2020 42nd Annual International Conference of the IEEE Engineering in Medicine &Amp; Biology Society (EMBC) 2020
DOI: 10.1109/embc44109.2020.9176109
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A Computational Internal Model to Quantify the Effect of Sensorimotor Augmentation on Motor Output

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Cited by 3 publications
(4 citation statements)
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“…To address the sensory loss and the ensuing balance problem, multiple motor augmentation approaches have been actively investigated, including exoskeletal assistance or functional electrical stimulation (FES) ( Kim et al, 2012 ; Chen et al, 2013 ). However, both exoskeleton and FES approaches apply corrective efforts directly to the motor output and bypass the central nervous system (CNS) ( Dollahon et al, 2020 ). The minimal involvement of the CNS may critically limit the neural reorganization necessary for balance enhancement.…”
Section: Introductionmentioning
confidence: 99%
“…To address the sensory loss and the ensuing balance problem, multiple motor augmentation approaches have been actively investigated, including exoskeletal assistance or functional electrical stimulation (FES) ( Kim et al, 2012 ; Chen et al, 2013 ). However, both exoskeleton and FES approaches apply corrective efforts directly to the motor output and bypass the central nervous system (CNS) ( Dollahon et al, 2020 ). The minimal involvement of the CNS may critically limit the neural reorganization necessary for balance enhancement.…”
Section: Introductionmentioning
confidence: 99%
“…As described in the internal model (Fig. 2) presented in our prior work [29], which was developed based on previous internal models [30], [31], both interaction gain (k) and sensory gain (β) can increase sensory feedback on the fingertip corresponding to the pinch. Therefore, the interaction gain (k) is likely to affect the closed-loop motor control performance as well as sensory feedback.…”
Section: Introductionmentioning
confidence: 99%
“…Note that the gain (k) can be adjusted simply by modulating the surface profile or parameters below the fingertips during a pinch, whose effect on the finger control is investigated and compared with the model-based understanding. [30], [31], with a new component called interaction gain (yellow highlighted) to consider the environmental interaction [29].…”
Section: Introductionmentioning
confidence: 99%
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