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Joint coordination constraints using an upper limb exoskeleton impact novel skill acquisition.
Keya
Ghonasgi, Reuth Mirsky, Adrian M. Haith, Peter
Stone, and Ashish D. Deshpande.
Wearable Technologies, 2025.
Robotic exoskeletons offer the potential to train novel motor skill acquisitionand thus aid physical rehabilitation. Our prior work demonstrated thatindividuals converge to certain kinematic coordinations as they learn a noveltask. An upper-limb exoskeleton controller that constrains individuals to thisknown coordination was also shown to significantly improve straight-line reachingtask performance. This paper studies the impact of variations of this controlleron novel skill acquisition. We quantify learning under three variations of theintervention (each group with N = 10 participants) against a control group (N =13). Our results show that introducing any constraint during learning can hinderthe learning process, as this alters the task dynamics that lead to success.However, when presented with a personalized constraint, participants still learn.When presented with a task-specific constraint, rather than a personalized one,participants cannot overcome the differences in the training and target task,suggesting exoskeleton-based training interventions should be personalized. Thechanges in kinematic behaviors during learning further suggest that participantsdo not have a statistically consistent performance. While participants respondmore to exoskeleton intervention, others may not respond in short trainingsessions, necessitating further analysis of how strong a response can beencouraged. Our findings emphasize the need for further study of the effects ofexoskeleton intervention for motor training and the potential need forpersonalization.
@Article{Keya_wearable_2025,
author = {Keya Ghonasgi and Reuth Mirsky and Adrian M. Haith and Peter Stone and Ashish D. Deshpande},
title = {Joint coordination constraints using an upper limb exoskeleton impact novel skill acquisition},
journal = {Wearable Technologies},
year = {2025},
abstract = {Robotic exoskeletons offer the potential to train novel motor skill acquisition
and thus aid physical rehabilitation. Our prior work demonstrated that
individuals converge to certain kinematic coordinations as they learn a novel
task. An upper-limb exoskeleton controller that constrains individuals to this
known coordination was also shown to significantly improve straight-line reaching
task performance. This paper studies the impact of variations of this controller
on novel skill acquisition. We quantify learning under three variations of the
intervention (each group with N = 10 participants) against a control group (N =
13). Our results show that introducing any constraint during learning can hinder
the learning process, as this alters the task dynamics that lead to success.
However, when presented with a personalized constraint, participants still learn.
When presented with a task-specific constraint, rather than a personalized one,
participants cannot overcome the differences in the training and target task,
suggesting exoskeleton-based training interventions should be personalized. The
changes in kinematic behaviors during learning further suggest that participants
do not have a statistically consistent performance. While participants respond
more to exoskeleton intervention, others may not respond in short training
sessions, necessitating further analysis of how strong a response can be
encouraged. Our findings emphasize the need for further study of the effects of
exoskeleton intervention for motor training and the potential need for
personalization.
},
}
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