Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- All Subjects: Technology and older people
- Creators: Li, Baoxin
Description
As people age, the desire to grow old independently and in place becomes larger and takes greater importance in their lives. Successful aging involves the physical, mental and social well-being of an individual. To enable successful aging of older adults, it is necessary for them to perform both activities of daily living (ADL) and instrumental activities of daily living (IADL). Embedded assessment has made it possible to assess an individual's functional ability in-place, however the success of any technology depends largely on the user than the technology itself. Previous researches in in-situ functional assessment systems have heavily focused on the technology rather than on the user. This dissertation takes a user-centric approach to this problem by trying to identify the design and technical challenges of deploying and using a functional assessment system in the real world.
To investigate this line of research, a case study was conducted with 4 older adults in their homes, interviews were conducted with 8 caregivers and a controlled lab experiment was conducted with 8 young healthy adults at ASU, to test the sensors. This methodology provides a significant opportunity to advance the scientific field by expanding the present focus on IADL task performance to an integrated assessment of ADL and IADL task performance. Doing so would not only be more effective in identifying functional decline but could also provide a more comprehensive assessment of individuals' functional abilities with independence and also providing the caregivers with much needed respite.
The controlled lab study tested the sensors embedded into daily objects and found them to be reliable, and efficient. Short term exploratory case studies with healthy older adults revealed the challenges associated with design and technical aspects of the current system, while inductive analysis performed on interviews with caregivers helped to generate central themes on which future functional assessment systems need to be designed and built. The key central themes were a) focus on design / user experience, b) consider user's characteristics, personality, behavior and functional ability, c) provide support for independence, and d) adapt to individual user's needs.
To investigate this line of research, a case study was conducted with 4 older adults in their homes, interviews were conducted with 8 caregivers and a controlled lab experiment was conducted with 8 young healthy adults at ASU, to test the sensors. This methodology provides a significant opportunity to advance the scientific field by expanding the present focus on IADL task performance to an integrated assessment of ADL and IADL task performance. Doing so would not only be more effective in identifying functional decline but could also provide a more comprehensive assessment of individuals' functional abilities with independence and also providing the caregivers with much needed respite.
The controlled lab study tested the sensors embedded into daily objects and found them to be reliable, and efficient. Short term exploratory case studies with healthy older adults revealed the challenges associated with design and technical aspects of the current system, while inductive analysis performed on interviews with caregivers helped to generate central themes on which future functional assessment systems need to be designed and built. The key central themes were a) focus on design / user experience, b) consider user's characteristics, personality, behavior and functional ability, c) provide support for independence, and d) adapt to individual user's needs.
ContributorsRavishankar, Vijay Kumar (Author) / Burleson, Winslow (Thesis advisor) / Coon, David (Committee member) / Mahoney, Diane (Committee member) / Walker, Erin (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2015
Description
Advances in the area of ubiquitous, pervasive and wearable computing have resulted in the development of low band-width, data rich environmental and body sensor networks, providing a reliable and non-intrusive methodology for capturing activity data from humans and the environments they inhabit. Assistive technologies that promote independent living amongst elderly and individuals with cognitive impairment are a major motivating factor for sensor-based activity recognition systems. However, the process of discerning relevant activity information from these sensor streams such as accelerometers is a non-trivial task and is an on-going research area. The difficulty stems from factors such as spatio-temporal variations in movement patterns induced by different individuals and contexts, sparse occurrence of relevant activity gestures in a continuous stream of irrelevant movements and the lack of real-world data for training learning algorithms. This work addresses these challenges in the context of wearable accelerometer-based simple activity and gesture recognition. The proposed computational framework utilizes discriminative classifiers for learning the spatio-temporal variations in movement patterns and demonstrates its effectiveness through a real-time simple activity recognition system and short duration, non- repetitive activity gesture recognition. Furthermore, it proposes adaptive discriminative threshold models trained only on relevant activity gestures for filtering irrelevant movement patterns in a continuous stream. These models are integrated into a gesture spotting network for detecting activity gestures involved in complex activities of daily living. The framework addresses the lack of real world data for training, by using auxiliary, yet related data samples for training in a transfer learning setting. Finally the problem of predicting activity tasks involved in the execution of a complex activity of daily living is described and a solution based on hierarchical Markov models is discussed and evaluated.
ContributorsChatapuram Krishnan, Narayanan (Author) / Panchanathan, Sethuraman (Thesis advisor) / Sundaram, Hari (Committee member) / Ye, Jieping (Committee member) / Li, Baoxin (Committee member) / Cook, Diane (Committee member) / Arizona State University (Publisher)
Created2010