Soft actuation and sensing towards robot-assisted facial rehabilitation

Continuing research efforts in robot-assisted rehabilitation demand more adaptable and inherently soft wearable devices. A wearable rehabilitative device is required to follow the motion of the body and to provide assistive or corrective motions to restore natural movements. Providing the required level of fluidity in wearable devices becomes a challenge for rehabilitation of more sensitive and fragile body parts, such as the face. To address this challenge, we propose a soft actuation method based on a tendon-driven robotic origami (robogami) and a soft sensing method based on a strain gauge with customized stretchable mesh design. The proposed actuation and sensing methods are compatible with the requirements in a facial rehabilitative device. The conformity of robogamis originates from their multiple and redundant degrees of freedom and the controllability of the joint stiffness, which is provided by adjusting the elasticity modulus of an embedded shape memory polymer (SMP) layer. The reconfiguration of the robogami and the trajectory and directional compliance of its end-effector are controlled by modulating the temperatures, hence the stiffness, of the SMP layers. Here we demonstrate this correlation using simulation and experimental results. In this paper, we introduce a thin and highly compliant sensing method for measuring facial movements with a minimal effect on the natural motions. The measurements of the sensors on the healthy side can be used to calculate the required tendon displacement for replicating the natural motion on the paralyzed side of the face in patients suffering from facial palsy.