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As healthy diets and nutrition are crucial for people with Alzheimer's disease (AD), caregivers of patients with AD need to provide a balanced diet with the correct nutrients to boost the health and well-being of patients. However, this is challenging as they are likely to suffer from aging-related problems (such as teeth or gum problems) that make eating more uncomfortable; the planners, who are usually patients' family members, generally face high pressure, a busy schedule, and little experience. To help unprofessional caregivers of AD plan meals with the right nutrition and flavors, in this paper, the authors propose a meal planning mechanism that uses a multiple criteria decision-making approach to integrate various factors that affect a caregiver's choice of meals for AD patients. Ontology-based knowledge has been used to model personal preferences and characteristics and customize general diet recommendations. Case studies have demonstrated the feasibility and usability of the proposed approach.
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ADDietCoach: A Personalized Virtual Diet Coach for Alzheimer's Disease
The aging population worldwide is expected to increase the prevalence of Alzheimer's disease. As there is no medical curative treatment for this disease to date, alternative treatments have been applied to improve the patient's brain and general health. One of these efforts includes providing Alzheimer's patients with proper food and nutrition. In this paper, the authors propose a knowledge-powered personalized virtual coach to provide diet and nutrition assistance to patients of Alzheimer's and/or their informal caregivers. The virtual coach is built on top of an ontology-enhanced knowledge base containing knowledge about patients, Alzheimer's disease, food, and nutrition. Semantics-based searching and reasoning are performed on the knowledge base to get personalized context-aware recommendation and education about healthy eating for Alzheimer's patients. The proposed system has been implemented as a mobile application. Evaluation based on use cases has demonstrated the usefulness of this tool.
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- Award ID(s):
- 1722913
- PAR ID:
- 10229770
- Date Published:
- Journal Name:
- International Journal of E-Health and Medical Communications
- Volume:
- 12
- Issue:
- 6
- ISSN:
- 1947-315X
- Page Range / eLocation ID:
- 1 to 18
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.4018/IJEHMC.20211101.oa6
