11 August 2025
Affordable Bionic Arm with Natural Grip Technology Gets Global Commendation for University Graduates
The freedom of mobility, a crucial aspect of wellbeing, gave rise to the prosthetics industry. However, while prosthetics are available, they remain inaccessible to many due to high costs and limited functionality, which often leads to user rejection. There is a clear need for more affordable and versatile devices that can handle a variety of objects with natural grip patterns. Existing prosthetic devices lack adaptability, are costly, and fail to provide natural-like gripping and feedback, thereby reducing accessibility for many amputees.
Addressing this problem, our graduates Hetav Shah and Dev Shah explored design elements for an affordable bionic prosthetic arm. Their research, which evolved from an initial three-claw prototype to a more advanced five-claw model, demonstrates how engineering can curb accessibility challenges by focusing on enhanced grip patterns, adaptive features, and economic feasibility.
Their solution, detailed in the paper, “Design and Development of a Low-Cost Prosthetic Arm: Towards Enhanced Grip Patterns, Versatility, and Accessibility,” was recently presented at the Second International Conference on Advances in Modern Age Technologies for Health and Engineering Science (AMATHE 2025). The paper was subsequently published in the IEEE Xplore proceedings.
The innovation’s uniqueness lies in its adaptive grip patterns, which incorporate four distinct modes, thumb-only, thumb and finger, pinch, and full power grip. This allows users to handle a wide variety of objects, from delicate items to heavier, irregular shapes, a feature often missing in current prosthetics. The grips closely mimic natural hand movements, increasing usability in real-life scenarios. Graduates they evolved their previous design from a three-claw to a five-claw structure to provide more stability and a wider contact area for better grip. Silicone tips on the fingers add friction, reducing slippage and enhancing precision.
Additionally, the innovation integrates Electromyographic (EMG) sensors to capture muscle signals from the forearm. This provides real-time, intuitive control with minimal delay (less than 0.5 seconds) and enhances the feeling of natural movement by directly mapping muscle contractions to prosthetic actions.
The students designed this with user feedback and current prosthetic rejection rates in mind, focusing on affordability, portability, and comfort. The device is customisable to individual needs through AI and sensor calibration and prioritises durability, long battery life, and ease of everyday use. This work is a result of the collaborative environment at Ahmedabad University, supported by Professor Maryam Kaveshgar’s mentorship and peer collaboration.
