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Product designers address the costs of assembly during the design process. Design process can be more efficient if assembly issues could be addressed early in its design process. Doing this requires the ability to assess assemblability among others. Assemblability refers to the ease of assembling the final product from its parts. Assemblability evaluation is applied by product designers for quantitatively estimating the degree of difficulty of the assembly. This helps in identifying areas of improvement, so as to reduce process time and production costs. This work focuses on assessing assemblability in a manual assembly and its importance in the earlier phases of design. Literature contains various methods for assessing assemblability (e.g. Boothroyd-Dewhurst method, the DFA house, Sturges DFA calculator and Sony DFA method). These methods are typically rule-based and their use requires insight and knowledge on the part of the designer. Further, the designer has to interpret and apply them differently in each specific and unique case. Literature also contains methods for ergonomic assessment of manual work and its link with assemblability. Both observation based ergonomic assessment such as RULA, REBA, VIDAR, LUBA and OWAS and instrumentation based ergonomic assessment using electro-goniometer and accelerometer are the techniques reviewed in this thesis for their suitability in assembly assessment. The most recent trend in the area is automation of the evaluation process. This thesis proposes an approach to automated assessment of assemblability using electromagnetic trackers. In spite of advances in industrial automation, manual assembly tasks continue to be an important feature of many industrial operations. The method proposed in the thesis is for the assessment of assemblability of manual assembly that combines both time and postural analysis. The tool used for the static analysis is called Rapid Upper Limb Assessment (RULA); for dynamic analysis a new method of time analysis is proposed that is based on the ratio of time spent in fine and gross motions carried out in an assembly process. The difficulty of assembly of a series of manual assembly tasks are carried out in a laboratory setting. Then by correlating this assessment with the feedback on the difficulty of these assembly task obtained from the subjects who carried out these tasks. The remaining work carried out as a part of this thesis is focussed on automating the process of carrying out the above assessment in an automated manner. Suitability of electromagnetic trackers as a means for automated capture of data necessary for executing the proposed assessment method is studied. Electromagnetic trackers have been used to capture postural data for various limbs of the assembly operators. Data from the limbs are then analysed to identify, to which limb movement signifies which sources of difficulty (i.e. reach, visibility, etc.) in assembly; for example reach difficulty is indicated by torso movement. Finally, the thesis proposes as a part of the future work in possible improvement of the assessment method. Also, its application using a virtual reality (VR) platform assesses in ascertaining ease or difficulties in assembly and many.

This thesis introduces a 3D body tracking system based on neutral networks and 3D geometry, which can robustly estimate body poses and accurate body joints. This system takes RGB-D data as input. Body poses and joints are firstly extracted from color image using deep learning approach. The estimated joints and skeletons are further translated to 3D space by using camera calibration information. This system is running at the rate of 3 4 frames per second. It can be used to any RGB-D sensors, such as Kinect, Intel RealSense [14] or any customized system with color depth calibrated. Comparing to the sate-of-art 3D body tracking system, this system is more robust, and can get much more accurate joints locations, which will benefits projects require precise joints, such as virtual try-on, body measure, real-time avatar driven.

Relying on signs and symptoms of head injury outcomes has shown to be unreliable in capturing the vulnerabilities associated with brain trauma (Karton & Hoshizaki, 2018). To accommodate the subjectivity of self-reported symptoms, data collection using sensor monitoring and video analysis combined with event reconstruction are used to objectively measure trauma exposure (Tator, 2013; Scorza & Cole, 2019; Hoshizaki et al., 2014). Athletes are instrumented with wireless sensors designed to measure head kinematics during play. However, these systems have not been widely adopted as they are expensive, face challenges with angular acceleration measures, and often require video confirmation to remove false positives. Video analysis of head impacts, in conjunction with physical event reconstruction and finite element (FE) modeling, is also used to calculate tissue level strain. This data collection method requires specialized equipment and expertise. Effective management of head trauma in sport requires an objective, accessible, and quantifiable tool that addresses the limitations associated with current measurement systems. The purpose of this research was to determine if a simplified version of video analysis and event reconstruction using impact characteristics (velocity, location, mass, and compliance) obtained from body tracking could yield similar measures of brain strain magnitude to the standard head tracking method. Ice hockey impacts (x36) that varied in terms of competition level, event type and maximum principal strain (MPS) were chosen for analysis. 2D videos of previously completed head reconstructions were reanalyzed and each event was reconstructed again in the laboratory using impact parameters obtained from body tracking. MPS values were calculated using finite element (FE) modeling and compared to the MPS values from events that were reconstructed using impact parameters obtained from head tracking. The relationship between head and body tracking MPS data and level of agreement between MPS categories were also assessed. Overall, a significant difference was observed between MPS magnitudes obtained using impact parameters from body and head tracking data from 2D video. When analyzed by event type, only shoulder and glass events demonstrated significant differences in MPS magnitudes. A strong linear relationship was depicted between the two data collection methods and moderate level of agreement between MPS categories was observed, demonstrating that impact characteristics obtained from body tracking and 2D video can be used to measure brain tissue strain.

