abstract: Parkinson’s disease (PD) is a neurological disorder with complicated and disabling motor and non-motor symptoms. The pathology for PD is difficult and expensive. Furthermore, it depends on patient diaries and the neurologist’s subjective assessment of clinical scales. Objective, accurate, and continuous patient monitoring have become possible with the advancement in mobile and portable equipment. Consequently, a significant amount of work has been done to explore new cost-effective and subjective assessment methods or PD symptoms. For example, smart technologies, such as wearable sensors and optical motion capturing systems, have been used to analyze the symptoms of a PD patient to assess their disease progression and even to detect signs in their nascent stage for early diagnosis of PD. This review focuses on the use of modern equipment for PD applications that were developed in the last decade. Four significant fields of research were identified: Assistance diagnosis, Prognosis or Monitoring of Symptoms and their Severity, Predicting Response to Treatment, and Assistance to Therapy or Rehabilitation. This study reviews the papers published between January 2008 and December 2018 in the following four databases: Pubmed Central, Science Direct, IEEE Xplore and MDPI. After removing unrelated articles, ones published in languages other than English, duplicate entries and other articles that did not fulfill the selection criteria, 778 papers were manually investigated and included in this review. A general overview of PD applications, devices used and aspects monitored for PD management is provided in this systematic review. / Dissertation/Thesis / Masters Thesis Computer Engineering 2019

DYSPHONIA is a music and dance work, for violin soloist with a live chamber orchestra, including multiple laptops and a custom-built gesture detection system worn by a dancer. The piece was choreographed by Professor Charlotte Adams of the University of Iowa Dance Department and premiered at the Faculty Graduate Dance Concerts in February of 2015. This piece is inspired by ongoing research into computer programming, gesture and music-making, artificial intelligence (AI), and creative algorithms. While the actual algorithms I developed for use in this piece are far from sentient, it is my hope that this piece may bring about discussion and further interest in creative AI. In our initial discussions, choreographer Charlotte Adams and I discovered that we both have witnessed a large number of people buying into immersive technologies without questioning the total cost to their well being, without questioning whether the technology has a positive impact on their lives, and without an understanding regarding the complex changes being wrought in our society due to the mass adoption of such technologies. Thus we designed this piece around the technology itself, so that the union between the dancer and the prosthesis is brought about by the movement and action that takes place in the piece. The intent was to create a scene where the audience suddenly becomes aware that something new is happening, namely that the dancer’s glove has started to make noise and there is a new connection made between the music and the dance.

Providing healthcare to the ever-rising elderly population has become a severe challenge and a top priority. Emerging innovations in healthcare, such as remote health monitoring technologies, promise to provide a better quality of care and reduce the cost of healthcare. However, many elderly people reject healthcare innovations. This lack of adoption constitutes a big practical problem because it keeps the elderly from benefiting from technology advances. The phenomenon is even more pronounced among elderly women, who represent the majority of the elderly population. A plethora of studies in the field of technology adoption resulted in sound, but highly generalized theories that are too parsimonious to provide practical insight into the phenomenon of elderly healthcare technology adoption (EHTA). There is a call to arms for novel approaches that facilitate the creation of models that expand technology adoption theories to the specifics of EHTA. This dissertation is a response to this call to arms, and it contributes to modeling practice in the EHTA field. It uses fuzzy cognitive mapping to design a novel mixed-methods modeling approach. Since elderly women constitute the majority of the elderly population, this dissertation treats elderly women's health technology adoption (EWHTA) as the case-in-point.

