Providing Support in Real Time with Smart Technologies to Improve Quality of Life
Abstract
Individuals living with symptoms of traumatic brain injury (TBI) and Alzheimer s disease (AD) experience changes in their memory and thinking abilities that can impact capacity to accurately manage everyday tasks of daily living (e.g., cooking, managing medications). Such functional impairment in older adults with cognitive difficulties has been associated with a host of negative healthcare consequences, including increased healthcare utilization and placement in long-term care facilities, difficulty gaining and maintaining employment, social isolation, and conversion to dementia. Caregivers of individuals living with symptoms of TBI and AD are also at increased risk for health problems. Technologies that can help these individuals complete everyday activities and maintain independent living in their own homes, while simultaneously decreasing caregiver burden are of significant value to the individuals, caregivers, and society. In the past decade, a convergence of technologies in data mining and pervasive computing, as well as increasing accessibility of sensors and actuators, have made smart environment technologies a reality. Smart environments provide the capability to sense activity in an everyday environment. Machine learning techniques can then be used to identify these activities and use this information to assess the functional health of the resident. The smart home can then act on the information in such a way that it sustains or improves the health of the resident and extends the time that the individual can live independently in the environment. In our previous work, we have shown that sensor data and machine learning techniques can be used to recognize everyday activities, provide insights on everyday functioning, and partially automate assistance. Currently, however, there remain gaps in our knowledge about how to use these technologies to design real-time automated assistance, which limits clinical use of smart environment technologies for supporting independent living. The primary objective of this application is to develop a smart home/digital memory notebook partnership that will assist older individuals with cognitive impairment in maintaining independence with everyday tasks of daily living, thereby improving their quality of life and reducing burden for caregivers living with the symptoms of TBI and AD (e.g., decrease need to monitor and track everyday activities). The central hypothesis is that activity-aware prompting and transition detection algorithms can be harnessed to continually engage individuals with cognitive impairment to use a digital memory notebook to plan daily tasks, track daily events, and initiate important activities to support and extend ability to remain independent at home. The rationale for the proposed work is that pairing the digital memory notebook with smart environment technologies will significantly enhance the learning and long-term usability of traditional paper-pencil memory notebooks, which are often lengthy to train, not utilized to their full extent, and abandoned with disease progression. We will build on our prior interface design and clinical work with a paper-pencil memory notebook to develop a user-friendly, digital version of a memory notebook that will be usable by older individuals with TBI and AD. We will then partner the digital memory notebook with our smart-home based recognition and discovery mechanisms to identify and track routine activities and to determine if planned tasks are being performed. The digital memory notebook will utilize information provided by a smart environment to sense daily activities and prompt individuals to use the notebook or initiate important activities such as showering in an activity-aware manner (e.g., after breakfast). In a pilot study, we will evaluate the effects of the digital memory notebook/smart home partnership on memory notebook use, everyday functioning, and quality of life for individuals with memory
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 31, 2017
- Source ID
- W81XWH1610709
Entities
People
- Maureen Schmitter-Edgecombe
Organizations
- United States Army
- Washington State University