This thesis surveys and analyzes applications of machine learning techniques to the fields of animation and computer graphics. Data-driven techniques utilizing machine learning have in recent years been successfully applied to many subfields of animation and computer graphics. These include, but are not limited to, fluid dynamics, kinematics, and character modeling. I argue that such applications offer significant advantages which will be pivotal in advancing the fields of animation and computer graphics. Further, I argue these advantages are especially relevant in real-time implementations when working with finite computational resources.

This study explores the results of an event hosted for undergraduate students in the Arts, Media and Engineering (AME) department at Arizona State University. 18 students were asked to sit and eat lunch with one another and share their opinions on personal and school-related topics. A follow-up survey consisting of eight questions was sent out to gauge how effective this event was in getting students to build stronger relationships with each other. Statistical analysis showed that 89% of students who attended would participate again and consider collaborating with another student at the event in future projects. From these results, a series of future interventions like the one mentioned in this paper could promote stronger relationships among students and add value to the department. A positive response from the students who participated could imply that students might be more inclined to reach out to classmates when in a setting made for that purpose.

Emerging technologies, such as augmented reality (AR), are growing in popularity and accessibility at a fast pace. Developers are building more and more games and applications with this technology but few have stopped to think about what the best practices are for creating a good user experience (UX). Currently, there are no universally accepted human-computer interaction guidelines for augmented reality because it is still relatively new. This paper examines three features - virtual content scale, indirect selection, and virtual buttons - in an attempt to discover their impact on the user experience in augmented reality. A Battleship game was developed using the Unity game engine with Vuforia, an augmented reality platform, and built as an iOS application to test these features. The hypothesis was that both virtual content scale and indirect selection would result in a more enjoyable and engaging user experience whereas the virtual button would be too confusing for users to fully appreciate the feature. Usability testing was conducted to gauge participants' responses to these features. After playing a base version of the game with no additional features and then a second version with one of the three features, participants rated their experiences and provided feedback in a four-part survey. It was observed during testing that people did not inherently move their devices around the augmented space and needed guidance to navigate the game. Most users were fascinated with the visuals of the game and two of the tested features. It was found that movement around the augmented space and feedback from the virtual content were critical aspects in creating a good user experience in augmented reality.

With the increasing popularity of video games and the emergence of game streaming brought about by platforms such as Youtube and Twitch, combined with the multitude of ways to learn how to code from schools and online resources including Codecademy and Treehouse, game development has become incredibly approachable. Yet that does not mean it is simple. Developing a game requires a substantial amount of work, even before a design is considered worth making into a complete game. Over the course of this thesis, I created eight designs with accompanying prototypes. Only one was made into a fully functional release. I sought to make a game with a great design while increasing my understanding of game development and the code needed to finish a game. I came out realizing that I was in over my head. With the amount of work involved in creating an entire game, iteration is key to finding an idea that is capable of becoming a game that feels complete and enjoyable. A game's design must be fleshed out before technical work can truly begin, yet the design can take nearly as much time and effort as the code. In this thesis, each design is detailed and associated with why it seemed great and why it was replaced, with extra focus on the final design and how players felt about it. These designs are followed by what I learned about game development over the course of the thesis, including both the technical and emotional sides of developing a video game.

Stroke is a leading cause of disability with varying effects across stroke survivors necessitating comprehensive approaches to rehabilitation. Interactive neurorehabilitation (INR) systems represent promising technological solutions that can provide an array of sensing, feedback and analysis tools which hold the potential to maximize clinical therapy as well as extend therapy to the home. Currently, there are a variety of approaches to INR design, which coupled with minimal large-scale clinical data, has led to a lack of cohesion in INR design. INR design presents an inherently complex space as these systems have multiple users including stroke survivors, therapists and designers, each with their own user experience needs. This dissertation proposes that comprehensive INR design, which can address this complex user space, requires and benefits from the application of interdisciplinary research that spans motor learning and interactive learning. A methodology for integrated and iterative design approaches to INR task experience, assessment, hardware, software and interactive training protocol design is proposed within the comprehensive example of design and implementation of a mixed reality rehabilitation system for minimally supervised environments. This system was tested with eight stroke survivors who showed promising results in both functional and movement quality improvement. The results of testing the system with stroke survivors as well as observing user experiences will be presented along with suggested improvements to the proposed design methodology. This integrative design methodology is proposed to have benefit for not only comprehensive INR design but also complex interactive system design in general.

