Gait augmentation through co-adaptation
Gait augmentation through co-adaptation
The foot and ankle play an important role during human gait, forming a dynamic link between the body and the ground, and hereby continuously adjusting their alignment and function to achieve the desirable movement. Assistive technology for gait such as footwear, ankle-foot orthoses, or prosthetic devices, could be used to support, augment or imitate the foot-ankle system to a user’s maximum. However, despite all innovations, the effectiveness of current state-of-the-art assistive technology stays behind expectations.
A method that could address present challenges and improve the efficacy of assistive technology for gait is human-in-the-loop optimization. During human-in-the-loop optimization, the human is included ‘in vivo’ in the iterative optimization loop and device parameters are systematically varied during the optimization process using an intelligent optimization algorithm in response to measured performance. The objective of the current thesis of Thijs Tankink is to explore human-in-the-loop optimization protocols for enhancing gait performance through a number of assistive technologies, spanning from individually optimized footwear to prosthetic ankle-foot devices.
We demonstrated that optimal device settings differ substantially between individuals, while even small differences in settings can already affect gait performance on an individual level. This highlights the need to tune assistive technology to the individual end-user. Human-in-the-loop optimization can identify optimal device settings while fostering motor learning, enabling co-adaptation between the user and device to augment gait performance. Although clinical feasibility remains questionable in its present state, current limitations could be addressed, and human-in-the-loop optimization has the potential to enhance the effectiveness of state-of-the-art assistive gait technology.