A wearable ankle robot prototype for assistance to foot drop is presented in this work. This device is built with soft and hard materials and employs one inertial sensor. First, the ankle robot uses a high-level method, developed with a Bayesian formulation, for recognition of walking activities and gait periods. Second, a low-level method, with a proportional-integral-derivative controller (PID), controls the wearable device to operate in assistive and transparent modes. In an assistive mode, activated by the toe-off detection, the wearable device assists the human foot in dorsiflexion orientation to reduce the effect of foot drop abnormality. In a transparent mode, activated by the heel-contact detection, the robot device follows the movements performed by the human foot. The wearable prototype is validated with experiments, in simulation and real-time modes, for recognition of walking activity and control of assistive and transparent modes during walking. Experiments achieved 99.87% and 99.20% accuracies for recognition of walking activity and gait periods. Results also show the ability of the wearable robot to operate according to the gait period recognised during walking. Overall, this work offers a wearable robot prototype with the potential to assist the human foot during walking, which is important to allow subjects to recover their confidence and quality of life.
|Name||IEEE International Conference on Systems, Man, and Cybernetics|
|Conference||2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC)|
|Period||6/10/19 → 9/10/19|
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Human-Computer Interaction