The health and safety of workers is critically important to all companies, especially those operating in hazardous environments.  Companies typically rely on an array of personal protective equipment to help ensure the safety of their workers, however as technology evolves, a new generation of devices are helping revolutionize the industry.  Wearable technology is now becoming commonplace in both our personal and professional lives.    This study focused on understanding the use of, and attitude towards, various wearable technologies by workers in hazardous environments.  It also explored the change in perception within the workers as these technologies were leveraged and made recommendations for improvement in the future.   A qualitive methodology was applied to understand the people, social, and cultural context.  Participants from industry were interviewed in an inductive and iterative manner, extracting data with an emphasis on the narrative.  Thematic analysis was then utilized to distill the data into Codes, Categories, and ultimately Concepts.   While it became evident that workers had limited personal experience with wearable technology outside of the workplace, they all used it in some manner during their work.  The use of wearable technology was largely motivated by policies and procedures imposed by the companies.  Interestingly, the workers did have an expectation that the user of these devices had a positive impact on their overall safety.  Somewhat surprisingly, the outlook on the future of the technology was not very positive.  There are several opportunities for improvement both to design and implementation of safety related wearable technology, as well as a desire to better leverage artificial intelligence and augmented reality.   Most companies utilize some level of wearable technology to assist in keeping their workers safe.  How workers utilize wearable technology to identify dangerous locations and situations varies greatly from organization to organization, but also between individual workers within any organization.  Although the use of wearable technology within the workplace has been demonstrated to improve safety, the primary motivator for its use is the fact that organization mandate their staff to compliance through policies and standard operating processes. Despite the fact that personal safety should be of utmost importance to any worker, they appear to be so unmotivated to actually utilize the technology available to them that it must be made mandatory through policy.  Within this environment, it becomes very difficult for workers to consider how wearable technology capabilities can be improved in regard to safety-related situational awareness.

INTRODUCTION: The zero-velocity update (ZUPT) method has become a popular approach to estimate foot kinematics from foot worn inertial measurement units (IMUs) for walking and running. However, it remains unknown how accurate the ZUPT method is for track sprinting speeds when using sensors with characteristics (i.e., higher ranges and sampling rates) better suited for sprinting. METHODS: 18 participants performed 70-meter track sprints while wearing a Blue Trident IMeasureU IMU. Two cameras, at 20 and 70 meters from the start, were placed to validate the ZUPT method on a stride-by-stride and on a cumulative distance basis. The validity of the method was assessed on: (1) A single stride attained at the end of the maximal speed phase, i.e., at 70m; (2) On a cumulative distance basis for the maximal speed phase from 20 to 70 meter; and (3) On total distance traveled for a 70-meter track sprint. RESULTS: Individual stride and cumulative distance errors remained within -8 to 3% and -4 to 2%, respectively. CONCLUSION: The results of this study demonstrate the ZUPT method is capable of yielding accurate estimates of stride length and cumulative distance traveled for sprinting speeds.

This body of work is the culmination of a two year investigation into the role of electronically enhanced apparel and artefacts in providing empathetic linkage between people who do not share physical space. The research draws from the diverse fields of philosophy, communications theory, neuropsychology, presence technologies and technologically advanced textiles, and proposes that a nexus of these disciplines may provide significant opportunities for enhancing the user interactivity of garments and artefacts. Remote emotional connection is investigated through the creation of sensor embedded garments and artefacts that have been developed in collaboration with a fashion designer and an electronics engineer. The prototypes encourage remote empathetic connection through the real-time transference of heartbeat. The exegesis is structured into five chapters which consider remote presence, flexible consciousness, the architecture of empathy, plasticity in sense perception and the development of prototypes. The project chapter focuses in the development of and testing of a rnage of garments and artefacts thatt conduct presence information between remotely located people. The garments sense, process, transmit and receive the heartbeat signal (ECG). They are enabled with ECG sensors, signal processing equipment, small vibration motors and radio transceivers which allow users to 'feel' the heartbeat of a remote friend/lover/relative as vibration through their garment. The prototypes aim to enrich the remote communications experience through reintroducing an embodied, tactile dimension that is present in face-to-face communication. A range of user testing trials are discussed in the thesis which have been undertaken to assess the impact of the garments at a conscious and a non-conscious level. Conscious experiences were gauged through qualitative testing by way of interviews and unsolicited written reactions. Non-conscious physiological ractions were assessed by recording ECG throughout user-testing periods. This data has been processed by using HRV (heart rate variability) analysis software, running on MatLab.

