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
eurological 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.

Most collegiate organizations aim to unite students with common interests and engage them in a like-minded community of peers. A significant sub-group of these organizations are classified under sororities and fraternities and commonly known as Greek Life. Member involvement is a crucial element for Greek Life as participation in philanthropic events, chapter meetings, rituals, recruitment events, etc. often reflects the state of the organization. The purpose of this project is to create a web application that allows members of an Arizona State University sorority to view their involvement activity as outlined by the chapter. Maintaining the balance between academics, sleep, a social life, and extra-curricular activities/organizations can be difficult for college students. With the use of this website, members can view their attendances, absences, and study/volunteer hours to know their progress towards the involvement requirements set by the chapter. This knowledge makes it easier to plan schedules and alleviate some stress associated with the time-management of sorority events, assignments/homework, and studying. It is also designed for the sorority leadership to analyze and track the participation of the membership. Members can submit their participation in events, making the need for manual counting and calculations disappear. The website administrator(s) can view and approve data from any and all members. The website was developed using HTML, CSS, and JavaScript in conjunction with Firebase for the back-end database. Human-Computer Interaction (HCI) tools and techniques were used throughout the development process to aide in prototyping, visual design, and evaluation. The front-end appearance of the website was designed to mimic the data manipulation used in the current involvement tracking system while presenting it in a more personalized and aesthetically pleasing manner.

Parkinson's disease is a neurodegenerative disorder in the central nervous system that affects a host of daily activities and involves a variety of symptoms; these include tremors, slurred speech, and rigid muscles. It is the second most common movement disorder globally. In Stage 3 of Parkinson's, afflicted individuals begin to develop an abnormal gait pattern known as freezing of gait (FoG), which is characterized by decreased step length, shuffling, and eventually complete loss of movement; they are unable to move, and often results in a fall. Surface electromyography (sEMG) is a diagnostic tool to measure electrical activity in the muscles to assess overall muscle function. Most conventional EMG systems, however, are bulky, tethered to a single location, expensive, and primarily used in a lab or clinical setting. This project explores an affordable, open-source, and portable platform called Open Brain-Computer Interface (OpenBCI). The purpose of the proposed device is to detect gait patterns by leveraging the surface electromyography (EMG) signals from the OpenBCI and to help a patient overcome an episode using haptic feedback mechanisms. Previously designed devices with similar intended purposes utilize accelerometry as a method of detection as well as audio and visual feedback mechanisms in their design.