Estimating anatomical wrist joint motion with a robotic exoskeleton

Abstract

Abstract-Robotic exoskeletons can provide the high intensity, long duration targeted therapeutic interventions required for regaining motor function lost as a result of neurological injury. Quantitative measurements by exoskeletons have been proposed as measures of rehabilitative outcomes. Exoskeletons, in contrast to end effector designs, have the potential to provide a direct mapping between human and robot joints. This mapping rests on the assumption that anatomical axes and robot axes are aligned well, and that movement within the exoskeleton is negligible. These assumptions hold well for simple one degree-of-freedom joints, but may not be valid for multiarticular joints with unique musculoskeletal properties such as the wrist. This paper presents an experiment comparing robot joint kinematic measurements from an exoskeleton to anatomical joint angles measured with a motion capture system. Joint-space position measurements and task-space smoothness metrics were compared between the two measurement modalities. The experimental results quantify the error between joint-level position measurements, and show that exoskeleton kinematic measurements preserve smoothness characteristics found in anatomical measures of wrist movements.

Design and characterization of the OpenWrist: A robotic wrist exoskeleton for coordinated hand-wrist rehabilitation

“…While not discussed in this paper, the OpenWrist was further characterized and validated in two separate subject studies involving wrist pointing tasks. The effects of the OpenWrist's dynamic properties on movement smoothness during wrist pointing tasks are characterized in [22], while wrist pointing trajectories as recorded by robot encoders and passive marker motion capture are compared in [23].…”

A Review on Design of Upper Limb Exoskeletons

“…The complex relative movements between the radial and ulna bones make it difficult to develop a mechanism which can precisely replicate the forearm supination/pronation. Few studies [6,22,33,34,50,58,70,72,167] have presented a design that can actively support the users in executing forearm supination/pronation by taking into account the effect of radial/ulnar deviation.…”

Assessing Wrist Movement With Robotic Devices

“…As expected, direction affected A sum and A net , but the variability of A net values likely prevented the difference from being significant. There was a significant main effect of target for each metric (ρ: χ 2 (7) = 41.11, p < .001; SAL:χ 2 (7) = 91.56, p < .001; A sum : χ 2 (7) = 162.22, p < .001; A net :χ 2 (7) = 89.14, p < .001), which follows commentary that the pointing distance of a percentage of ROM made some targets more difficult than others [35].…”

“…1) Task Description: The task consisted of pointing movements starting from a center, near neutral, position to one of eight outbound targets, displayed on a circle whose radius corresponded to a constant percentage (60%) of wrist ROM [38] as detailed in prior work [35]. After reaching and remaining inside a target for one second, subjects would return to the center target, as seen in Fig.…”

“…1b), which are then used to determine human joint angles. Joint angles are either approximated via a least-squares calibration [20], [35] (Section III and IV), or trigonometry [33] (Section V). The calibration takes the difference between the orientation of two rigid bodies, (in this case, the forearm and hand) in the world frame to estimate the axes of rotation based on single DOF calibration movements.…”