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Neste trabalho, modelos de pedestres, utilizados para simular a caracterização da radiopropagação em interiores de edifícios, são reproduzidos, analisados e comparados em diversos ambientes e com diferentes fluxos de pedestres. Estes modelos têm como base o método de traçado de raios (imagens), e se diferenciam em relação ao formato (lâmina, paralelepípedo e cilindro), constantes eletromagnéticas (material absorvente, condutor e dielétrico) e mecanismos de espalhamento de onda eletromagnética (difração, reflexão ou ambos) considerados sobre o pedestre. Para cada um dos modelos, um algoritmo foi criado e detalhado através da apresentação de equações e estrutura dos dados. A análise dos modelos foi realizada em duas etapas de comparação: uma com dados empíricos e outra entre parâmetros de caracterização do canal, como desvanecimentos e dispersão no tempo, obtidos através de simulações com cada tipo de modelo de pedestre. Dentre os vinte e nove modelos ensaiados, os resultados da análise mostraram que o pedestre modelado por um cilindro condutor é aquele que apresenta resultados mais satisfatórios. / In this work, pedestrian models, used to simulate characterization of indoor radio propagation are reproduced, analyzed and compared in different environments with different pedestrian flows. These models are based on the image ray-tracing method, and differs themselves on shape (plate, cylinder and cuboid), electromagnetic constant (absorber, conductive and dielectric materials) and considered spread mechanisms (diffraction, reflection, or both). For each model, an algorithm is created and detailed through the presentation of equations and data structure. The models analysis were made in two comparison steps: one with empirical data and the other with the environment characterization parameters, like fading and time spread, obtained through simulations of each pedestrian model. Within twenty nine models simulation, the results analysis show that the most satisfactory results are given by the model that considers the pedestrian as a conducting cylinder.

Neste trabalho, modelos de pedestres, utilizados para simular a caracterização da radiopropagação em interiores de edifícios, são reproduzidos, analisados e comparados em diversos ambientes e com diferentes fluxos de pedestres. Estes modelos têm como base o método de traçado de raios (imagens), e se diferenciam em relação ao formato (lâmina, paralelepípedo e cilindro), constantes eletromagnéticas (material absorvente, condutor e dielétrico) e mecanismos de espalhamento de onda eletromagnética (difração, reflexão ou ambos) considerados sobre o pedestre. Para cada um dos modelos, um algoritmo foi criado e detalhado através da apresentação de equações e estrutura dos dados. A análise dos modelos foi realizada em duas etapas de comparação: uma com dados empíricos e outra entre parâmetros de caracterização do canal, como desvanecimentos e dispersão no tempo, obtidos através de simulações com cada tipo de modelo de pedestre. Dentre os vinte e nove modelos ensaiados, os resultados da análise mostraram que o pedestre modelado por um cilindro condutor é aquele que apresenta resultados mais satisfatórios. / In this work, pedestrian models, used to simulate characterization of indoor radio propagation are reproduced, analyzed and compared in different environments with different pedestrian flows. These models are based on the image ray-tracing method, and differs themselves on shape (plate, cylinder and cuboid), electromagnetic constant (absorber, conductive and dielectric materials) and considered spread mechanisms (diffraction, reflection, or both). For each model, an algorithm is created and detailed through the presentation of equations and data structure. The models analysis were made in two comparison steps: one with empirical data and the other with the environment characterization parameters, like fading and time spread, obtained through simulations of each pedestrian model. Within twenty nine models simulation, the results analysis show that the most satisfactory results are given by the model that considers the pedestrian as a conducting cylinder.

Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (p. 156-158).

The primary purpose of this thesis was to develop, validate and implement a novel ergonomics tool for manual arm strength (MAS) prediction. In Chapter 2, an empirical study was conducted to: 1) fill in gaps in our MAS database, and 2) examine the relationships between MAS and shoulder/elbow moments, to help identify important sources of variance for future predictive modeling attempts. Chapter 3 focused on the evaluation of artificial neural network (ANN) and traditional multiple regression approaches for MAS prediction, and revealed that ANNs provided a more accurate and generalizable prediction of MAS for our specific dataset. Chapter 4 drew on the data and findings of Chapters 2 & 3, and described the development of the ‘Arm Force Field’ (AFF) method for MAS prediction. The AFF method can be used to predict the MAS for any percentage of the population, given only the simple inputs of force vector direction, hand location (relative to the right shoulder), and torso orientation. In Chapter 5, a theoretical examination of the relative changes in wrist strength, due to interacting forearm and wrist postures, was conducted. That study resulted in a set of regression equations that can be used to predict wrist strength correction factors in complex wrist and forearm postures, allowing for more accurate estimations of the limiting joint once the MAS is calculated. An example of the AFF method’s implementation is provided and discussed in Chapter 6. The four studies, presented in this thesis, add to the current knowledge related to strength prediction in ergonomics, and the AFF method has the potential to be easily integrated within digital human models, for more valid estimates of manual force capabilities for the population. / Dissertation / Doctor of Philosophy (PhD)

