof height may lead to an unacceptable car configuration. Finally, the steering wheel is an essential car element helping drivers to produce the necessary extension torque at the left knee for getting up

This dissertation focuses on the investigation and development of an effective prosthetic training and rehabilitation platform with the use of virtual reality to facilitate an effective process to return amputees to the highest level of independence and functioning possible. It has been reported that approximately 10 million people live with a limb loss worldwide, with around 30% being an upper-extremity amputee. The sudden loss of a hand or arm causes the loss of fine, coordinated movements, reduced joint range of motion (ROM), proprioceptive feedback and aesthetic appearance, all which can be improved with the use of a prosthesis and proper training. Current literature has shown prosthetic devices to provide limited function to users in a variety of areas including hand operation, functionality and usability, all which could be improved with proper rehabilitation and training. It has been exhibited that a large percentage of amputees abandon or reject prosthesis use mostly due to limited function and lack of training or knowledge of the device. It has been reported that untrained amputees will adjust their body in an awkward or compensatory body motion rather than repositioning a joint position while performing a task with a prosthetic device. This causes misuse and improper function that has been shown to lead to significant injuries. An effective prosthetic training and rehabilitation regime would be advantageous in returning the patient to the highest level of independence and functioning possible, with proper use of their prosthetic device. A successful training and rehabilitation program would allow an amputee to improve their ability to perform with optimal motion and use all prosthetic control capabilities. This dissertation describes the development of a stick figure model of the user’s motion in real-time and a character avatar animating the individualized optimal goal motions. The real-time model directly corresponds to the user’s motion, with the option to have the character avatar simultaneously animating an optimal goal motion for the user to follow. These were implemented into the Computer Assisted Rehabilitation Environment (CAREN) system (Motek Medical, Amsterdam, Netherlands) to provide real-time visual feedback to the users while performing specified training and rehabilitating tasks. A ten camera Vicon (Oxford, UK) optical motion captured system was used with the CAREN system capabilities to track body and upper extremity prosthetic segments during range of motion (ROM), activities of daily living (ADL), and return to duty (RTD) tasks, with and without the use of the virtual reality visual feedback. Data was collected on five able-bodied subjects and five subjects with a unilateral transradial amputation using their personal prosthetic device. Through investigation and development, a preferred and effective way to display the visualization of the real-time and optimal models were revealed. Testing the subjects with and without the virtual reality visualization, exhibited the effectiveness of providing visual feedback. Results showed subject’s to have improved positing, movement symmetry, joint range of motion, motivation, and overall an improved performance of the series of tasks tested. With the integration of the optimal model visualization, real-time visual feedback, and additional CAREN system capabilities, upper-extremity training and rehabilitation techniques were shown to enhance with the use of virtual reality, through improved task performance, and functional advances. The results of this dissertation introduce an alternative means for clinicians to consider for effectively rehabilitating and training upper-limb amputees. Findings of this dissertation sought to provide useful guidelines and recommendation to aid in the development of a small-scale adaptable option for rehabilitation practitioners and at home use. The techniques investigated in this study could also be applicable for lower-limb amputee, post-stroke, traumatic brain injury, poly-trauma, and other patients with physically limiting disabilities. The techniques investigated in this study are expected to aid in the development of training and rehabilitation procedures for a variety of patient populations, to enhance the effectiveness and assist in improving the overall quality of life of others.

Title: Loading analysis of soccer players during different form of small-side games Objectives: The main goal of thesis was analyze physiological changes of the body in various forms of small football games by selected players of the pupil category U14. To analyze was used a total of four skill games, always with the same number of players, but with a different size of the board. Next goal of research was to find which size of the pitch is the most effective for the players of this category in terms of response to physiological functions. Methods: The test group was consisted of 16 Football players aged 13-14 years old. Testing took place in two training units, in each of training units players having completed two forms of playable games with four repeating. In work is used indirect (mediated) observation because the data was recorded by using the devices. The data from the devices was subsequently processed into the result form. During the testing was used this device GPSports and sporttester "Polar RS800". Results: The results of the work inform about the physiological responses of the organism in individual forms of preparatory games and also compare one another. Based on results was found, that different size of playing table will cause both internal and external changes in the response of...

No description available.

京都大学 / 0048 / 新制・課程博士 / 博士(人間・環境学) / 甲第21861号 / 人博第890号 / 新制||人||213(附属図書館) / 2018||人博||890(吉田南総合図書館) / 京都大学大学院人間・環境学研究科共生人間学専攻 / (主査)教授 神﨑 素樹, 教授 石原 昭彦, 教授 久代 恵介 / 学位規則第4条第1項該当 / Doctor of Human and Environmental Studies / Kyoto University / DGAM

Motion segmentation is part of the computer vision field and aims to find the moving parts in a video sequence. It is used in applications such as autonomous driving, surveillance, robotics, human motion analysis, and video indexing. Since there are so many applications, motion segmentation is ill-defined and the research field is vast. Despite the advances in the research over the years, the existing methods are still far behind human capabilities. Problems such as changes in illumination, camera motion, noise, mixtures of motion, missing data, and occlusion remain challenges. Feature-based approaches have grown in popularity over the years, especially manifold clustering methods due to their strong mathematical foundation. Methods exploiting sparse and low-rank representations are often used since the dimensionality of the data is reduced while useful information regarding the motion segments is extracted. However, these methods are unable to effectively handle large and complete occlusions as well as missing data since they tend to fail when the amount of missing data becomes too large. An algorithm based on Sparse Subspace Clustering (SSC) has been proposed to address the issue of occlusions and missing data so that SSC can handle these cases with high accuracy. A frame-to-frame analysis was adopted as a pre-processing step to identify motion segments between consecutive frames, called inter-frame motion segments. The pre-processing step is called Multiple Split-And-Merge (MSAM), which is based on the classic top-down split-and-merge algorithm. Only points present in both frame pairs are segmented. This means that a point undergoing an occlusion is only assigned to a motion class when it has been visible for two consecutive frames after re-entering the camera view. Once all the inter-frame segments have been extracted, the results are combined in a single matrix and used as the input for the classic SSC algorithm. Therefore, SSC segments inter-frame motion segments rather than point trajectories. The resulting algorithm is referred to as MSAM-SSC. MSAM-SSC outperformed some of the most popular manifold clustering methods on the Hopkins155 and KT3DMoSeg datasets. It was also able to handle complete occlusions and 50% missing data sequences, as well as outliers. The algorithm can handle mixtures of motions and different numbers of motions. However, it was found that MSAM-SSC is more suited for traffic and articulate motion scenes which are often used in applications such as robotics, surveillance, and autonomous driving. For future work, the algorithm can be optimised to reduce the execution time so that it can be used for real-time applications. Additionally, the number of moving objects in the scene can be estimated to obtain a method that does not rely on prior knowledge. / Dissertation (MEng (Computer Engineering))--University of Pretoria, 2021. / CSIR / Electrical, Electronic and Computer Engineering / MEng (Computer Engineering) / Unrestricted

Zařízení k analýze pohybu umožnují zdokonalit chirurgický zákrok, rahebilitaci patologií pohybového systému a jsou také velmi přínosné pro výzkum v oboru biomechaniky. V dešní době existuje mnoho zařízení k analýze pohybu, jejihž cena může dosáhnout až 150 k€ (Vicon, Motion Analysis). Cílem této diplomové práce je vyvinutí levného prototypu zařízení k analýze pohybu založeného na sledování barevných terčíků pomocí dvou jedoduchých digitálních kamer a programu ke zpracování obrazu.