Although modeling and simulation are fertile areas for research and development within medicine, education, and human factors, there is a growing need for fully integrated organ systems as part of any digital human model (DHM). This need is particularly high in task-based survivability assessment. However, the current static geometry used in DHM is insufficient for evaluating conditions during simulated task performance. This insufficiency is due to the fact that internal viscera are inherently non-rigid objects. Therefore, undesirable, and unrealistic behaviors occur when using static models to represent internal viscera as the DHM moves through a variety of postures. The capacity for DHMs to take on a variety of postures and positions contributes to their overall usefulness in modeling and simulation. By using static models to represent internal viscera, errors in model behavior must be tolerated, or the DHM must be limited to a posture that matches the models’ configurations. With the either option being undesirable there is a need to represent internal viscera using dynamic models. A dynamic model will allow for the geometry used in representing the internal viscera to deform as the DHM. Thus this work proposes a computational platform for controlling the motion and deformation of internal viscera models within a DHM. This platform consists of two components. The first component is a new method for maintaining a relative position within a dynamic character’s mesh called skin-based parenting. The second component is a system which takes a free-from deformation technique used in artistic modeling and eliminates the manual input that is usually required. This platform produces representations of internal viscera which conform to the character’s posture in real-time at an interactive rate. Thus enabling the assessment of how particular environmental influences relate to the position and orientation of internal viscera models within a DHM in a variety of postures.

Human-robot interaction is an important and broad area of study. To achieve success- ful interaction, we have to study human decision making rules. This work investigates human learning rules in games with the presence of intelligent decision makers. Par- ticularly, we analyze human behavior in a congestion game. The game models traffic in a simple scenario where multiple vehicles share two roads. Ten vehicles are con- trolled by the human player, where they decide on how to distribute their vehicles on the two roads. There are hundred simulated players each controlling one vehicle. The game is repeated for many rounds, allowing the players to adapt and formulate a strategy, and after each round, the cost of the roads and visual assistance is shown to the human player. The goal of all players is to minimize the total congestion experienced by the vehicles they control. In order to demonstrate our results, we first built a human player simulator using Fictitious play and Regret Matching algorithms. Then, we showed the passivity property of these algorithms after adjusting the passivity condition to suit discrete time formulation. Next, we conducted the experiment online to allow players to participate. A similar analysis was done on the data collected, to study the passivity of the human decision making rule. We observe different performances with different types of virtual players. However, in all cases, the human decision rule satisfied the passivity condition. This result implies that human behavior can be modeled as passive, and systems can be designed to use these results to influence human behavior and reach desirable outcomes.

This study focuses on testing the validity and reliability of dynamic Virtual Interactive Design (VID) methodology with dynamic ergonomics analysis. Virtual Interactive Design methodology has been introduced and applied on practical problems in several previous studies, and initially validated with posture-based static ergonomics analysis tools. Although most results have proved the validity and reliability based on static information considered, such validation processes is not sufficient since risks for performing certain tasks can not be fully examined without examining dynamic aspects. But the dynamic virtual interactive design environment has not been validated sufficiently. In my subsequent study, a dynamic ergonomics analysis tool will be integrated into virtual interactive design environment. For the validation of new dynamic virtual interactive design environment, experimental human motion data from 36 subjects in several tasks are imported into the integrated system and dynamic analysis results are achieved. Also, dynamic ergonomics risk results from motion captured directly from human subjects and static ergonomics risk results from virtual interactive design environment are calculated, which two will be used as standard. Comparisons between interested motion series and standard series with respect to ergonomics risk results are applied for validation purpose. And test-retest method is used for testing reliability.

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Today's challenge for workforce management lies in providing a healthy, safe and productive working culture where people are valued, empowered and respected. Workforce diversity is becoming an essential aspect of the global workforce, and ageing is the most prominent and significant factor in this regard. Diversity brings many opportunities and challenges, as workers with different backgrounds, cultures, working attitudes, behaviours and age work together, and in future, the key to organizational effectiveness and sustainability will heavily depend on developing and sustaining inclusive work environments where people with their differences can co-exist safely and productively. Manufacturing organizations expect the highest levels of productivity and quality, but unfortunately the manufacturing system design process does not take into account human variability issues caused by age, skill, experience, attitude towards work etc. This thesis focuses on proposing an inclusive design methodology to address the design needs of a broader range of the population. However, the promotion and implementation of an inclusive design method is challenging due to the lack of relevant data and lack of relevant tools and methods to help designers. This research aims to support the inclusive design process by providing relevant data and developing new design methodologies. The inclusive design methodology suggested in this thesis is a three step approach for achieving a safe and sustainable work environment for workers, with special concern for older workers. The methodology is based on the provision of relevant human capabilities data, the capture and analysis of difference in human behaviour and the use of this knowledge in a digital human modelling tool. The research is focused on manual assembly through a case study in the furniture manufacturing industry and joint mobility data from a wide-ranging population has been analysed and the task performing strategies and behaviours of workers with different levels of skills have been recorded and analysed. It has been shown that joint mobility significantly decreases with age and disability and that skilful workers are likely to adopt safer and more productive working strategies. A digital human modelling based inclusive design strategy was found to be useful in addressing the design needs of older workers performing manufacturing assembly activities. This strategy validates the concept of using human capabilities data for assessing the level of acceptability of any adopted strategy for older workers, and suggests that the strategies adopted by skilful workers are more likely to be equally acceptable for older and younger workers keeping in view differences in their joint mobility. The overall purpose of this thesis is to present a road map towards the promotion and implementation of the inclusive design method for addressing workforce challenges and in future the same strategies might be implemented within a variety of other industrial applications. The proposed three step inclusive design methodology and getting a reasonable understanding of human variability issues along with the use of human capabilities data (joint mobility in this case) in a human modelling system for design assessment at a pre-design stage can be considered as the major contributions of this research.

