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Project # 36
Neo-Limb: Adaptive Socket Intelligence
| Team Lead: | Isaiah Perry |
| Other Team Members: | Jerome Dales | Alejandra Rosas | Hannah Huggins | Aric White | Hemshankar Laugi |
| Faculty Advisor(s): | Young-Tae Kim |
| Department: | BE |
| Project Type: | REU |
| Title: | Neo-Limb: Adaptive Socket Intelligence |
| Abstract: | Neo-Limb: Adaptive Socket Intelligence is an AI-powered prosthetic socket system designed to dynamically respond to the changing shape and pressure distribution of a residual limb. Traditional prosthetic sockets are rigid and static, often relying on manual adjustments that only modify overall diameter. However, residual limbs are much more complex and experience daily volume fluctuations due to activity, temperature, and fluid shifts. These inconsistencies can lead to discomfort, skin breakdown, and reduced mobility. Neo-Limb addresses this limitation through an embedded network of pressure sensors and micro-adjustment mechanisms that adapt regionally, not uniformly, across the socket interface. By collecting real-time biomechanical data and a little bit of help from intelligent algorithms, we aim to optimize pressure distribution and maintain a secure, personalized fit throughout the day. This localized adaptability improves comfort, enhances stability, and reduces the need for frequent refitting appointments. The long-term vision of Neo-Limb is to redefine the human to prosthetic connection by transforming passive prosthetic components into responsive, data-driven systems. By integrating adaptive hardware with machine learning capabilities, Neo-Limb aims to improve user confidence, mobility, and quality of life while advancing the next generation of intelligent assistive technologies. |
| Poster: | View Poster #36 (PDF) |
| Judges Scoring: | Submit Evaluation (judges only) |