Matching Items (21)
Description
Achievement of many long-term goals requires sustained practice over long durations. Examples include goals related to areas of high personal and societal benefit, such as physical fitness, which requires a practice of frequent exercise; self-education, which requires a practice of frequent study; or personal productivity, which requires a practice of performing work. Maintaining these practices can be difficult, because even though obvious benefits come with achieving these goals, an individual's willpower may not always be sufficient to sustain the required effort. This dissertation advocates addressing this problem by designing novel interfaces that provide people with new practices that are fun and enjoyable, thereby reducing the need for users to draw upon willpower when pursuing these long-term goals. To draw volitional usage, these practice-oriented interfaces can integrate key characteristics of existing activities, such as music-making and other hobbies, that are already known to draw voluntary participation over long durations. This dissertation makes several key contributions to provide designers with the necessary tools to create practice-oriented interfaces. First, it consolidates and synthesizes key ideas from fields such as activity theory, self-determination theory, HCI design, and serious leisure. It also provides a new conceptual framework consisting of heuristics for designing systems that draw new users, plus heuristics for making systems that will continue drawing usage from existing users over time. These heuristics serve as a collection of useful ideas to consider when analyzing or designing systems, and this dissertation postulates that if designers build these characteristics into their products, the resulting systems will draw more volitional usage. To demonstrate the framework's usefulness as an analytical tool, it is applied as a set of analytical lenses upon three previously-existing experiential media systems. To demonstrate its usefulness as a design tool, the framework is used as a guide in the development of an experiential media system called pdMusic. This system is installed at public events for user studies, and the study results provide qualitative support for many framework heuristics. Lastly, this dissertation makes recommendations to scholars and designers on potential future ways to examine the topic of volitional usage.
ContributorsWallis, Isaac (Author) / Ingalls, Todd (Thesis advisor) / Coleman, Grisha (Committee member) / Sundaram, Hari (Committee member) / Arizona State University (Publisher)
Created2013
Description
The fashion industry dubs couture as high fashion, yet couture never reaches the finish line when it comes to comfort. Most of the brand name high heels on the market are too painful to wear for long periods of time. For this project, I have developed 3D printed high heels with detachable insoles that will relieve tired feet based on the principle of reflexology. The product integrates traditional flexible insoles with Arduino computing and the result is a functional surface that can ease the pain of the wearer. This paper introduces the product and with it, under-explored opportunities to customize your own high heels at home. Essentially, each consumer will have the ability to personalize and switch out their style without sacrificing comfort. Soon, a consumer will be a designer.
ContributorsNguyen, Nhi N. (Author) / Ingalls, Todd (Thesis director) / Gigantino, Josh (Committee member) / Barrett, The Honors College (Contributor) / Herberger Institute for Design and the Arts (Contributor) / School of Arts, Media and Engineering (Contributor)
Created2015-05
Description
The fundamental concept that I have developed and applied throughout my college career is to try to discover innovative ways to combine the experimental production techniques that I learned in my classes with more traditional songwriting structures. In doing so, I explore the line that distinguishes the two from each other and instill a foreign, yet familiar feeling within the listener. With this approach in mind, I created audio for a variety of media and attempted to push myself in terms of genre and production, ultimately allowing myself to survey a multitude of instruments and audio effects outside of what I learned in my classes. In my portfolio, I have an organized layout of my audio work within the categories of film soundtracks, game audio, and original music, along with how to contact me and information about the licensing of my music. In learning how to create a professional online portfolio, I learned more about the business side of music and where I stand regarding how people listen to my music or use it within their own projects. The process of creating my portfolio taught me a lot about the relationships that I want to pursue with artists that I work with in the future. My portfolio can be found at: markusrennemann.weebly.com
ContributorsRennemann, Markus Horst Florian (Author) / Ingalls, Todd (Thesis director) / Paine, Garth (Committee member) / Barrett, The Honors College (Contributor) / School of Arts, Media and Engineering (Contributor)
Created2015-05
Description
This creative project thesis involves electronic music composition and production, and it uses some elements of algorithmic music composition (through recurrent neural networks). Algorithmic composition techniques are used here as a tool in composing the pieces, but are not the main focus. Thematically, this project explores the analogy between artificial neural networks and neural activity in the brain. This project consists of three short pieces, each exploring these concept in different ways.
ContributorsKarpur, Ajay (Author) / Suzuki, Kotoka (Thesis director) / Ingalls, Todd (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This creative project is a visual and sonic exploration of emotion in a video game format. The game is a 2D side-scroller created using PyGame and Python that focuses on a character who uses "emotions" to navigate their increasingly unrecognizable world. This project was taken on to explore the ways in which technologically-created media can relate to the human experience of emotion, and the ways in which emotions are like software to the human body's hardware. Additionally, this project conceptually comments on and rejects the idea that human situations always require a specific "appropriate" human emotion in response. Credit for the music in this game goes to Markus Rennemann.
