Predicting Prosthetic Limb Movement and Integrated Tactile-Based Walker Systems for Improving Mobility and Safety for the Elderly, Visually Impaired & Prosthetic Patients by exploring their shared technological foundations and paired objectives. Both focus on improving mobility, adaptability, and user safety through intelligent systems. The prosthetic limb device uses machine learning to predict user intentions, enabling seamless, intuitive control of artificial limbs, thereby enhancing precision and user confidence. Simultaneously, the tactile-based walker system employs multimodal depth sensing to provide real-time environmental awareness, minimizing fall risks and improving navigation for individuals who face challenge in walking. These systems share key elements, such as sensor fusion, real-time decision-making, and adaptability, making their integration a promising pathway for developing unified assistive technologies. By combining predictive modeling with multimodal sensory feedback, this framework can address diverse mobility challenges, organizing to prosthetic limb users, elderly and visionary impaired individuals with limited physical capabilities. The resulting platform would deliver personalized support, enhancing independence, safety, and quality of life. These aids are technologically advanced, user-centric, and capable of adapting to the dynamic needs of diverse users.

 

Products and Technical Aids

• Tactile-based Walker System Utilizing Multimodal Depth Sensing System (Unique and Innovative Product)
• Tactile Sticks  (Unique and Innovative Product)
• Smart Machine Learning based Device for Predicting Prosthetic Limb Movement (PATENTED)