This study develops theorems which generalize or improve the existing predictive dynamics method and implements them to simulate several motion tasks of a human model. Specifically, the problem of determination of contact forces (non-adhesive) between the environment and the digital human model is addressed. Determination of accurate contact forces is used in the calculation of joint torques and is important to account for human strength limitations in simulation of various tasks. It is shown that calculation of the contact forces based on the distance of the contact areas from the Zero Moment Point (ZMP) leads to unrealistic values for some of the forces. This is the approach that has been used in the past. In this work, necessary and sufficient constraints for modeling the non-adhesiveness of a contact area are presented through the definition of NCM (Normal Contact Moment) concepts. NCM point, constraints and stability margins are the new theoretical concepts introduced. When there is only one contact area between the body and the environment, the ZMP and the NCM point coincide. In this case, the contact forces and moments are deterministic. When there are more than one contact areas, the contact forces and moments are indeterminate. In this case, an optimization problem is defined based on the NCM constraints where contact forces and moments are treated as the unknown design variables. Here, kinematics of the motion is assumed to be known. It is shown that this approach leads to more realistic values for the contact forces and moments for a human motion task as opposed to the ZMP based approach. The proposed approach appears to be quite promising and needs to be fully integrated into the predictive dynamics approach of human motion simulation. Some other insights are obtained for the predictive dynamics approach of human motion simulation. For example, it is mathematically proved and also validated that there is a need for an individual constraint to ensure that the normal component of the resultant global forces remains compressive for non-adhesive contacts between the body and the environment. Also, the ZMP constraints and stability margins are applicable for the problems where all the contacts between the environment and the body are in one plane; however, the NCM constraints and stability margins are applicable for all types of arbitrary contacts between the body and the environment. The ZMP and NCM methods are used to model the motion of a human (soldier) performing several military tasks: Aiming, Kneeling, Going Prone and Aiming in Prone Position. New collision avoidance theorems are also presented and used in these simulations.

In order to leverage advances made in body-armor materials, as well as to further the design landscape, considering body armor as a complete human-centric system is becoming more prevalent. This trend necessitates a greater focus on human systems integration (HSI) and human-centric design. Digital human models (DHMs) provide a powerful tool for HSI, but modeling-and-simulation tools, let alone DHMs, have rarely been used with body armor. With respect to analysis, this is changing. New methods for evaluating body armor from a biomechanical perspective have been developed within the SantosTM DHM. It is now possible to import digital models of body-armor systems, place them on an avatar, simulate various tasks (i.e., running, aiming, etc.), and then virtually evaluate the armor's effect on performance, balance, mobility, bulk, etc. However, with respect to design, there are no available simulation tools to help users balance the goals of maximizing mobility and survivability concurrently. In response to these growing needs, there are two new areas of work being proposed and discussed. First, this work leverages a series of new virtual evaluation capabilities for Personal Protective Equipment (PPE) and implements a filter that automatically evaluates and selects from a library of designs the most advantageous PPE system based on user-selected objectives and constraints. Initial tests have shown realistic results with minimal computational demand. Secondly, this thesis proposes a new method for armor-system topology optimization that optimizes not only biomechanical metrics but also external (to the DHM system) metrics from potentially complex injury and protection models. The design variables for this optimization problem represent the position on the body of small body-armor elements. In addition, the existence of each element is modeled as a variable, such that unnecessary elements are determined and removed automatically. This inclusion of location in combination with the traditional existence variable is a novel inclusion to the topology optimization method. Constraints require that no two elements overlap. The objective functions that govern where the armor elements are moved must be general enough to function with any external data, such as survivability. Thus, a novel process has been developed for importing external data points (i.e., stress at points in the body resulting from a blast simulation) and using regression analysis to represent these points analytically. Then, by using sequential quadratic programming for gradient-based optimization, the armor elements are automatically positioned in order to optimize the objective function (i.e., minimize potential injury). This new approach allows any metric to be used in order to determine general body-armor concepts upstream in the design process. This system has the potential to become especially useful when trying to optimize multiple objectives simultaneously, the results of which are not necessarily intuitive. Thus, given a specified amount of material, one can determine where to place it in order to, for example, maximize mobility, maximize survivability, and maximize balance during a series of specified mission-critical tasks. The intent is not necessarily to provide a final design with one "click"; accurately considering all aspects of hard and soft armor is beyond the scope of this work. However, these methods work towards providing a design aid to help steer system concepts. Test cases have been successfully run to maximize coverage of specific external data for internal organs (and thus survivability) and mobility, while minimizing weight. The weight metric has also been successfully used as a constraint in the optimal armor design. In summary, this work provides 1) initial steps towards an automated design tool for body armor, 2) a means for integrating different analysis models, and 3) a unique example of human-in-the-loop analysis and optimization.