Conventional ergonomics analysis involves building physical mockups and conducting simulated operations, such that the constraints experienced by the human subjects can be directly observed. The limitations of this approach are that, they are resource intensive, less flexible for testing design variability and difficult to involve large number of subjects to account for population variability and thus, it is a reactive approach. With the advent of computer aided techniques, efforts are on to support ergonomics analysis processes for proactive design approaches. To achieve this, real scenarios are being simulated in virtual environments which include induction of representative human subjects into such envi-ronments and are termed as Digital Human Models (DHMs). The main challenge in the simulation of humans is to obtain the naturalness that is perceived in human interaction with the environment. This naturalness can be achieved by synergetically modeling the physical performance and cognitive aspects of humans in such a way that one aspect caters the requirements posed from the other. But in current DHMs, the various elements in the physical performance aspect are not in line with the requirements of higher level behav¬ioral/cogntive aspects. Towards meeting this objective, the influence of physical performance aspects of humans on achieving naturalness when DHM interacts with the virtual environment has been studied. In this work, the task of ’reach’ has been chosen for studying the influence of kinematic structure, posture modeling and stability aspects on achieving naturalness for both discrete and statistical humans. Also, a framework has been developed to give instructions based on relations between the segments of the body and objects in the environment. Kinematic structure is modeled to simulate the humans with varied dimensions taking care of the change of link fixations necessary for various tasks. The conventional techniques used to define kinematic structures have limitations in resolving the issues that arise due to change in link fixations. In this work a new scheme is developed to effectively handle precedence relationship sand change of configuration of the existing posture whenever link fixations change. The advantage with this new approach is that complex maneuvers which involve different link fixations and multiple fixations at a time can be managed automati¬cally without the user’s intervention. Posture prediction involves estimation of the whole body posture which a human operator is likely to assume while performing a task. It involves finding a configuration satisfy¬ing the constraints like placing the body-segments in preferred locations of the task space and satisfying the relations specified between body segments. There are two main chal¬lenges in this regard; one is achieving naturalness in the predicted postures and the other is minimizing the mathematical complexity involved in finding the real time solutions. A human-specific posture prediction framework is developed which can handle a variety of constraints and realize the natural behavior. The approach is completely geometry based and unlike numerical methods, the solutions involve no matrix inversions. Digital human models (DHMs), both as avatars and agents, need to be controlled to make them manipulate the objects in the virtual world. A relations based description scheme is developed to instruct the DHM to perform the tasks. The descriptions as a set of relations and postures involve simple triplets and quadruplets. As the descriptions constitute only the relations between actors, incorporating different behavior models while executing the relations is feasible through this framework. Static balancing is one of the crucial factors influencing the posture of humans. The stim¬ulus for the static balancing is the body’s self weight and is governed by the location of its point of application, namely the center of mass (COM). The main focus is on determin¬ing suitable locations for COM to infer about the mobility of the segments which supports the human structure in slow motion scenarios. Various geometric conditions necessary for support retaining, altering are deduced and developed strategies for posture transitions for effective task performance while maintaining stability. These conditions are useful in de¬termining the posture transition required to shift the COM from one region to the other and thus the behaviors realized while accomplishing the tasks are realistic. These behaviors are simulated through statically stable walking and sit to stand posture transition. One of the advantages of employing DHMs in virtual simulations is the feasibility of creat¬ing human models with varied dimensions. A comparative study is conducted on different methods based on probabilistic and statistic theory as an alternative to the percentile based approach with a view to answer the questions like ’what percentage of people can success-fully accomplish a certain task’ and ’how well can people perform when they reach a point in the operational space’. The case study is done assuming upper and lower arms of hu¬mans as a two link planar manipulator and their link lengths as random variables. Making use of statistical DHMs, the concept of task dependent boundary manikins is introduced to geometrically characterize the extreme individuals in the given population who would ac-complish the task. Simulations with these manikins would help designers to visualize how differently the extreme individuals would perform the task. All these different aspects of DHM discussed are incorporated in our native DHM developed named ’MAYAMANAV’. Finally this thesis will end with conclusions and future work discussing how these different aspects of DHM discussed can be combined with behavioral models to simulate the human error.

Zur ergonomischen Analyse manueller Arbeitsprozesse wird an der Professur Arbeitswissenschaft ein Modell für dynamische Beanspruchungen entwickelt. Dazu wurden diese analytisch zerlegt und parametrisiert. In einem Laborversuchsstand werden elementare dynamische Beanspruchungen einzelner Körperteile systematisch mittels elektromyografischer Messung der beteiligten Muskeln untersucht und anschließend analysiert. Es konnten Zusammenhänge zwischen den Belastungsgrößen Bewegungsgeschwindigkeit, Bewegungswiderstand (Moment) und Bewegungsrichtung und der Beanspruchungsgröße der elektrischen Muskelaktivität gezeigt werden.

