Intuitive movement-based prosthesis control enables arm amputees to reach naturally in virtual reality.

Impressive progress is being made in bionic limbs design and control. Yet, controlling the numerous joints of a prosthetic arm necessary to place the hand at a correct position and orientation to grasp objects remains challenging. Here, we designed an intuitive, movement-based prosthesis control that leverages natural arm coordination to predict distal joints missing in people with transhumeral limb loss based on proximal residual limb motion and knowledge of the movement goal.

Shoulder kinematics plus contextual target information enable control of multiple distal joints of a simulated prosthetic arm and hand.

Background: Prosthetic restoration of reach and grasp function after a trans-humeral amputation requires control of multiple distal degrees of freedom in elbow, wrist and fingers. However, such a high level of amputation reduces the amount of available myoelectric and kinematic information from the residual limb.

Methods: To overcome these limits, we added contextual information about the target's location and orientation such as can now be extracted from gaze tracking by computer vision tools.

Biological Plausibility of Arm Postures Influences the Controllability of Robotic Arm Teleoperation.

Objective: We investigated how participants controlling a humanoid robotic arm's 3D endpoint position by moving their own hand are influenced by the robot's postures. We hypothesized that control would be facilitated (impeded) by biologically plausible (implausible) postures of the robot.

Background: Kinematic redundancy, whereby different arm postures achieve the same goal, is such that a robotic arm or prosthesis could theoretically be controlled with less signals than constitutive joints.

Reachy, a 3D-Printed Human-Like Robotic Arm as a Testbed for Human-Robot Control Strategies.

To this day, despite the increasing motor capability of robotic devices, elaborating efficient control strategies is still a key challenge in the field of humanoid robotic arms. In particular, providing a human "pilot" with efficient ways to drive such a robotic arm requires thorough testing prior to integration into a finished system. Additionally, when it is needed to preserve anatomical consistency between pilot and robot, such testing requires to employ devices showing human-like features.

Performance and Usability of Various Robotic Arm Control Modes from Human Force Signals.

Elaborating an efficient and usable mapping between input commands and output movements is still a key challenge for the design of robotic arm prostheses. In order to address this issue, we present and compare three different control modes, by assessing them in terms of performance as well as general usability. Using an isometric force transducer as the command device, these modes convert the force input signal into either a position or a velocity vector, whose magnitude is linearly or quadratically related to force input magnitude.