More Like this

1. Impact of Haptic Cues and an Active Ankle Exoskeleton on Gait Characteristics

   https://doi.org/10.1177/00187208221113625  

   Wu, Man I. ; Stegall, Paul ; Siu, Ho Chit ; Stirling, Leia ( July 2022 , Human Factors: The Journal of the Human Factors and Ergonomics Society)

   This study examined the interaction of gait-synchronized vibrotactile cues with an active ankle exoskeleton that provides plantarflexion assistance.

   An exoskeleton that augments gait may support collaboration through feedback to the user about the state of the exoskeleton or characteristics of the task.

   Participants ( N = 16) were provided combinations of torque assistance and vibrotactile cues at pre-specified time points in late swing and early stance while walking on a self-paced treadmill. Participants were either given explicit instructions ( N = 8) or were allowed to freely interpret (N=8) how to coordinate with cues.

   For the free interpretation group, the data support an 8% increase in stride length and 14% increase in speed with exoskeleton torque across cue timing, as well as a 5% increase in stride length and 7% increase in speed with only vibrotactile cues. When given explicit instructions, participants modulated speed according to cue timing—increasing speed by 17% at cues in late swing and decreasing speed 11% at cues in early stance compared to no cue when exoskeleton torque was off. When torque was on, participants with explicit instructions had reduced changes in speed.

   These findings support that the presence of torque mitigates how cues were used and highlights the importance of explicit instructions for haptic cuing. Interpreting cues while walking with an exoskeleton may increase cognitive load, influencing overall human-exoskeleton performance for novice users.

   Interactions between haptic feedback and exoskeleton use during gait can inform future feedback designs to support coordination between users and exoskeletons.

    

   more » « less
2. A Novel Control Law for Multi-joint Human-Robot Interaction Tasks While Maintaining Postural Coordination

   Keya Ghonasgi ; Reuth Mirsky ; Adrian M. Haith ; Peter Stone ; Ashish D. Deshpande ( October 2023 , IEEE)

   Exoskeleton robots are capable of safe torque- controlled interactions with a wearer while moving their limbs through pre-defined trajectories. However, affecting and assist- ing 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 m 

   more » « less
3. The Impact of an In-Home Co-Located Robotic Coach in Helping People Make Fewer Exercise Mistakes

   https://doi.org/10.1109/RO-MAN53752.2022.9900722  

   Salomons, Nicole ; Wallenstein, Tom ; Ghose, Debasmita ; Scassellati, Brian ( January 2022 , 31st IEEE International Conference on Robot & Human Interactive Communication)

   Regular exercise provides many mental and physical health benefits. However, when exercises are done incorrectly, it can lead to injuries. Because the COVID-19 pandemic made it challenging to exercise in communal spaces, the growth of virtual fitness programs was accelerated, putting people at risk of sustaining exercise-related injuries as they received little to no feedback on their exercising techniques. Colocated robots could be one potential enhancement to virtual training programs as they can cause higher learning gains, more compliance, and more enjoyment than non-co-located robots. In this study, we compare the effects of a physically present robot by having a person exercise either with a robot (robot condition) or a video of a robot displayed on a tablet (tablet condition). Participants (N=25) had an exercise system in their homes for two weeks. Participants who exercised with the colocated robot made fewer mistakes than those who exercised with the video-displayed robot. Furthermore, participants in the robot condition reported a higher fitness increase and more motivation to exercise than participants in the tablet condition. 

   more » « less
4. Kinematic coordinations capture learning during human–exoskeleton interaction

   https://doi.org/10.1038/s41598-023-35231-3  

   Ghonasgi, Keya ; Mirsky, Reuth ; Bhargava, Nisha ; Haith, Adrian M. ; Stone, Peter ; Deshpande, Ashish D. ( June 2023 , Scientific Reports)

   Human–exoskeleton interactions have the potential to bring about changes in human behavior for physical rehabilitation or skill augmentation. Despite significant advances in the design and control of these robots, their application to human training remains limited. The key obstacles to the design of such training paradigms are the prediction of human–exoskeleton interaction effects and the selection of interaction control to affect human behavior. In this article, we present a method to elucidate behavioral changes in the human–exoskeleton system and identify expert behaviors correlated with a task goal. Specifically, we observe the joint coordinations of the robot, also referred to as kinematic coordination behaviors, that emerge from human–exoskeleton interaction during learning. We demonstrate the use of kinematic coordination behaviors with two task domains through a set of three human-subject studies. We find that participants (1) learn novel tasks within the exoskeleton environment, (2) demonstrate similarity of coordination during successful movements within participants, (3) learn to leverage these coordination behaviors to maximize success within participants, and (4) tend to converge to similar coordinations for a given task strategy across participants. At a high level, we identify task-specific joint coordinations that are used by different experts for a given task goal. These coordinations can be quantified by observing experts and the similarity to these coordinations can act as a measure of learning over the course of training for novices. The observed expert coordinations may further be used in the design of adaptive robot interactions aimed at teaching a participant the expert behaviors.

    

   more » « less
5. Human Trust After Robot Mistakes: Study of the Effects of Different Forms of Robot Communication

   https://doi.org/10.1109/RO-MAN46459.2019.8956424  

   Ye, Sean ; Neville, Glen ; Schrum, Mariah ; Gombolay, Matthew ; Chernova, Sonia ; Howard, Ayanna ( October 2019 , 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN))

   Collaborative robots that work alongside humans will experience service breakdowns and make mistakes. These robotic failures can cause a degradation of trust between the robot and the community being served. A loss of trust may impact whether a user continues to rely on the robot for assistance. In order to improve the teaming capabilities between humans and robots, forms of communication that aid in developing and maintaining trust need to be investigated. In our study, we identify four forms of communication which dictate the timing of information given and type of initiation used by a robot. We investigate the effect that these forms of communication have on trust with and without robot mistakes during a cooperative task. Participants played a memory task game with the help of a humanoid robot that was designed to make mistakes after a certain amount of time passed. The results showed that participants' trust in the robot was better preserved when that robot offered advice only upon request as opposed to when the robot took initiative to give advice. 

   more » « less