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Description
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

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.
ContributorsBaran, Michael (Author) / Rikakis, Thanassis (Thesis advisor) / Olson, Loren (Thesis advisor) / Wolf, Steven L. (Committee member) / Ingalls, Todd (Committee member) / Arizona State University (Publisher)
Created2014
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Description
When cartographers and graphic designers create maps they choose typefaces. Often, serif and sans serif typefaces are paired together to represent different information on a map. Typefaces have a communicated tone and choosing the correct typeface combination to send the intended message can be challenging. The purpose of this study

When cartographers and graphic designers create maps they choose typefaces. Often, serif and sans serif typefaces are paired together to represent different information on a map. Typefaces have a communicated tone and choosing the correct typeface combination to send the intended message can be challenging. The purpose of this study was to create an analysis of the aesthetic characteristics of typeface pairings to assist map creators when choosing typefaces. An online survey was utilized to collect responses from graphic designers who have been trained in at least one year or more in design from a higher education institution. There were 30 participants in the study and they scored 24 typeface pairings, 12 differentiating and 12 superfamily, on 48 maps. Scoring was done on eight aesthetic characteristics: friendly, whimsical, cheap, neutral, bland, corporate, serious and modern. The researcher conducted an analysis of each typeface’s microaesthetics and then compared these to the survey’s scored aesthetic characteristics. It was concluded that there are many factors that go into comparing the typeface pairings of serif and sans serif typeface combinations. However, a selection of a superfamily typeface pairing is better than selecting a differentiating pairing. Future research should focus on conducting studies with a varying amount of typeface styles. Also, to include less maps per survey and a survey completion status bar.
ContributorsFinden, Nathan (Author) / Ralston, Laurie (Thesis advisor) / Carrasquilla, Christina (Committee member) / Westover, William (Committee member) / Arizona State University (Publisher)
Created2018