Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling

Guillaume Durandau, Dario Farina, Guillermo Asín-Prieto, Iris Dimbwadyo-Terrer, Sergio Lerma-Lara, Jose L. Pons, Juan C. Moreno, Massimo Sartori

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Abstract

Background: Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery. Methods: We have developed a patient-specific computational model of the human musculoskeletal system controlled via neural surrogates, i.e., electromyography-derived neural activations to muscles. The electromyography-driven musculoskeletal model was synthesized into a human-machine interface (HMI) that enabled poststroke and incomplete spinal cord injury patients to voluntarily control multiple joints in a multifunctional robotic exoskeleton in real time. Results: We demonstrated patients' control accuracy across a wide range of lower-extremity motor tasks. Remarkably, an increased level of exoskeleton assistance always resulted in a reduction in both amplitude and variability in muscle activations as well as in the mechanical moments required to perform a motor task. Since small discrepancies in onset time between human limb movement and that of the parallel exoskeleton would potentially increase human neuromuscular effort, these results demonstrate that the developed HMI precisely synchronizes the device actuation with residual voluntary muscle contraction capacity in neurologically impaired patients. Conclusions: Continuous voluntary control of robotic exoskeletons (i.e. event-free and task-independent) has never been demonstrated before in populations with paretic and spastic-like muscle activity, such as those investigated in this study. Our proposed methodology may open new avenues for harnessing residual neuromuscular function in neurologically impaired individuals via symbiotic wearable robots.

Original languageEnglish
Article number91
JournalJournal of neuroengineering and rehabilitation
Volume16
Issue number1
DOIs
Publication statusPublished - 17 Jul 2019

Fingerprint

Paresis
Electromyography
Muscles
Musculoskeletal System
Muscle Spasticity
Muscle Contraction
Spinal Cord Injuries
Lower Extremity
Skeletal Muscle
Extremities
Joints
Exoskeleton Device
Technology
Equipment and Supplies
Research
Population

Keywords

  • Electromyography
  • EMG-driven modeling
  • Neuromechanical modeling
  • Neuromuscular injury
  • Robotic exoskeleton

Cite this

Durandau, Guillaume ; Farina, Dario ; Asín-Prieto, Guillermo ; Dimbwadyo-Terrer, Iris ; Lerma-Lara, Sergio ; Pons, Jose L. ; Moreno, Juan C. ; Sartori, Massimo. / Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling. In: Journal of neuroengineering and rehabilitation. 2019 ; Vol. 16, No. 1.
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Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling. / Durandau, Guillaume; Farina, Dario; Asín-Prieto, Guillermo; Dimbwadyo-Terrer, Iris; Lerma-Lara, Sergio; Pons, Jose L.; Moreno, Juan C.; Sartori, Massimo.

In: Journal of neuroengineering and rehabilitation, Vol. 16, No. 1, 91, 17.07.2019.

Research output: Contribution to journalArticleAcademicpeer-review

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T1 - Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling

AU - Durandau, Guillaume

AU - Farina, Dario

AU - Asín-Prieto, Guillermo

AU - Dimbwadyo-Terrer, Iris

AU - Lerma-Lara, Sergio

AU - Pons, Jose L.

AU - Moreno, Juan C.

AU - Sartori, Massimo

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AB - Background: Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery. Methods: We have developed a patient-specific computational model of the human musculoskeletal system controlled via neural surrogates, i.e., electromyography-derived neural activations to muscles. The electromyography-driven musculoskeletal model was synthesized into a human-machine interface (HMI) that enabled poststroke and incomplete spinal cord injury patients to voluntarily control multiple joints in a multifunctional robotic exoskeleton in real time. Results: We demonstrated patients' control accuracy across a wide range of lower-extremity motor tasks. Remarkably, an increased level of exoskeleton assistance always resulted in a reduction in both amplitude and variability in muscle activations as well as in the mechanical moments required to perform a motor task. Since small discrepancies in onset time between human limb movement and that of the parallel exoskeleton would potentially increase human neuromuscular effort, these results demonstrate that the developed HMI precisely synchronizes the device actuation with residual voluntary muscle contraction capacity in neurologically impaired patients. Conclusions: Continuous voluntary control of robotic exoskeletons (i.e. event-free and task-independent) has never been demonstrated before in populations with paretic and spastic-like muscle activity, such as those investigated in this study. Our proposed methodology may open new avenues for harnessing residual neuromuscular function in neurologically impaired individuals via symbiotic wearable robots.

KW - Electromyography

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