ContributorsBennett, Ashley Laura (Author) / Ingalls, Todd (Thesis director) / Kautz, Luke (Committee member) / Barrett, The Honors College (Contributor) / School of Arts, Media and Engineering (Contributor) / School of International Letters and Cultures (Contributor)
Created2014-12
Description
This project consists of 2 electronic/instrumental musical albums, each with 4 songs, aimed at becoming a source of solo therapy for those affected by mental illnesses. The calm album contains calm and relaxing music to combat anxiety and the HAPPY album contains happy and uplifting music to combat depression. While the musical elements stabilize the listener’s mental state, their own internal dialogue and meditation work to heal the listener’s mental illness.
ContributorsHendrix, Austin J. (Author) / Ingalls, Todd (Thesis director) / Rigsby, Clarke (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Modern audio datasets and machine learning software tools have given researchers a deep understanding into Music Information Retrieval (MIR) applications. In this paper, we investigate the accuracy and viability of using a machine learning based approach to perform music genre recognition using the Free Music Archive (FMA) dataset. We compare the classification accuracy of popular machine learning models, implement various tuning techniques including principal components analysis (PCA), as well as provide an analysis of the effect of feature space noise on classification accuracy.
ContributorsKhondoker, Farib (Co-author) / Wildenstein, Diego (Co-author) / Spanias, Andreas (Thesis director) / Ingalls, Todd (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
We propose the Bio-HCI framework, that focuses on three major components: biological materials, intermediate platforms, and interaction with the user. In this context, "biological materials" is meant to broadly cover biological matter (DNA, RNA, enzyme), biological information (gene, epigenetic), biological process (mutation, reproduction, self assembling), and biological form. These biological materials serve as the design elements for designers to use in the same way as digital materials. Intermediate Platform focuses on methods of connecting biological materials to a user, or a digital platform that connect to users. In most current use-cases, biological materials need an intermediate platform to transfer the information to the user and transfer the user's response back to biological materials. Examples include a DNA sequencer, microscope, or petri dish. User interaction emphasizes the interactivity between a user and the biological machine (biological materials + intermediate platform). The interaction ranges from a basic human-computer interaction such as using a biological machine as a file storage to a unique interaction such as having a biological machine that evolves to solve user's task. To examine this framework further, we present four experiments which focus on the different aspect of the Bio-HCI framework.
ContributorsPataranutaporn, Pat (Author) / Finn, Edward (Thesis director) / Kusumi, Kenro (Committee member) / Ingalls, Todd (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Nearly one percent of the population over 65 years of age is living with Parkinson’s disease (PD) and this population worldwide is projected to be approximately nine million by 2030. PD is a progressive neurological disease characterized by both motor and cognitive impairments. One of the most serious challenges for an individual as the disease progresses is the increasing severity of gait and posture impairments since they result in debilitating conditions such as freezing of gait, increased likelihood of falls, and poor quality of life. Although dopaminergic therapy and deep brain stimulation are generally effective, they often fail to improve gait and posture deficits. Several recent studies have employed real-time feedback (RTF) of gait parameters to improve walking patterns in PD. In earlier work, results from the investigation of the effects of RTF of step length and back angle during treadmill walking demonstrated that people with PD could follow the feedback and utilize it to modulate movements favorably in a manner that transferred, at least acutely, to overground walking. In this work, recent advances in wearable technologies were leveraged to develop a wearable real-time feedback (WRTF) system that can monitor and evaluate movements and provide feedback during daily activities that involve overground walking. Specifically, this work addressed the challenges of obtaining accurate gait and posture measures from wearable sensors in real-time and providing auditory feedback on the calculated real-time measures for rehabilitation. An algorithm was developed to calculate gait and posture variables from wearable sensor measurements, which were then validated against gold-standard measurements. The WRTF system calculates these measures and provides auditory feedback in real-time. The WRTF system was evaluated as a potential rehabilitation tool for use by people with mild to moderate PD. Results from the study indicated that the system can accurately measure step length and back angle, and that subjects could respond to real-time auditory feedback in a manner that improved their step length and uprightness. These improvements were exhibited while using the system that provided feedback and were sustained in subsequent trials immediately thereafter in which subjects walked without receiving feedback from the system.
ContributorsMuthukrishnan, Niveditha (Author) / Abbas, James (Thesis advisor) / Krishnamurthi, Narayanan (Thesis advisor) / Shill, Holly A (Committee member) / Honeycutt, Claire (Committee member) / Turaga, Pavan (Committee member) / Ingalls, Todd (Committee member) / Arizona State University (Publisher)
Created2022
Description
This project explores the potential for the accurate prediction of basketball shooting posture with machine learning (ML) prediction algorithms, using the data collected by an Internet of Things (IoT) based motion capture system. Specifically, this question is addressed in the research - Can I develop an ML model to generalize a decent basketball shot pattern? - by introducing a supervised learning paradigm, where the ML method takes acceleration attributes to predict the basketball shot efficiency. The solution presented in this study considers motion capture devices configuration on the right upper limb with a sole motion sensor made by BNO080 and ESP32 attached on the right wrist, right forearm, and right shoulder, respectively, By observing the rate of speed changing in the shooting movement and comparing their performance, ML models that apply K-Nearest Neighbor, and Decision Tree algorithm, conclude the best range of acceleration that different spots on the arm should implement.
ContributorsLiang, Chengxu (Author) / Ingalls, Todd (Thesis advisor) / Turaga, Pavan (Thesis advisor) / De Luca, Gennaro (Committee member) / Arizona State University (Publisher)
Created2023