02379nas a2200241 4500008004100000245011000041210006900151260000800220520153900228653002401767653001701791653002801808653002101836653001201857653001301869653001501882100001901897700001801916700002201934700001701956700002601973856013801999 2023 eng d00aA Novel Control Law for Multi-Joint Human-Robot Interaction Tasks While Maintaining Postural Coordination0 aNovel Control Law for MultiJoint HumanRobot Interaction Tasks Wh cOct3 a

Exoskeleton robots are capable of safe torque-controlled interactions with a wearer while moving their limbs through predefined trajectories. However, affecting and assisting the wearer's movements while incorporating their inputs (effort and movements) effectively during an interaction re-mains an open problem due to the complex and variable nature of human motion. In this paper, we present a control algorithm that leverages task-specific movement behaviors to control robot torques during unstructured interactions by implementing a force field that imposes a desired joint angle coordination behavior. This control law, built by using principal component analysis (PCA), is implemented and tested with the Harmony exoskeleton. We show that the proposed control law is versatile enough to allow for the imposition of different coordination behaviors with varying levels of impedance stiffness. We also test the feasibility of our method for unstructured human-robot interaction. Specifically, we demonstrate that participants in a human-subject experiment are able to effectively perform reaching tasks while the exoskeleton imposes the desired joint coordination under different movement speeds and interaction modes. Survey results further suggest that the proposed control law may offer a reduction in cognitive or motor effort. This control law opens up the possibility of using the exoskeleton for training the participating in accomplishing complex multi-joint motor tasks while maintaining postural coordination.

10aBehavioral sciences10aExoskeletons10aHuman-robot interaction10aRobot kinematics10aSurveys10aTraining10aTrajectory1 aGhonasgi, Keya1 aMirsky, Reuth1 aHaith, Adrian, M.1 aStone, Peter1 aDeshpande, Ashish, D. uhttps://reneu.robotics.utexas.edu/novel-control-law-multi-joint-human-robot-interaction-tasks-while-maintaining-postural-coordination02483nas a2200265 4500008004100000245008700041210006900128260000900197520162200206653001701828653002001845653002101865653002201886653002101908653001301929653001301942100002101955700002501976700001902001700001802020700002002038700001902058700002602077856011402103 2022 eng d00aImpact of Gravity Compensation on Upper Extremity Movements in Harmony Exoskeleton0 aImpact of Gravity Compensation on Upper Extremity Movements in H cJuly3 a

Robots have been used to offset the limb weight through gravity compensation in upper body rehabilitation to delineate the effects of loss of strength and loss of dexterity, which are two common forms of post-stroke impairments. In this paper, we explored the impact of this anti-gravity support on the quality of movement during reaching and coordinated arm movements in a pilot study with two participants with chronic stroke. The subjects donned the Harmony exoskeleton which supported proper shoulder coordination in addition to providing gravity compensation. Participants had previously taken part in seven one-hour sessions with the Harmony exoskeleton, performing six sets of passive-stretching and active exercises. Pre- and post-training sessions included assessments of two separate tasks, planar reaching and a set of six coordinated arm movements, in two conditions, outside of and supported by the exoskeleton. The movements were recorded using an optical motion capture system and analyzed using spectral arc length (SPARC) and straight line deviation to quantify movement smoothness and quality. We observed that gravity compensation resulted in an increased smoothness for the subject with high level of impairment whereas compensation resulted in a reduction in smoothness for the subject with low level of impairment in the reaching task. Both participants demonstrated better coordination of the shoulder-arm joint with gravity compensation. This result motivates further studies into the role of gravity compensation during coordinated movement training and rehabilitation interventions.

10aExoskeletons10aNeural pathways10aOptical feedback10aOptical recording10aRobot kinematics10aShoulder10aTraining1 aHailey, Rhet, O.1 aDe Oliveira, Ana, C.1 aGhonasgi, Keya1 aWhitford, Bob1 aLee, Robert, K.1 aRose, Chad, G.1 aDeshpande, Ashish, D. uhttps://reneu.robotics.utexas.edu/impact-gravity-compensation-upper-extremity-movements-harmony-exoskeleton-001991nas a2200241 4500008004100000245008800041210006900129260000800198520119100206653002901397653001701426653001001443653002801453653002401481653001501505653001301520100001901533700001801552700002201570700001701592700002601609856011401635 2022 eng d00aQuantifying Changes in Kinematic Behavior of a Human-Exoskeleton Interactive System0 aQuantifying Changes in Kinematic Behavior of a HumanExoskeleton  cOct3 a

While human-robot interaction studies are becoming more common, quantification of the effects of repeated interaction with an exoskeleton remains unexplored. We draw upon existing literature in human skill assessment and present extrinsic and intrinsic performance metrics that quantify how the human-exoskeleton system's behavior changes over time. Specifically, in this paper, we present a new performance metric that provides insight into the system's kinematics associated with ‘successful’ movements resulting in a richer characterization of changes in the system's behavior. A human subject study is carried out wherein participants learn to play a challenging and dynamic reaching game over multiple attempts, while donning an upper-body exoskeleton. The results demonstrate that repeated practice results in learning over time as identified through the improvement of extrinsic performance. Changes in the newly developed kinematics-based measure further illumi-nate how the participant's intrinsic behavior is altered over the training period. Thus, we are able to quantify the changes in the human-exoskeleton system's behavior observed in relation with learning.

10aAtmospheric measurements10aExoskeletons10aGames10aHuman-robot interaction10aInteractive systems10aKinematics10aTraining1 aGhonasgi, Keya1 aMirsky, Reuth1 aHaith, Adrian, M.1 aStone, Peter1 aDeshpande, Ashish, D. uhttps://reneu.robotics.utexas.edu/quantifying-changes-kinematic-behavior-human-exoskeleton-interactive-system