Robots are increasingly capable of co-existing with human beings in the places where we live and work. I believe, however, for robots to collaborate and assist human beings in their daily lives, new methods are required for enhancing humanrobot communication. In this dissertation, I focus on how a robot can acquire and refine expressive and receptive communication skills with human beings. I hypothesize that communication has its roots in motor behavior and present an approach that is unique in the following aspects: (1) representations of humans and the skills for interacting with them are learned in the same way as the robot learns to interact with other “objects,” (2) expressive behavior naturally emerges as the result of the robot discovering new utility in existing manual behavior in a social context, and (3) symmetry in communicative behavior can be exploited to bootstrap the learning of receptive behavior. Experiments have been designed to evaluate the approach: (1) as a computational framework for learning increasingly comprehensive models and behavior for communicating with human beings and, (2) from a human-robot interaction perspective that can adapt to a variety of human behavior. Results from these studies illustrate that the robot successfully acquired a variety of expressive pointing gestures using multiple limbs and eye gaze, and the perceptual skills with which to recognize and respond to similar gestures from humans. Due to variations in human reactions over the training subjects, the robot developed a preference for certain gestures over others. These results support the experimental hypotheses and offer insights for extensions of the computation framework and experimental designs for future studies.

3D human models play an important role in computer graphics applications from a wide range of domains, including education, entertainment, medical care simulation and military training. In many situations, we want the 3D model to have a visual appearance that matches that of a specific living person and to be able to be controlled by that person in a natural manner. Among other uses, this approach supports the notion of human surrogacy, where the virtual counterpart provides a remote presence for the human who controls the virtual character's behavior. In this dissertation, a human modeling pipeline is proposed for the problem of creating a 3D digital model of a real person. Our solution involves reshaping a 3D human template with a 2D contour of the participant and then mapping the captured texture of that person to the generated mesh. Our method produces an initial contour of a participant by extracting the user image from a natural background. One particularly novel contribution in our approach is the manner in which we improve the initial vertex estimate. We do so through a variant of the ShortStraw corner-finding algorithm commonly used in sketch-based systems. Here, we develop improvements to ShortStraw, presenting an algorithm called IStraw, and then introduce adaptations of this improved version to create a corner-based contour segmentatiuon algorithm. This algorithm provides significant improvements on contour matching over previously developed systems, and does so with low computational complexity. The system presented here advances the state of the art in the following aspects. First, the human modeling process is triggered automatically by matching the participant's pose with an initial pose through a tracking device and software. In our case, the pose capture and skeletal model are provided by the Microsoft Kinect and its associated SDK. Second, color image, depth data, and human tracking information from the Kinect and its SDK are used to automatically extract the contour of the participant and then generate a 3D human model with skeleton. Third, using the pose and the skeletal model, we segment the contour into eight parts and then match the contour points on each segment to a corresponding anchor set associated with a 3D human template. Finally, we map the color image of the person to the 3D model as its corresponding texture map. The whole modeling process only take several seconds and the resulting human model looks like the real person. The geometry of the 3D model matches the contour of the real person, and the model has a photorealistic texture. Furthermore, the mesh of the human model is attached to the skeleton provided in the template, so the model can support programmed animations or be controlled by real people. This human control is commonly done through a literal mapping (motion capture) or a gesture-based puppetry system. Our ultimate goal is to create a mixed reality (MR) system, in which the participants can manipulate virtual objects, and in which these virtual objects can affect the participant, e.g., by restricting their mobility. This MR system prototype design motivated the work of this dissertation, since a realistic 3D human model of the participant is an essential part of implementing this vision.

This study was conducted to assess the validity and reliability of the Virtual Build methodology for ergonomics design and analysis. Thirty-six human subjects participated in this study and performed a set of six tasks. The tasks were performed twice in both real and virtual environment. The subject?s motion in performing tasks was analyzed by ergonomics assessments by using Virtual Build methodology. Criteria-related validity was evaluated by comparing the Virtual Build ergonomic assessment results with manual calculation. Test-retest reliability was evaluated by correlating ergonomics assessment results between two trials. The result shows that the Virtual Build methodology is reliable for ergonomic assessments. 48 out of 51 reliability index scores are higher than 0.8. The Virtual Build with virtual environment has lower over-time reliability performance than the real environment. The t-test shows that the Virtual Build is valid for 1991 NIOSH lifting equation assessment when using real environment. Some improvements in enhancing human perception need to be done to make Virtual Build valid when using virtual environment.