Control and Implementation of a Fluidic Elastomer Actuator for Active Suppression of Hand Tremor

Active exoskeletons for tremor suppression show potential for treatment of pathological tremor thanks to their non-invasive nature. However, the active force was only used for the voluntary movement following. As a potential alternative, fluidic elastomer actuators (FEAs) possess compliance and flexibility that is important for wearable devices. In this study, we introduce the control implementation for a FEA to the application of active suppression of hand tremor, which allows a wearable FEA actively exerting force on the finger against tremor and meanwhile following the voluntary motion. The proposed pressure control algorithm could push the closed-loop pressure control to 19 Hz cutoff frequency. A combination neural network of GRU-MLP (Gated Recurrent Unit-Multilayer Perceptron) was proposed to identify and control a fiber-reinforced FEA following the voluntary movement of hand. The active tremor suppression effectiveness of the proposed method was tested on a bench-top tremor simulator, and such method could suppress the hand tremor from the original amplitude of more than 5° to less than 1°. The proposed method paves a new way for tremor suppression exoskeletons.