| Affiliations: | College of Nursing |
| Team Leader: |
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| Faculty Mentor: |
Ladda Thiamwong, PhD, MSN, RN
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Team Size:
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4 |
| Open Spots: | 4 |
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Team Member Qualifications:
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Preferred: Team members applying to this project are expected to have experience or interest in research related to AI, healthcare technology, aging, or computer vision. Familiarity with machine learning, computer vision, or app development is a plus. An interest or background in computer science, engineering, kinesiology, health sciences, or related fields is preferred. Basic programming knowledge (Python preferred, but not mandatory) is required. |
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Description:
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This project focuses on the development and evaluation of the SafeFall Coach application. It is a mobile application that combines interactive video-based learning with AI-driven feedback, enabling older adults (OAs) to practice safer movement tailored to their individual mobility levels. The objective is to enhance personalized learning, support independence, and promote aging in place, bridging the gap between detection and prevention in fall-related care. This research integrates artificial intelligence, computer vision, and user-centered design to provide real-time, personalized feedback on user movement and fall recovery techniques. The system analyzes movements through video-based pose estimation and translates them into simple, actionable guidance using AI models. The project involves both technology development and human-centered research, including usability testing, participant engagement, and evaluation of the app’s effectiveness in real-world settings. Team members will focus on research activities, including data collection, application testing, evaluation, and preparation of research manuscripts. They will gain hands-on experience in healthcare technology research. |