02646nas a2200313 4500008004100000022001400041245012900055210006900184260001000253300001400263490000600277520158700283653002901870653001501899653001701914653002801931653003701959653002201996653001102018653002102029653001102050653002302061653002202084100002102106700002202127700001802149700002602167856013902193 2024 eng d a2377-376600aExperimental and Simulation-Based Estimation of Interface Power During Physical Human-Robot Interaction in Hand Exoskeletons0 aExperimental and SimulationBased Estimation of Interface Power D cMarch a2575-25810 v93 a

Even the best wearable robots face challenges with power losses in the system, especially at the physical attachment interface. While some sources for power loss are inherent to the system, such as human soft tissue or musculoskeletal joint damping, other sources such as soft padding materials and bias strap forces can be modulated to optimize interface power transmission. Few methods currently exist for estimating power loss at physical human-robot interfaces, especially for upper-body exoskeletons. This letter presents a novel method to estimate interface power from experimental data in a wearable hand device, along with a simulation model for predicting interaction behavior by incorporating viscoelastic properties at the attachment interface. The experimental method is implemented with the Maestro hand exoskeleton, and repeatability of the interface power estimation is confirmed with pilot human testing. Simulation results are compared with experimental estimation of interface power, showing agreement of trends and validating the use of a simulation model to predict physical human-robot interaction behavior. These findings highlight the advantages of multi-body simulations as a tool to perform modular, inexpensive, and predictive investigations in physical human-robot interaction, without affecting the real-world mechatronic system or hindering the subject's safety. The proposed tools for experimental estimation of interface power and simulation modeling can optimize the design and control of robots for seamless integration with the human body.

10adesign and human factors10aEstimation10aExoskeletons10ahuman-centered robotics10aPhysical human-robot interaction10aPower measurement10aRobots10aSea measurements10aTorque10aTorque measurement10awearable robotics1 aYousaf, Saad, N.1 aMukherjee, Gaurav1 aKing, Raymond1 aDeshpande, Ashish, D. uhttps://reneu.robotics.utexas.edu/experimental-and-simulation-based-estimation-interface-power-during-physical-human-robot-interaction02761nas a2200301 4500008004100000022001400041245010800055210006900163260000800232300001200240490000700252520175000259653002102009653002902030653001702059653002502076653001502101653001902116653003402135653002602169653002802195653002602223653002402249653001302273100002502286700002602311856012202337 2023 eng d a2168-230500aAssessment of Upper-Body Movement Quality in the Cartesian-Space is Feasible in the Harmony Exoskeleton0 aAssessment of UpperBody Movement Quality in the CartesianSpace i cDec a985-9950 v533 a

To determine the most effective interventions for poststroke patients, it is imperative to monitor the recovery process. Robotic exoskeletons' built-in sensing capabilities enable accurate kinematic measurement with no additional setup time. Although position sensors used in exoskeletons are accurate, a mismatch between the robot's and the human's joints can lead to inaccurate measurements. In addition, the robot's residual dynamics can interfere with human's natural movements and the kinematic metrics assessed in the robot would not be representative of the human's movement in free-motion. So far, the accuracy of robotic exoskeletons in assessing upper-body kinematics has not been verified. The bilateral upper-body Harmony exoskeleton has features favorable to minimize joint misalignments and the robot's residual dynamics. In this study, we examined Harmony's ability to accurately assess Cartesian-space kinematic parameters associated with the wearer's movement quality. We analyzed data collected from eight healthy participants that executed point-to-point movements with and without the presence of the robot and at fast and slow speeds. Ground truth was acquired with an optical motion capture, and we extracted the kinematic parameters from the measured data. The results suggest that Harmony can accurately measure kinematic parameters associated with movement quality, and these parameters could appropriately reflect wearer's natural movements at a slow speed. Therefore, Harmony could aid the evaluation of the effectiveness of different interventions, which is more sensitive and efficient than currently adopted clinical outcomes. This allows for individualization of a treatment plan and a detailed follow-up.

