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. This control was validated on 29 participants, including seven with above-elbow limb loss, who picked and placed bottles in a wide range of locations in virtual reality, with median success rates over 99% and movement times identical to those of natural movements. This control also enabled 15 participants, including three with limb differences, to reach and grasp real objects with a robotic arm operated according to the same principle. Remarkably, this was achieved without any prior training, indicating that this control is intuitive and instantaneously usable. It could be used for phantom limb pain management in virtual reality, or to augment the reaching capabilities of invasive neural interfaces usually more focused on hand and grasp control.

A guide to inter-joint coordination characterization for discrete movements: a comparative study.

Characterizing human movement is essential for understanding movement disorders, evaluating progress in rehabilitation, or even analyzing how a person adapts to the use of assistive devices. Thanks to the improvement of motion capture technology, recording human movement has become increasingly accessible and easier to conduct. Over the last few years, multiple methods have been proposed for characterizing inter-joint coordination. Despite this, there is no real consensus regarding how these different inter-joint coordination metrics should be applied when analyzing the coordination of discrete movement from kinematic data. In this work, we consider 12 coordination metrics identified from the literature and apply them to a simulated dataset based on reaching movements using two degrees of freedom. Each metric is evaluated according to eight criteria based on current understanding of human motor control physiology, i.e, each metric is graded on how well it fulfills each of these criteria. This comparative analysis highlights that no single inter-joint coordination metric can be considered as ideal. Depending on the movement characteristics that one seeks to understand, one or several metrics among those reviewed here may be pertinent in data analysis. We propose four main factors when choosing a metric (or a group of metrics): the importance of temporal vs. spatial coordination, the need for result explainability, the size of the dataset, and the computational resources. As a result, this study shows that extracting the relevant characteristics of inter-joint coordination is a scientific challenge and requires a methodical choice. As this preliminary study is conducted on a limited dataset, a more comprehensive analysis, introducing more variability, could be complementary to these results.

Human Exteroception during Object Handling with an Upper Limb Exoskeleton.

Upper limb exoskeletons may confer significant mechanical advantages across a range of tasks. The potential consequences of the exoskeleton upon the user's sensorimotor capacities however, remain poorly understood. The purpose of this study was to examine how the physical coupling of the user's arm to an upper limb exoskeleton influenced the perception of handheld objects. In the experimental protocol, participants were required to estimate the length of a series of bars held in their dominant right hand, in the absence of visual feedback. Their performance in conditions with an exoskeleton fixed to the forearm and upper arm was compared to conditions without the upper limb exoskeleton. Experiment 1 was designed to verify the effects of attaching an exoskeleton to the upper limb, with object handling limited to rotations of the wrist only. Experiment 2 was designed to verify the effects of the structure, and its mass, with combined movements of the wrist, elbow, and shoulder. Statistical analysis indicated that movements performed with the exoskeleton did not significantly affect perception of the handheld object in experiment 1 (BF01 = 2.3) or experiment 2 (BF01 = 4.3). These findings suggest that while the integration of an exoskeleton complexifies the architecture of the upper limb effector, this does not necessarily impede transmission of the mechanical information required for human exteroception.