Digital Twin for Manufacturing

Virtual AI Health Assistant

Current Students: Keerthana Srinivasan, Sam Rahimzadeh Holagh, Lavanya Nidamanuri, Johannas Meela Katikala

Status: Current

Recent advancements in generative artificial intelligence (AI), especially large language models (LLMs), have added a new dimension to the capabilities of NPCs (non-player characters) within these environments. These AI agents, powered by models like GPT, enable natural language understanding and generation, which allows users to engage in real-time, emotionally intelligent conversations. The goal of research in Virtual AI Health Assistants is to develop intelligent systems that can support, enhance, or automate healthcare services through natural and effective interaction with patients and healthcare providers. These assistants aim to provide accessible, personalized, and efficient care using artificial intelligence. Our vision is to create AI-powered assistants that are safe, reliable, empathetic, and medically competent, serving as partners in health management for both patients and professionals. Embedded within this environment are ConvAI-powered GPT NPCs that serve as the primary interface for user interaction. These agents engage in real-time conversations with users, helping them reflect on their emotional state, explore cognitive-behavioral techniques, and participate in mindfulness activities. The NPCs are capable of mood detection, enabling them to adapt their responses based on the user’s current affective state. This makes the interactions more authentic and supportive, mimicking the empathy and attentiveness of human therapists. Our objectives are

Personalized Health Support
1. Use data (e.g., medical history, symptoms, lifestyle) to tailor recommendations.
2. Offer continuous monitoring and support for chronic conditions.
Early Detection and Prevention
1. Identify potential health issues based on symptoms or trends in user data.
2. Encourage preventive care through reminders and education.
3. Guide users to appropriate care based on symptom analysis.
4. Reduce unnecessary ER visits by providing self-care guidance or connecting users to virtual consultations.
Integration with Healthcare Systems
1. Seamlessly share data with electronic health records (EHRs) or healthcare providers.
2. Assist with scheduling, medication adherence, and follow-ups.

Publications

Sharma, S., Pesaladinne R., "Spatial Analysis and Visual Communication of Emergency Information through Augmented Reality", Proceedings of the IS&T International Symposium on Electronic Imaging (EI 2024) in the Engineering Reality of Virtual Reality Conference, DOI: 10.2352/J.ImagingSci.Technol.2023.67.6.060401, January 21-25, 2024.