New Algorithm Enhances Robotic Prosthetics for Amputee Mobility

Researchers from North Carolina State University and the University of North Carolina at Chapel Hill have unveiled a groundbreaking algorithm aimed at enhancing the functionality of robotic prosthetics. This innovative approach not only optimizes the movement of prosthetic limbs but also assists users in maintaining a natural walking pattern, a significant development in addressing health issues related to amputations.

The study, published in the journal IEEE Transactions on Robotics, details how this new algorithm combines dual processes to personalize robotic prosthetic devices. According to Varun Nalam, co-lead and co-corresponding author, this method represents a shift from previous designs that focused solely on replicating the movement of the missing joint. “When people have an amputation above the knee, it affects the way they move other parts of their body,” explains Nalam, an assistant research professor in the Lampe Joint Department of Biomedical Engineering. He notes that these changes can lead to complications such as lower back pain and hip problems.

Improving Mobility for Amputees

The primary goal of this research was to develop an algorithm that ensures the prosthetic knee functions effectively while also promoting natural bodily movements. “This not only gives the user the full range of leg motion but will also help to avoid lower back pain and hip problems,” Nalam adds.

The research builds on previous work that introduced an intelligent system designed to “tune” powered prosthetic knees. This earlier system enabled patients to walk comfortably within minutes, a process that typically required hours of adjustment by a trained clinician. Helen Huang, the senior author of the paper and the Jackson Family Distinguished Professor of Biomedical Engineering, states that the previous work focused exclusively on the prosthetic’s behavior. The new algorithm, however, utilizes inverse reinforcement learning to consider the movements of both the prosthetic limb and the user.

Testing and Results

To validate the effectiveness of the new approach, the researchers enlisted five study participants, two of whom had undergone above-the-knee amputations. Each participant performed tasks using the robotic prosthetic knee under two different conditions: one using the existing knee control software and the other employing the new dual-algorithm system.

The results were promising. Incorporating the new algorithm improved the hip range of motion for all participants, indicating a potential enhancement in hip health. “We also found that the new algorithm changed the gait of our study subjects in ways which indicate that movement felt more natural for users,” Nalam reports. Notably, participants took longer strides when walking, a sign of improved mobility.

Looking ahead, the researchers aim to collaborate with clinicians to assess the long-term effects of the new algorithm on user well-being. They are also interested in partnering with robotic prosthetic manufacturers to explore integrating this approach into existing software frameworks.

From a research perspective, Nalam expresses interest in expanding the application of this algorithm to address various human locomotive behaviors, potentially revolutionizing the field of prosthetics. The integration of technology and human biomechanics could pave the way for more effective solutions in aiding amputees, enhancing their quality of life significantly.