Active Ankle–Foot Orthosis Design and Computer Simulation with Multi-Objective Parameter Optimization

There are many current active orthosis designs to assist with disabilities related to foot-drop, with most of them intervening during the whole gait cycle. We propose that, for the treatment of foot-drop, it is possible to design an ankle–foot device that will assist a walking user only during the dorsiflexion stages of the gait, avoiding interference with other stages, by using a single actuator with a simple transmission and a suspension block. This design can be improved by the use of multi-objective optimization to obtain a static set of parameters that are applicable to varying initial conditions. We present a computer simulation study of an active ankle–foot orthosis design, based on the interaction of a cam and lever with a suspension block, with the objective of assisting only with dorsiflexion during the gait cycle, leaving the rest of the movements unimpeded while reducing the complexity and weight of the device. This design is validated using a full simulation environment that includes the movements of the lower leg and foot, as they interact with our device and a ground element. As part of the design and validation, we found sets of mechanical and control parameters that provoke adequate output behavior of the orthosis to help the wearer perform a moderate-speed, normal gait. To optimize the design, we proposed three objectives to warrant ankle angle accuracy, minimal oscillations, and low energy consumption. A set of solutions was obtained with multi-objective optimization algorithms NSGA-II and RVEA to tune the parameters of the active orthosis. The solutions set from RVEA resulted in lower mean and standard deviation values for the oscillations and energy objectives in comparison to the solutions from NSGA-II, while for the MSE objective, NSGA-II obtained lower mean and standard deviation; for the energy consumption objective, the mean score using RVEA is 17% less than with NSGA-II. The orthosis is shown to be robust to differences in initial ankle angles. We observed that it is possible to obtain a broad set of solutions with a good performance during the gait cycle in controlled spaces and that in this application, the RVEA algorithm results in a better option for optimization to balance the objectives.