MUHAMMAD HAZEEM BIN FAIZUL ZAHAR Universiti Teknologi Malaysia
Mobility decline and fall-related injuries are major causes of disability and hospitalization among elderly yet early biomechanical assessment is often inaccessible due to high costs specialized equipment and physically demanding clinical visits. Mobivia addresses this gap as a low-cost artificial intelligence (AI) based system for home-based mobility and fall risk screening using standard consumer cameras without wearable sensors. The system uses advanced computer vision with real-time three-dimensional (3D) coordinate mapping and modeling to track key anatomical landmarks during a structured three-minute dynamic assessment. Mobivia shifts from reactive fall detection to proactive prevention, promoting independent living and reducing long-term healthcare burdens.