The proliferation of body worn autometric devices has been enabled by advances in low-power electronics and fueled by the quantified-self movement. These devices range in complexity from pedometers to clinical vital sign measurement. They all share the same drawback, typically the most expensive and heaviest component, the battery. The future of autometric devices lies in wireless power. This work explores what is required from autometric devices and presents the results of testing both an embedded version and an application specific integrated circuit (ASIC) version of a wirelessly powered autometric device. / Graduation date: 2013

A Wearable Mobility Monitoring System (WMMS) can be an advantageous device for rehabilitation decision-making. This thesis presents the design and evaluation of a proof-of-concept WMMS that uses the BlackBerry Smartphone platform. A Java program was developed for the BlackBerry 9550, using the integrated tri-axial accelerometer, Global Positioning System sensor (GPS), CMOS digital video camera, and timer to identify change-of-state (CoS) among static states, dynamic states, small activity of daily living (ADL) movements, and car riding. Static states included sitting, lying, standing, and taking an elevator. Dynamic states included walking on level ground, walking on stairs, and walking on a ramp. Small activity of daily living movements included bathroom activities, working in the kitchen, and meal preparation. Following feature extraction from the sensor data, two decision trees were used to distinguish CoS and mobility activities. CoS identification subsequently triggered video recording for improved mobility context analysis during post-processing.

A Wearable Mobility Monitoring System (WMMS) can be an advantageous device for rehabilitation decision-making. This thesis presents the design and evaluation of a proof-of-concept WMMS that uses the BlackBerry Smartphone platform. A Java program was developed for the BlackBerry 9550, using the integrated tri-axial accelerometer, Global Positioning System sensor (GPS), CMOS digital video camera, and timer to identify change-of-state (CoS) among static states, dynamic states, small activity of daily living (ADL) movements, and car riding. Static states included sitting, lying, standing, and taking an elevator. Dynamic states included walking on level ground, walking on stairs, and walking on a ramp. Small activity of daily living movements included bathroom activities, working in the kitchen, and meal preparation. Following feature extraction from the sensor data, two decision trees were used to distinguish CoS and mobility activities. CoS identification subsequently triggered video recording for improved mobility context analysis during post-processing.

Human beings live and work in large and complex environments. It is often difficult for individuals to perceive and understand the structure of these environments. However, the formation of an accurate and reliable cognitive map, a mental model of the environment, is vital for optimal navigation and coordination. The need to develop a reliable cognitive map is common to the average individual as well as workers with more specialized tasks, for example, law enforcement or military personnel who must quickly learn to operate in a new area. In this dissertation, I propose the use of a wearable computer as a platform for a spatial cognition aid. This spatial cognition aid uses terrain visualization software, GPS positioning, orientation sensors, and an eyeglass mounted display to provide an overview of the surrounding environment. While there are a number of similar mobile or wearable computer systems that function as tourist guides, navigation aids, and surveying tools, there are few examples of spatial cognition aids. I present an architecture for the wearable computer based spatial cognition aid using a relationship mediation model for wearable computer applications. The relationship mediation model identifies and describes the user relationships in which a wearable computer can participate and mediate. The dissertation focuses on how the wearable computer mediates the users perception of the environment. Other components such as interaction techniques and a scalable system of servers for distributing spatial information are also discussed. Several user studies were performed to determine an effective presentation for the spatial cognition aid. Participants were led through an outdoor environment while using different presentations on a wearable computer. The spatial learning of the participants was compared. These studies demonstrated that a wearable computer can be an effective spatial cognition aid. However, factors such as such as mental rotation, cognitive load, distraction, and divided attention must be taken into account when presenting spatial information to a wearable computer user.