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Abstract AimThe aim of this study is to develop a Smarthealth system of monitoring, modelling, and interactive recommendation solutions (for caregivers) for in‐home dementia patient care that focuses on caregiver–patient relationships. DesignThis descriptive study employs a single‐group, non‐randomized trial to examine functionality, effectiveness, feasibility, and acceptability of the novel Smarthealth system. MethodsThirty persons with Alzheimer's Disease or related dementia and their family caregivers (N = 30 dyads) will receive and install Smarthealth technology in their home. There will be a 1‐month observation phase for collecting baseline mood states and a 2‐month implementation phase when caregivers will receive stress management techniques for each detected, negative mood state. Caregivers will report technique implementation and usefulness, sent via Ecological Momentary Assessment system to the study‐provided smartphone. Caregivers will provide daily, self‐reported mood and health ratings. Instruments measuring caregiver assessment of disruptive behaviours and their effect on caregivers; caregiver depressive symptoms, anxiety and stress; caregiver strain; and family functioning will be completed at baseline and 3 months. The study received funding in 2018 and ethics board approval in 2019. DiscussionThis study will develop and test novel in‐home technology to improve family caregiving relationships. Results from this study will help develop and improve the Smarthealth recommendation system and determine its usefulness, feasibility, and acceptability for persons with dementia and their family caregiver. ImpactThe Smarthealth technology discussed will provide in‐home stress reduction resources at a time when older adults may be experiencing increasingly high rates of isolation and anxiety and caregiver dyads may be experiencing high levels of relationship strain. Trial RegistrationThis study was registered with Clinical Trials.gov (Identifier NCT04536701).
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CAL: A Smart Home Environment for Monitoring Cognitive Decline
The increased growth of the aging population (i.e., 65 years or older) has led to emerging technologies in health care that provide in-home support to patients using devices throughout the household. Such smart home environments can monitor and interact with patients and their doctors/caregivers to augment patient medical data for diagnosis than can be generated via traditional doctor visits. Moreover, smart homes are enabling older adults to stay at home longer as opposed to permanent moves to assisted living or nursing facilities, increasing health and well-being and decreasing overall costs to the individual and society at large. This paper proposes Cognitive Assisted Living (CAL), a cyber-physical system comprising a network of embedded devices for collecting and analyzing patient speech patterns over time for monitoring cognitive function beginning in the early stages of Alzheimer’s disease. Specifically, CAL will analyze patient speech patterns and spatial abilities, via a set of daily interactions, to provide a longitudinal analysis of speech deterioration, a significant indicator of cognitive decline resulting from Alzheimer’s disease. Understanding the rate of cognitive decline can enable caregivers and health care professionals to better manage the patient’s daily care and medical requirements. Additionally, the patient’s cognitive state can be shared across household devices to increase the patient’s comfort and better accommodate lifestyle changes. To these ends, we describe the architecture of the proposed system, the methods to which we will detect cognitive decline, and specify how the system will provide continuing fault tolerance and data security at run time.
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- Award ID(s):
- 1657061
- PAR ID:
- 10063903
- Date Published:
- Journal Name:
- Proceedings of the International Conference on Distributed Computing Systems
- ISSN:
- 1063-6927
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Purpose/ObjectivesWe aim to explore Current Procedural Terminology (CPT) codes for caregiving training services and their potential impacts on caregivers of people living with dementia. Description of the Project/ProgramIn response to the growing need for support for caregivers of people living with physical and mental health issues, CPT codes for caregiving training services will be activated for the calendar year 2024. These codes cover (1) family group behavior management and modification training services and (2) caregiver training for techniques to help patients maintain their quality of life. Caregivers will access such training support through the CPT codes provided by treating practitioners. The duration of training will vary by code. OutcomeImplementing CPT codes for caregiver training services highlights the vital role of caregivers in patient care. This support may improve their skills and communication with healthcare providers. However, timing and accessibility in care delivery need clarification, especially for caregivers of people living with dementia. Regular skill assessment and culturally competent care are essential. Before providing the service, provider training may also promote person-centered care, benefiting patients and their caregivers. ConclusionActivating CPT codes for caregiving training services may enhance caregivers' support and skills, including dementia care.more » « less
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The number of patients diagnosed with Alzheimer's disease is significantly increasing, given the boom in the aging population (i.e., 65 years and older). There exist approximately 5.5 million people in the United States that have been diagnosed with Alzheimer's, and as a result friends and family often need to provide care and support (estimated at 15 million people to the cost of $1.1 trillion). Common symptoms of Alzheimer's disease include memory loss, drastic behavioral change, depression, and loss in cognitive and/or spatial abilities. To support the growing need for caregivers, this project developed a prototype virtual reality (VR) environment for enabling caregivers to experience typical scenarios, as well as common strategies for managing each scenario, that they may experience when providing care and support, thereby providing. For instance, a patient may turn on a gas stove and then leave, forgetting that the stove is on. The caregiver then would be required to turn the stove off, to minimize any potential dangers. The prototype environment, CARETAKVR, was developed as an undergraduate research project for learning the process of research as well as the Unity programming environment and VR. The prototype provides a gamified training tool, masking scenarios as objectives and success with a score, to enable the potential caregiver to feel rewarded for correctly supporting the patient. The virtual patient is controlled via artificial intelligence and follows an initial set of guidelines to behave as a patient with early-stage Alzheimer's may behave. The caregiver is provided with a set of tasks to perform, in VR space, to achieve their goals for each scenario. Common tasks include Check Refrigerator, Check Stove, and Comfort Patient. This project has been demonstrated to colleagues in the health care domain and has seeded future collaborations to iterate the capabilities of this tool. All project artifacts have been open-sourced and are available online.more » « less
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