Modular one-to-many clutchable actuator for a soft elbow exosuit.

Exoskeletons have been developed for a wide range of applications, from the military to the medical field, with the aim of augmenting human performance or compensating for neuromuscular deficiencies. However, to empower the high number of degrees of freedom of the human body, they often employ a high number of motors, increasing the size, weight and power consumption of the system. We hereby present an actuation strategy to empower our elbow exosuit that adopts a single motor to drive multiple, independently actuated, degrees of freedom. This paradigm, known as One-to-many, is achieved using a modular design where each module comprises a clutchable mechanism that allows to convert a single directional motion from the prime mover to a selectable bidirectional output. Moreover, the mechanism has a locking feature that enables the wearer of the exoskeleton to hold a static load with a minimal power consumption. We present a simple controller for the clutchable unit based on a finite-state machine model, and evaluate its performance for varying input velocities. The system is shown to have a bandwidth of 1.5 Hz, sufficient for daily elbow movements, whilst retaining a compact design.

A synergy-driven approach to a myoelectric hand.

In this paper, we present the Pisa/IIT SoftHand with myoelectric control as a synergy-driven approach for a prosthetic hand. Commercially available myoelectric hands are more expensive, heavier, and less robust than their body-powered counterparts; however, they can offer greater freedom of motion and a more aesthetically pleasing appearance. The Pisa/IIT SoftHand is built on the motor control principle of synergies through which the immense complexity of the hand is simplified into distinct motor patterns. As the SoftHand grasps, it follows a synergistic path with built-in flexibility to allow grasping of a wide variety of objects with a single motor. Here we test, as a proof-of-concept, 4 myoelectric controllers: a standard controller in which the EMG signal is used only as a position reference, an impedance controller that determines both position and stiffness references from the EMG input, a standard controller with vibrotactile force feedback, and finally a combined vibrotactile-impedance (VI) controller. Four healthy subjects tested the control algorithms by grasping various objects. All controllers were sufficient for basic grasping, however the impedance and vibrotactile controllers reduced the physical and cognitive load on the user, while the combined VI mode was the easiest to use of the four. While these results need to be validated with amputees, they suggest a low-cost, robust hand employing hardware-based synergies is a viable alternative to traditional myoelectric prostheses.