Leveraging a Large Language Model to Empower Informal Caretakers of People with Dementia

Behavioral symptoms of Alzheimer's Disease and Related Dementias (ADRD) are detrimental to the quality of life for individuals with ADRD and their caregivers. Symptoms such as wandering, agitation, and confusion can often overwhelm caregivers leading to stress, depression, or burnout which can lead to a decrease in the quality of care. These challenges often result in increased hospitalizations and care costs, creating a need for a solution to support informal caregivers. This project proposes the development of an AI-based Dementia Care Voice Assistant application to meet the needs of caregivers. Using large language models, the application will provide real-time and personalized guidance to help caregivers manage complex behavioral symptoms. The LLMs will be designed to adapt responses to the user based on how they are prompted. To ensure that the output aligns with the best medical practices, we will establish a dataset based on evidence-based interventions from extensive literature reviews and interviews with informal caregivers. In addition to providing tailored responses, the application will offer assistance during emergency situations. The voice assistant will feature intuitive features such as recognizing signs of medical emergencies and prompting the user to contact 911 when necessary. Through the development of this application, informal caregivers will have access to accurate information and personalized assistance, alleviating caregiver stress, enhancing their confidence, and ultimately improving the quality of the care they deliver.