abstract: The burden of adaptation has been a major limiting factor in the adoption rates of new wearable assistive technologies. This burden has created a necessity for the exploration and combination of two key concepts in the development of upcoming wearables: anticipation and invisibility. The combination of these two topics has created the field of Anticipatory and Invisible Interfaces (AII)
In this dissertation, a novel framework is introduced for the development of anticipatory devices that augment the proprioceptive system in individuals with neurodegenerative disorders in a seamless way that scaffolds off of existing cognitive feedback models. The framework suggests three main categories of consideration in the development of devices which are anticipatory and invisible:
• Idiosyncratic Design: How do can a design encapsulate the unique characteristics of the individual in the design of assistive aids?
• Adaptation to Intrapersonal Variations: As individuals progress through the various stages of a disability/neurological disorder, how can the technology adapt thresholds for feedback over time to address these shifts in ability?
• Context Aware Invisibility: How can the mechanisms of interaction be modified in order to reduce cognitive load?
The concepts proposed in this framework can be generalized to a broad range of domains; however, there are two primary applications for this work: rehabilitation and assistive aids. In preliminary studies, the framework is applied in the areas of Parkinsonian freezing of gait anticipation and the anticipation of body non-compliance during rehabilitative exercise. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2020
| Identifer | oai:union.ndltd.org:asu.edu/item:57384 |
| Date | January 2020 |
| Contributors | Tadayon, Arash (Author), Panchanathan, Sethuraman (Advisor), McDaniel, Troy (Committee member), Krishnamurthi, Narayanan (Committee member), Davulcu, Hasan (Committee member), Li, Baoxin (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Doctoral Dissertation |
| Format | 137 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/ |
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