This study examines the complex relationship between gender, virtual reality (VR), and social interaction within the context of full-body tracking (FBT) technology in social VR platforms. As VR technology advances and becomes increasingly integrated into users’ lives, understanding the implications of gender expression and perception in these immersive environments is crucial. Utilizing unobtrusive observations and interviews within the VRChat platform, this research explores avatar choices, interactions, and FBT technology utilization as they relate to users’ expressions and perceptions of gender. The findings reveal that cultural background plays a significant role in shaping users’ gender expressions and perceptions in social VR. The study also demonstrates the fluidity of gender expression in virtual environments, highlighting how users can challenge and subvert traditional gender norms, and the potential of virtual reality as a tool for experiential learning, fostering cross-cultural understanding, and promoting inclusive and diverse gender expressions. This study contributes to the emerging body of literature on virtual reality and gender, providing insights that can inform future research and technology development in the field.

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In this dissertation, we address the problem of understanding human activities in videos by developing a two-pronged approach: coarse level modeling of scene activities and fine level modeling of individual activities. At the coarse level, where the resolution of the video is low, we rely on person tracks. At the fine level, richer features are available to identify different parts of the human body, therefore we rely on the body joint tracks. There are three main goals of this dissertation: (1) identify unusual activities at the coarse level, (2) recognize different activities at the fine level, and (3) predict the behavior for synthesizing and tracking activities at the fine level. The first goal is addressed by modeling activities at the coarse level through two novel and complementing approaches. The first approach learns the behavior of individuals by capturing the patterns of motion and size of objects in a compact model. Probability density function (pdf) at each pixel is modeled as a multivariate Gaussian Mixture Model (GMM), which is learnt using unsupervised expectation maximization (EM). In contrast, the second approach learns the interaction of object pairs concurrently present in the scene. This can be useful in detecting more complex activities than those modeled by the first approach. We use a 14-dimensional Kernel Density Estimation (KDE) that captures motion and size of concurrently tracked objects. The proposed models have been successfully used to automatically detect activities like unusual person drop-off and pickup, jaywalking, etc. The second and third goals of modeling human activities at the fine level are addressed by employing concepts from theory of chaos and non-linear dynamical systems. We show that the proposed model is useful for recognition and prediction of the underlying dynamics of human activities. We treat the trajectories of human body joints as the observed time series generated from an underlying dynamical system. The observed data is used to reconstruct a phase (or state) space of appropriate dimension by employing the delay-embedding technique. This transformation is performed without assuming an exact model of the underlying dynamics and provides a characteristic representation that will prove to be vital for recognition and prediction tasks. For recognition, properties of phase space are captured in terms of dynamical and metric invariants, which include the Lyapunov exponent, correlation integral, and correlation dimension. A composite feature vector containing these invariants represents the action and will be used for classification. For prediction, kernel regression is used in the phase space to compute predictions with a specified initial condition. This approach has the advantage of modeling dynamics without making any assumptions about the exact form (polynomial, radial basis, etc.) of the mapping function. We demonstrate the utility of these predictions for human activity synthesis and tracking.

