Rose, Chad G.Kann, Claudia K.Deshpande, Ashish D.O’Malley, Marcia K.2018-01-252018-01-252017Rose, Chad G., Kann, Claudia K., Deshpande, Ashish D., et al.. "Estimating anatomical wrist joint motion with a robotic exoskeleton." <i>2017 International Conference on Rehabilitation Robotics (ICORR),</i> (2017) IEEE: 1437-1442. https://doi.org/10.1109/ICORR.2017.8009450.https://hdl.handle.net/1911/99248Robotic 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 multi-articular 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.engThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IEEE.Journal articleRose_Estimating_ICORR_199https://doi.org/10.1109/ICORR.2017.8009450