Digitale Menschmodelle (DMM) werden aktuell in Unternehmen vorwiegend zur ergonomischen Planung und Überprüfung der Ausführbarkeit und Erträglichkeit von Arbeitsprozessen eingesetzt. Im Rahmen der Nachwuchsforschergruppe „The Smart Virtual Worker“, welche im Interdisziplinären Kompetenzzentrum Virtual Humans der TU Chemnitz angesiedelt ist, entstand ein Framework zur Simulation komplexer Arbeitsabläufe im Kontext der virtuellen Fabrik. Ziel war die Entwicklung eines digitalen Menschmodells für den Einsatz in klein- und mittelständischen Unternehmen. Hierbei standen die autonome Steuerung, eine realistische Animation sowie die Einbeziehung physischer und psychischer Faktoren in die ergonomische Bewertung eines Arbeitsablaufes im Mittelpunkt. Darauf aufbauend wurde eine haptische Nutzerschnittstelle zur interaktiven Fabrik- und Aufgabenplanung entwickelt. Neben der Positionierung von statischen Objekten ist mit diesem Interface auch die Integration und Anpassung von Arbeitsaufgaben möglich.

Les modèles humains numériques sont devenus des outils indispensables à l’étude de la posture est du mouvement dans de nombreux domaines de la biomécanique visant des applications en ergonomie ou pour la clinique. Ces modèles intègrent une représentation géométrique de la surface du corps et un squelette filaire interne composé de segments rigides et d’articulations assurant leur mise en mouvement. La personnalisation des mannequins s'effectue d’abord sur les dimensions anthropométriques externes, servant ensuite de données d’entrée à l’ajustement des longueurs des segments du squelette en interne. Si les données externes sont de plus en plus facilement mesurables à l’aide des outils de scanning 3D actuels, l’enjeu scientifique est de pouvoir prédire des points caractéristiques du squelette en interne à partir de données uniquement externes. L’Institut de Biomécanique Humaine Georges Charpak (Arts et Métiers ParisTech) a développé des méthodes de reconstruction des os et de l’enveloppe externe à partir de radiographies biplanes obtenues avec le système basse dose EOS. En s’appuyant sur cette technologie, ces travaux ont permis de proposer de nouvelles relations statistiques externes-internes pour prédire des points du squelette longitudinal, en particulier l’ensemble des centres articulaires du rachis, à partir d’une base de données de 80 sujets. L'application de ce travail pourrait permettre d’améliorer le réalisme des modèles numériques actuels en vue de mener des analyses biomécaniques, principalement en ergonomie, nécessitant des informations dépendant de la position des articulations comme les mesures d’amplitude de mouvement et de charges articulaires / Digital human models have become instrumental tools in the analysis of posture and motion in many areas of biomechanics, including ergonomics and clinical settings. These models include a geometric representation of the body surface and an internal linkage composed of rigid segments and joints allowing simulation of human movement. The customization of human models first starts with the adjustment of external anthropometric dimensions, which are then used as input data to the adjustment of internal skeletal segments lengths. While the external data points are more readily measurable using current 3D scanning tools, the scientific challenge is to predict the characteristic points of the internal skeleton from external data only. The Institut de Biomécanique Humaine Georges Charpak (Arts et Métiers ParisTech) has developed 3D reconstruction methods of bone and external envelope from biplanar radiographs obtained from the EOS system (EOS Imaging, Paris), a low radiation dose technology. Using this technology, this work allowed proposing new external-internal statistical relationships to predict points of the longitudinal skeleton, particularly the complete set of spine joint centers, from a database of 80 subjects. The implementation of this work could improve the realism of current digital human models used for biomechanical analysis requiring information of joint center location, such as the estimation of range of motion and joint loading

The present work deals with the development of a computational geometric framework for vision modeling for performing visibility and legibility analyses in Digital Human Modeling (DHM) using the field-of-view (FoV), estimated geometrically from 3D tessellated head scans. DHM is an inter-disciplinary area of research with the prime objective of evaluating a product, job or environment for intended users through computer-based simulations. Vision modeling in the existing DHM’s has been primarily addressed through FoV modeling using right circular cones (RCC). Perimetry literature establishes that the human FoV is asymmetric due to unrestricted zygomatic vision and restrictions on the nasal side of the face. This observation is neither captured by the simplistic RCC models in DHM, nor rigorously studied in vision literature. Thus, the RCC models for FoV are inadequate for rigorous simulations and the accurate modeling of FoV is required in DHM. The computational framework developed in this work considers three broad components namely, the geometric estimation and representation of FoV, visibility and statistical visibility, and legibility of objects in a given environment. A computational geometric method for estimating FoV from 3D laser-scanned models of the human head is presented in this work. The strong one-to-one similarity between computed and clinically perimetry maps establishes that the FoV can be geometrically computed using tessellated head models, without necessarily going through the conventional interaction based clinical procedures. The algorithm for FoV computation is extended to model the effect of gaze-direction on the FoV resulting in binocular FoV. A novel unit-cube scheme is presented for robust, efficient and accurate modeling of FoV. This scheme is subsequently used to determine the visibility of 3D tessellated objects for a given FoV. In order to carry out population based visibility studies, the statistical modeling FoV and generation of percentile-based FoV curves are introduced for a given population of FoV curves. The percentile data thus generated was not available in the current ergonomics or perimetry literature. Advanced vision analysis involving character-legibility is demonstrated using the unit-cube with an improved measure to incorporate the effect of character-thickness on its legibility.