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Doctoral thesis
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Personalized, narrative and interactive simulation based on a rules-engine system designed to confront caregivers with personalized virtual Alzheimer's patients and to train their communicative coping strategy skills

ContributorsChauveau, Lucie
Defense date2020-10-23
Abstract

Alzheimer's Disease is a long lasting and ultimately severely debilitating mental illness. Although deterioration is inevitable, the rate of progression of the disease is quite variable from one individual to the other. The modification of the patient behavior at each stage of the illness makes caring for a patient with Alzheimer difficult and emotionally distressing for family members. Informal caregivers generally prefer to avoid placing their elderly relatives in nursing homes. However, family-caregivers require considerable support and assistance to keep patients at home. The innovative concept of this work is the combination of various technical fields of research and its application to a soft science field where the human is in the center. Research had been conducted in the fields of decision-support systems, behavior trees, hierarchical task networks, narrative interactive, educative system, agent behavior and personalization in simulation. The final user of this project is a non-technophile person, with a relative affected by Alzheimer's disease, overwhelmed by her caring duties, who is in need of learning how to behave in a more efficient way. This PhD work aims to design, to develop and to test a personalized, narrative and interactive simulation based on a rules-engine system dedicated to Alzheimer's informal caregivers to confront and learn coping strategies during activities of daily living.

eng
Citation (ISO format)
CHAUVEAU, Lucie. Personalized, narrative and interactive simulation based on a rules-engine system designed to confront caregivers with personalized virtual Alzheimer’s patients and to train their communicative coping strategy skills. 2020. doi: 10.13097/archive-ouverte/unige:144328
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Creation10/30/2020 6:38:00 PM
First validation10/30/2020 6:38:00 PM
Update time06/20/2023 11:06:04 AM
Status update06/20/2023 11:06:04 AM
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