Structural Optimization of a Passive ExoNET for Forearm Supination

Impairments in forearm supination are a common consequence of stroke, impeding essential activities of daily living and hand-object interactions. To address this, we present a forearm ExoNET-a novel, passive, wearable device designed to both assist and improve forearm supination for stroke survivors...

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Published inIEEE International Conference on Rehabilitation Robotics Vol. 2025; pp. 1779 - 1786
Main Authors Wilson, Valentino, Ryali, Partha, OShea, Leah, Srivatsa, Adith, Camardo, Mac, Celian, Courtney, Patton, James L.
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.05.2025
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ISSN1945-7901
1945-7901
DOI10.1109/ICORR66766.2025.11063006

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Abstract Impairments in forearm supination are a common consequence of stroke, impeding essential activities of daily living and hand-object interactions. To address this, we present a forearm ExoNET-a novel, passive, wearable device designed to both assist and improve forearm supination for stroke survivors and others with movement deficits by generating clinician-defined, multijoint torque patterns using elastic actuators. Guided by torque deficit measurements from a custom-designed diagnostic device and driven by a mathematical model and structural optimization algorithm, the forearm ExoNET can be customized in real time to meet individual needs, providing configurations that deliver both assistive and therapeutic applied torque fields. Initial results demonstrate that the diagnostic device effectively identifies supination torque deficits in stroke survivors, while the optimization algorithm achieves strong predictive accuracy (R 2 =0.987) in designing ExoNET configurations to countract these deficits. These findings underscore the forearm ExoNET's potential to support active supination across the full range of motion, offering a lowcost, accessible solution with significant promise for improving upper-limb rehabilitation outcomes.
AbstractList Impairments in forearm supination are a common consequence of stroke, impeding essential activities of daily living and hand-object interactions. To address this, we present a forearm ExoNET-a novel, passive, wearable device designed to both assist and improve forearm supination for stroke survivors and others with movement deficits by generating clinician-defined, multijoint torque patterns using elastic actuators. Guided by torque deficit measurements from a custom-designed diagnostic device and driven by a mathematical model and structural optimization algorithm, the forearm ExoNET can be customized in real time to meet individual needs, providing configurations that deliver both assistive and therapeutic applied torque fields. Initial results demonstrate that the diagnostic device effectively identifies supination torque deficits in stroke survivors, while the optimization algorithm achieves strong predictive accuracy (R =0.987) in designing ExoNET configurations to countract these deficits. These findings underscore the forearm ExoNET's potential to support active supination across the full range of motion, offering a lowcost, accessible solution with significant promise for improving upper-limb rehabilitation outcomes.
Impairments in forearm supination are a common consequence of stroke, impeding essential activities of daily living and hand-object interactions. To address this, we present a forearm ExoNET-a novel, passive, wearable device designed to both assist and improve forearm supination for stroke survivors and others with movement deficits by generating clinician-defined, multijoint torque patterns using elastic actuators. Guided by torque deficit measurements from a custom-designed diagnostic device and driven by a mathematical model and structural optimization algorithm, the forearm ExoNET can be customized in real time to meet individual needs, providing configurations that deliver both assistive and therapeutic applied torque fields. Initial results demonstrate that the diagnostic device effectively identifies supination torque deficits in stroke survivors, while the optimization algorithm achieves strong predictive accuracy (R2=0.987) in designing ExoNET configurations to countract these deficits. These findings underscore the forearm ExoNET's potential to support active supination across the full range of motion, offering a lowcost, accessible solution with significant promise for improving upper-limb rehabilitation outcomes.Impairments in forearm supination are a common consequence of stroke, impeding essential activities of daily living and hand-object interactions. To address this, we present a forearm ExoNET-a novel, passive, wearable device designed to both assist and improve forearm supination for stroke survivors and others with movement deficits by generating clinician-defined, multijoint torque patterns using elastic actuators. Guided by torque deficit measurements from a custom-designed diagnostic device and driven by a mathematical model and structural optimization algorithm, the forearm ExoNET can be customized in real time to meet individual needs, providing configurations that deliver both assistive and therapeutic applied torque fields. Initial results demonstrate that the diagnostic device effectively identifies supination torque deficits in stroke survivors, while the optimization algorithm achieves strong predictive accuracy (R2=0.987) in designing ExoNET configurations to countract these deficits. These findings underscore the forearm ExoNET's potential to support active supination across the full range of motion, offering a lowcost, accessible solution with significant promise for improving upper-limb rehabilitation outcomes.
Impairments in forearm supination are a common consequence of stroke, impeding essential activities of daily living and hand-object interactions. To address this, we present a forearm ExoNET-a novel, passive, wearable device designed to both assist and improve forearm supination for stroke survivors and others with movement deficits by generating clinician-defined, multijoint torque patterns using elastic actuators. Guided by torque deficit measurements from a custom-designed diagnostic device and driven by a mathematical model and structural optimization algorithm, the forearm ExoNET can be customized in real time to meet individual needs, providing configurations that deliver both assistive and therapeutic applied torque fields. Initial results demonstrate that the diagnostic device effectively identifies supination torque deficits in stroke survivors, while the optimization algorithm achieves strong predictive accuracy (R 2 =0.987) in designing ExoNET configurations to countract these deficits. These findings underscore the forearm ExoNET's potential to support active supination across the full range of motion, offering a lowcost, accessible solution with significant promise for improving upper-limb rehabilitation outcomes.
Author Celian, Courtney
Wilson, Valentino
Camardo, Mac
Patton, James L.
Ryali, Partha
OShea, Leah
Srivatsa, Adith
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Snippet Impairments in forearm supination are a common consequence of stroke, impeding essential activities of daily living and hand-object interactions. To address...
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SubjectTerms Actuators
Adult
Algorithms
Biomechanical Phenomena
Equipment Design
Female
Forearm - physiology
Forearm - physiopathology
Humans
Male
Middle Aged
Optimization
Prediction algorithms
Safety
Stroke (medical condition)
Stroke Rehabilitation - instrumentation
Supination - physiology
Time measurement
Torque
Torque measurement
Usability
Wearable devices
Wearable Electronic Devices
Title Structural Optimization of a Passive ExoNET for Forearm Supination
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