We live in a time when technology is digitalizing the world. Technology is a medium that brings people closer to each other and enables more experiences to take place; at home. The increase of music concert attendance boomed the music industry in 2016 and set record sales already halfway into the year. However, there are still people that cannot attend music concerts or performances due to other factors. It was not only the music industry that boomed in 2016; artists started producing music concerts in Virtual Reality (VR) enabling them to reach out to a wider audience. This study shows how music fans in the age between 20-30 perceive music concerts and performances in virtual worlds. The study conducted qualitative experiments and focus group discussions with a total of nine participants. The conclusion is that music fans perceive virtual reality as a media technology that needs more product development and focus on the possibilities of becoming a more social experience. Virtual reality is a technology that isolates the user; the music fans demanded an experience that enables co-presence. That is, achieving immersion and experiencing being present in a virtual world with another person.

[ES] Los desórdenes del equilibrio y la marcha se encuentran entre los déficits motores más frecuentes entre aquellos individuos que han sufrido un ictus. En la clínica, estas habilidades son comúnmente evaluadas mediante herramientas clínicas que, pese a ser generalmente fáciles y rápidas de administrar, adolecen de poca precisión y estar sesgadas. Los sistemas instrumentados de laboratorio existentes para valorar la postura y la marcha resuelven potencialmente estas limitaciones a costa de requerir una preparación previa por parte de los evaluadores, un amplio espacio reservado en la clínica, un elevado tiempo de realización, y tener un coste muy elevado. El desarrollo tecnológico del sector del entretenimiento ha dado lugar en la última década a periféricos, como plataformas de presión y sensores de profundidad, que permiten la interacción mediante movimientos corporales manteniendo un bajo coste y una gran portabilidad y accesibilidad. Estudios iniciales han mostrado un rendimiento de estos dispositivos muy prometedor, y a veces comparable al de sistemas de laboratorio. Sin embargo, la falta de acceso a los sistemas desarrollados, la escasa investigación en personas con ictus y el desconocimiento de las propiedades psicométricas de las pruebas basadas en estos dispositivos en esta población comprometen la relevancia clínica que podrían tener estos sistemas. La hipótesis principal de este trabajo es que plataformas de fuerzas y sensores de profundidad de bajo coste, como la Nintendo Wii Balance Board y la Microsoft Kinect v2, respectivamente, pueden proporcionar información válida para cuantificar y evaluar la postura y la marcha de sujetos que han sufrido un ictus. Durante la presente tesis doctoral, por tanto, se ha llevado a cabo el desarrollo de herramientas de valoración de la postura y la marcha mediante los dispositivos nombrados, se ha posibilitado su acceso libre, se han determinado los valores normativos de las pruebas incluidas en las herramientas desarrolladas, y, finalmente, se ha investigado su sensibilidad, su validez convergente con herramientas clínicas estandarizadas y su fiabilidad inter e intraevaluador. Los resultados obtenidos de la participación de un total de 544 sujetos sanos y 173 sujetos con ictus en los cinco estudios que comprenden este trabajo evidencian que las herramientas desarrolladas permiten caracterizar satisfactoriamente la postura y la marcha de sujetos con ictus con respecto a la de sujetos sanos, poseen una validez convergente con instrumentos variables y coherente, y tienen una fiabilidad inter e intraevaluador excelente para casi todas las pruebas incluidas. Estos hallazgos sugieren que, pese a las limitaciones existentes, las herramientas desarrolladas podrían ser potencialmente usadas como una alternativa de bajo coste a los sistemas de laboratorio existentes para complementar la valoración de la postura y la marcha de sujetos con ictus. / [CA] Els desordres de l'equilibri i la marxa es troben entre els dèficits motors més freqüents entre aquells individus que han patit un ictus. A la clínica, aquestes habilitats són comunament avaluades mitjançant instruments clínics que, tot i ser generalment fàcils i ràpids d'administrar, poden tindre poca precisió i solen estar esbiaixades. Els sistemes instrumentats de laboratori existents per avaluar la postura i la marxa permeten resoldre aquestes limitacions, però requereixen una preparació prèvia per part dels avaluadors, un ampli espai reservat a la clínica, un elevat temps per realitzar cada prova i tenen un cost molt elevat. El desenvolupament tecnològic del sector de l'entreteniment ha donat lloc a plataformes