The project aims to develop a prototype software tool that utilizes AI and machine learning to assess frailty indicators in older adults. The focus will be on measuring key indicators such as walking speed, grip strength, balance, and flexibility. By analyzing these metrics, the tool will help in early detection of frailty, potentially improving the quality of life for the elderly. The project will involve data collection, algorithm development, and testing to ensure accuracy and reliability. Learners will apply their knowledge of AI and machine learning to create a user-friendly interface that people can use from their personal computing devices. The project will also require a review of existing literature to understand current methodologies and identify gaps that the new tool can address.

The deliverables for this project include a functional prototype of the frailty indicator analysis tool, complete with a user interface. Additionally, a comprehensive report detailing the development process, algorithms used, and testing results will be provided. The team will also prepare a presentation to demonstrate the tool's capabilities and potential applications in healthcare settings.