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Using Interactive Genetic Algorithms to Support Aesthetic Ergonomic Design

Posted on:2013-03-22Degree:Ph.DType:Dissertation
University:University of MichiganCandidate:Nathan-Roberts, DanFull Text:PDF
GTID:1458390008481429Subject:Engineering
Abstract/Summary:
Aesthetic Ergonomics applies rigorous quantitative methodologies to the field of design to better understand aesthetic preference, potential tradeoffs between aesthetic and traditional ergonomic factors, and provide tools and methods that can be used in product design. This dissertation gives a better understanding of how users make aesthetic judgments within the domains of mobile phones and blood glucose meters, and demonstrates a tool and method for product designers.;Mobile phones and blood glucose meters are selected because they are common handheld digital input/output devices of functional and ergonomic consequence, whose users care immensely about their aesthetics. Interactive Genetic Algorithms (IGAs) and traditional Genetic Algorithms (GAs) are the primary research methodologies used in this dissertation. IGAs are a method of iteratively exploring a design space through a process of user-driven evolution that mimics natural selection. A GA, with a simplified physical ergonomics fitness function was used as a method of increasing the physical ergonomics of users' designs by combining it with an IGA.;Following the Dual Process Research Methodology, this dissertation uses top-down analysis to determine the aesthetic and ergonomic factors important in mobile device design, and then goes onto include bottom-up experiments to learn about aesthetic ergonomics, the use of genetic algorithms in aesthetic ergonomics, and mobile device design.;These studies found several ways that user aesthetic preference changes, specifically when: the user's goal(s) change, the way a device is used (touchscreen vs. non-touchscreen mobile phones) changes, and by experience. The research also found an aesthetic link between domains. IGAs combined with a physical ergonomic GA, to make mobile devices that were significantly more physically ergonomic, but not significantly less aesthetically pleasing to users, when compared to designs without a GA.;This dissertation has significant theoretical implications, including showing how users can hold multiple goals separate and combine them when designing devices. Practical implications include that the classic definitions of beauty, like the golden ratio, can serve as guides for designers, but do not apply perfectly to mobile devices.
Keywords/Search Tags:Aesthetic, Ergonomic, Genetic algorithms, Mobile, Devices
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