10aAssistive robots10aAtmospheric measurements10aExoskeletons10aKinematic assessment10aKinematics10aMotion capture10aOptical variables measurement10aParticle measurements10arehabilitation robotics10aRobot sensing systems10arobotic exoskeleton10aTraining1 aDe Oliveira, Ana, C.1 aDeshpande, Ashish, D. uhttps://reneu.robotics.utexas.edu/assessment-upper-body-movement-quality-cartesian-space-feasible-harmony-exoskeleton02640nas a2200241 4500008004100000245012300041210006900164260000800233520175800241653001301999653001702012653002602029653001702055653002402072653002702096653002602123100002002149700002602169700001802195700002602213700002702239856013202266 2023 eng d00aCharacterizing the Onset and Offset of Motor Imagery During Passive Arm Movements Induced by an Upper-Body Exoskeleton0 aCharacterizing the Onset and Offset of Motor Imagery During Pass cOct3 a

Two distinct technologies have gained attention lately due to their prospects for motor rehabilitation: robotics and brain-machine interfaces (BMIs). Harnessing their combined efforts is a largely uncharted and promising direction that has immense clinical potential. However, a significant challenge is whether motor intentions from the user can be accurately detected using non-invasive BMIs in the presence of instrumental noise and passive movements induced by the rehabilitation exoskeleton. As an alternative to the straight-forward continuous control approach, this study instead aims to characterize the onset and offset of motor imagery during passive arm movements induced by an upper-body exoskeleton to allow for the natural control (initiation and termination) of functional movements. Ten participants were recruited to perform kinesthetic motor imagery (MI) of the right arm while attached to the robot, simultaneously cued with LEDs indicating the initiation and termination of a goal-oriented reaching task. Using electroencephalogram signals, we built a decoder to detect the transition between i) rest and beginning MI and ii) maintaining and ending MI. Offline decoder evaluation achieved group average onset accuracy of 60.7% and 66.6% for offset accuracy, revealing that the start and stop of MI could be identified while attached to the robot. Furthermore, pseudo-online evaluation could replicate this performance, forecasting reliable online exoskeleton control in the future. Our approach showed that participants could produce quality and reliable sensorimotor rhythms regardless of noise or passive arm movements induced by wearing the exoskeleton, which opens new possibilities for BMI control of assistive devices.

10aDecoding10aExoskeletons10aLight emitting diodes10aManipulators10aNeurorehabilitation10aPerformance evaluation10aRobot sensing systems1 aMitra, Kanishka1 aRacz, Frigyes, Samuel1 aKumar, Satyam1 aDeshpande, Ashish, D.1 aMillán, José, Del R. uhttps://reneu.robotics.utexas.edu/characterizing-onset-and-offset-motor-imagery-during-passive-arm-movements-induced-upper-body02318nas a2200277 4500008004100000245009800041210006900139260000900208520139900217653001601616653001701632653001001649653001901659653001201678653002501690653003401715653001501749653002501764653002001789653001801809100002101827700002101848700002601869700002301895856012201918 2023 eng d00aAn Extended Virtual Proxy Haptic Algorithm for Dexterous Manipulation in Virtual Environments0 aExtended Virtual Proxy Haptic Algorithm for Dexterous Manipulati cJuly3 a

With the evolution of hand-based haptic interfaces, novel forms of controlled force feedback arise allowing multipoint interaction between virtual objects and the hand’s digits. With these advances, there must be an effective force display coupled with an intuitive visualization of the hand at its points of high manipulability. This is the basis for dexterous manipulation immersion in virtual environments. Still, there are challenges due to the complexity of force interaction, bandwidth limitations, and redundant visual configurations. In this paper, we present an extended proxy algorithm for digit-based interactions, which through configuration-based optimization, provides an efficient, robust, and visually plausible way to interact with virtual objects with a virtual hand. Additionally, we revisit a seldom-seen modality of haptic rendering, whole-hand kinesthetic feedback, with the Maestro exoskeleton in the implementation of our algorithm. We unify these methods and develop a CHAI3D module in a comprehensive visuo-haptic framework that was evaluated through demonstrations of joint-level haptic force data during interaction with static and dynamic objects alike. Our computationally-efficient approach sets the foundation for the visual display of in-hand virtual object manipulation with the effective rendering of stable haptic interactions under complex tasks.

10aExoskeleton10aExoskeletons10aForce10aForce feedback10aHaptics10aHeuristic algorithms10aRendering (computer graphics)10aSimulation10aVirtual environments10aVirtual Reality10aVisualization1 aGalvan, Aldo, F.1 aRamirez, Job, D.1 aDeshpande, Ashish, D.1 aFey, Ann, Majewicz uhttps://reneu.robotics.utexas.edu/extended-virtual-proxy-haptic-algorithm-dexterous-manipulation-virtual-environments02379nas 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