As the application of interactive media systems expands to address broader problems in health, education and creative practice, they fall within a higher dimensional space for which it is inherently more complex to design. In response to this need an emerging area of interactive system design, referred to as experiential media systems, applies hybrid knowledge synthesized across multiple disciplines to address challenges relevant to daily experience. Interactive neurorehabilitation (INR) aims to enhance functional movement therapy by integrating detailed motion capture with interactive feedback in a manner that facilitates engagement and sensorimotor learning for those who have suffered neurologic injury. While INR shows great promise to advance the current state of therapies, a cohesive media design methodology for INR is missing due to the present lack of substantial evidence within the field. Using an experiential media based approach to draw knowledge from external disciplines, this dissertation proposes a compositional framework for authoring visual media for INR systems across contexts and applications within upper extremity stroke rehabilitation. The compositional framework is applied across systems for supervised training, unsupervised training, and assisted reflection, which reflect the collective work of the Adaptive Mixed Reality Rehabilitation (AMRR) Team at Arizona State University, of which the author is a member. Formal structures and a methodology for applying them are described in detail for the visual media environments designed by the author. Data collected from studies conducted by the AMRR team to evaluate these systems in both supervised and unsupervised training contexts is also discussed in terms of the extent to which the application of the compositional framework is supported and which aspects require further investigation. The potential broader implications of the proposed compositional framework and methodology are the dissemination of interdisciplinary information to accelerate the informed development of INR applications and to demonstrate the potential benefit of generalizing integrative approaches, merging arts and science based knowledge, for other complex problems related to embodied learning.

The wide adoption and continued advancement of information and communications technologies (ICT) have made it easier than ever for individuals and groups to stay connected over long distances. These advances have greatly contributed in dramatically changing the dynamics of the modern day workplace to the point where it is now commonplace to see large, distributed multidisciplinary teams working together on a daily basis. However, in this environment, motivating, understanding, and valuing the diverse contributions of individual workers in collaborative enterprises becomes challenging. To address these issues, this thesis presents the goals, design, and implementation of Taskville, a distributed workplace game played by teams on large, public displays. Taskville uses a city building metaphor to represent the completion of individual and group tasks within an organization. Promising results from two usability studies and two longitudinal studies at a multidisciplinary school demonstrate that Taskville supports personal reflection and improves team awareness through an engaging workplace activity.

This thesis presents a multi-modal motion tracking system for stroke patient rehabilitation. This system deploys two sensor modules: marker-based motion capture system and inertial measurement unit (IMU). The integrated system provides real-time measurement of the right arm and trunk movement, even in the presence of marker occlusion. The information from the two sensors is fused through quaternion-based recursive filters to promise robust detection of torso compensation (undesired body motion). Since this algorithm allows flexible sensor configurations, it presents a framework for fusing the IMU data and vision data that can adapt to various sensor selection scenarios. The proposed system consequently has the potential to improve both the robustness and flexibility of the sensing process. Through comparison between the complementary filter, the extended Kalman filter (EKF), the unscented Kalman filter (UKF) and the particle filter (PF), the experimental part evaluated the performance of the quaternion-based complementary filter for 10 sensor combination scenarios. Experimental results demonstrate the favorable performance of the proposed system in case of occlusion. Such investigation also provides valuable information for filtering algorithm and strategy selection in specific sensor applications.