Assisting Personalized Healthcare of Elderly People: Developing a Rule-Based Virtual Caregiver System Using Mobile...

Area of Science:

• Gerontology
• Human-Computer Interaction
• Digital Health

Background:

• Personalized healthcare for the elderly requires effective monitoring of mental and physical health states.
• Conventional health monitoring methods may lack engagement and personalized feedback mechanisms.

Purpose of the Study:

• To implement and evaluate a virtual caregiver system using a mobile chatbot for elderly healthcare.
• To integrate rule-based systems with questionnaires for comprehensive health assessment.

Main Methods:

• Developed a mobile chatbot integrating a rule-based "Mind Monitoring" service with physical, mental, and social questionnaires.
• Utilized daily questions answered via button press or speech recognition.
• Implemented a novel method to quantify answers, generate visual graphs, and provide tailored summaries/advice.

Main Results:

• Achieved an 80% response rate in experimental evaluations with elderly and younger subjects.
• Demonstrated accurate reflection of subjects' real lives through responses.
• Confirmed high usefulness of feedback messages aligned with software quality requirements.

Conclusions:

• The virtual caregiver system effectively monitors elderly health through dialogue-based human-computer interaction.
• The integrated approach offers a promising tool for personalized elderly healthcare and feedback.
• Further analysis through subject interviews supports health improvement strategies.