de pressió i sensors de profunditat de baix cost, gran portabilitat i accessibilitat, que permeten la interacció amb entorns virtuals mitjançant moviments corporals. Estudis preliminars han mostrat un rendiment d'aquests dispositius molt prometedor i, de vegades, comparable al de sistemes de laboratori. No obstant això, la falta d'accés a les aplicacions desenvolupades, l'escassa investigació en persones amb ictus i el desconeixement de les propietats psicomètriques de les proves basades en aquests dispositius en aquesta població comprometen la rellevància clínica dels resultats obtinguts. La hipòtesi principal d'aquest treball és que plataformes de forces i sensors de profunditat de baix cost, com la Nintendo Wii Balance Board i la Microsoft Kinect v2, respectivament, poden proporcionar informació vàlida per quantificar i avaluar la postura i la marxa de subjectes amb ictus. Durant la present tesi doctoral, per tant, s'han desenvolupat eines de valoració de la postura i la marxa mitjançant els dispositius anomenats, s'ha possibilitat el seu accés lliure, s'han determinat els valors normatius de les proves incloses en les eines desenvolupades, i, finalment, s'ha investigat la seva sensibilitat, la seva validesa convergent amb instruments clínics estandarditzats i la seua fiabilitat inter i intraavaluador. Els resultats obtinguts de la participació d'un total de 544 subjectes sans i 173 subjectes amb ictus en els cinc estudis que comprenen aquest treball evidencien que les eines desenvolupades permeten caracteritzar satisfactòriament la postura i la marxa de subjectes amb ictus respecte a la de subjectes sans, tenen una validesa convergent amb instruments variable i coherent, i tenen una fiabilitat inter i intraavaluador excel·lent en gairebé totes les proves incloses. Aquestes troballes suggereixen que, tot i les limitacions existents, les aplicacions desenvolupades podrien ser potencialment usades com una alternativa de baix cost als sistemes de laboratori existents per complementar la valoració de la postura i la marxa de subjectes amb ictus. / [EN] Balance and gait disorders are common after stroke. In the clinical setting, these skills are usually assessed using clinical instruments that, despite being generally quick and easy to administer, may have limited accuracy and be biased. Instrumented laboratory-grade systems aimed at assessing posture and gait can potentially overcome these limitations. However, they require specific training to be operated and a long time to perform the assessments, and are usually bulky and expensive. In the last decade, the technological advances in the gaming industry have given rise to low-cost, portable and off-the-shelf devices, such as pressure platforms and depth sensors, which enable interaction with videogames through body movements. Previous research on the performance of these devices has shown promising results, and suggests that some measures could have comparable accuracy to those estimated by laboratory-grade systems. However, the lack of access to the software used in the experiments, the limited research in stroke patients, and the absence of knowledge about the psychometric properties of the assemment tests based on these devices, could limit the clinical relevance of the preliminary findings. The main hypothesis of this thesis is that low-cost force platforms and depth sensors, such as the Nintendo Wii Balance Board and the Microsoft Kinect v2, can provide sensitive, valid and reliable information to quantify and asses the postural control and gait of individuals with stroke, respectively. This work describes the development of two customized applications to assess posture and gait using the devices mentioned above, their publication on a dedicated website, the exploration of the normative values of tests included in the assessment, and, finally, the investigation of the sensitivity, convergent validity with standardized clinical instruments, and their inter- and intra-rater reliability. A total of 544 healthy subjects and 173 individuals with stroke have participated in the five studies that encompass this thesis. The results of these studies showed good sensitivity to motor impairment, variable and consistent convergent validity with clinical instruments, and excellent inter- and intra-rater reliability for almost all the tests examined. All these findings suggest that, despite their limitations, the developed applications interfaced with low-cost force platforms and depth sensors, could be potentially used as a low-cost alternative to instrumented laboratory-grade systems to complement the clinical assessment of the posture and gait of individuals with stroke. / Latorre Grau, J. (2022). Valoración del equilibrio y la marcha mediante sistemas de bajo coste en sujetos con ictus [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181339