Dynamic Adaptation of Robotic Ankle-Foot Prostheses to Compliant Terrain: Reacting to Surface Stiffness Changes in Real-Time.

Real-time adaptability to varying terrain stiffness is a critical factor in enhancing the functionality of robotic ankle-foot prostheses. This paper introduces a novel reactive control framework that classifies surface stiffness and adjusts the prosthesis' behavior in real-time on compliant terrain, utilizing kinematic data from the prosthesis. The framework is tested with three able-bodied participants who completed treadmill walking trials on simulated rigid and compliant surfaces, replicating typical real-life scenarios. The proposed framework employs a Support Vector Machine (SVM) classifier that leverages data such as ankle angle, ankle moment, and In-ertial Measurement Unit (IMU) measurements from a powered prosthesis to differentiate between terrains of different stiffness. Results show a classification accuracy of up to 88%, while the classification process is streamlined for rapid decision-making, enabling surface adaptation within milliseconds of initial foot-ground contact. This approach represents a significant step toward creating responsive, user-centric assistive technologies for individuals with lower-limb amputation.