Seniar Project
-A Framework for Dependable AI-driven Edge-Cloud
System for Elderly Activity Monitoring:
Contributed to the development of an innovative healthcare solution addressing the challenges of traditional elderly activity monitoring. The system integrates a Flutter-based web application, a custom-trained YOLOv8m pose estimation model, and real-time edge-cloud computing for activity detection and caregiver support.
UX/UI Project
-Osteoporosis web application:
A web application for medical staff to streamline osteoporosis risk assessment and patient management. The app calculates FRAX scores based on patient data, identifies risk levels, and provides treatment recommendations.
-PharmEasy:
A medical consultation and drug delivery app. The objective is to provide medical services to people in remote areas that lack basic healthcare facilities and healthcare professionals.
-THERAVISION
The app uses AI and computer vision to monitor and analyze physical movement, providing real-time feedback for individuals in rehabilitation. Using the PhysioPose YOLOv11 model, it helps users track exercises, ensuring proper form for better recovery. Designed for both in-clinic and at-home use.