Mohamed Abdelbar, Sigurður Brynjólfsson, Kristín Briem, Atli Örn Sverrisson and Christophe Lecomte
Active lower-limb prostheses that generate net positive work can enhance the mobility and function of individuals with lower limb amputation by enabling more natural and efficient walking compared to passive devices. Finding a balance between adaptability for unexpected or non-standard movements and repeatability for cyclic standard movements is a known control challenge for active lower-limb prostheses. Ankle angle, ankle torque, ankle power, and ankle peak power were the parameters investigated in this research to assess the feasibility, effectiveness, and perception of a robotic ankle-foot prosthesis hybrid controller.
A volitional controller electromyography (EMG)-driven musculoskeletal model was combined with a non-volitional finite-state machine impedance controller. The Gastrocnemius muscle and Tibialis Anterior muscle were modeled using a Hill-type muscle model to function around an ankle joint. The system uses input from ankle sensors as well as EMG data from antagonist muscle pairs to activate the muscle models. In addition, muscle parameters within the model are optimized to improve the neuromuscular model controller’s performance and responsiveness.
In an initial study, biological ankle characteristics for various activities, including walking, ramps, and stairs, were comparable to measured ankle characteristics such as ankle angle, torque, and power. The proposed hybrid controller, based on the study, may achieve the desired results for a variety of tasks.
By integrating volitional and non-volitional control, the controller may enhance functionality and provide prosthetic users with a more intuitive and comfortable experience. Furthermore, the research shows that using neural signals as control signals for prosthetic limb controllers is both possible and desired.
