Literature DB >> 19964581

Slacking by the human motor system: computational models and implications for robotic orthoses.

David J Reinkensmeyer1, O Akoner, Daniel P Ferris, Keith E Gordon.   

Abstract

Recent experimental evidence suggests that a fundamental property of the human motor system is that it "slacks"; that is, that it continuously attempts to decrease levels of muscle activation when movement error is small during repetitive motions. This paper reviews several computational models of slacking, and discusses implications of slacking for the design of robotic orthoses. For therapeutic applications of robotic orthoses, slacking may reduce human effort during rehabilitation training, with negative consequences for use-dependent motor recovery. For assistive applications of robotic orthoses, slacking may allow the motor system to learn to take advantage of force amplification provided by an orthosis, with positive consequences for human energy efficiency.

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Year:  2009        PMID: 19964581     DOI: 10.1109/IEMBS.2009.5333978

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  44 in total

1.  The nature of constant and cyclic force production: unintentional force-drift characteristics.

Authors:  Satyajit Ambike; Daniela Mattos; Vladimir M Zatsiorsky; Mark L Latash
Journal:  Exp Brain Res       Date:  2015-09-29       Impact factor: 1.972

2.  Self-powered robots to reduce motor slacking during upper-extremity rehabilitation: a proof of concept study.

Authors:  Edward P Washabaugh; Emma Treadway; R Brent Gillespie; C David Remy; Chandramouli Krishnan
Journal:  Restor Neurol Neurosci       Date:  2018       Impact factor: 2.406

3.  Sonification and haptic feedback in addition to visual feedback enhances complex motor task learning.

Authors:  Roland Sigrist; Georg Rauter; Laura Marchal-Crespo; Robert Riener; Peter Wolf
Journal:  Exp Brain Res       Date:  2014-12-16       Impact factor: 1.972

4.  Processes underlying unintentional finger-force changes in the absence of visual feedback.

Authors:  Satyajit Ambike; Vladimir M Zatsiorsky; Mark L Latash
Journal:  Exp Brain Res       Date:  2014-11-23       Impact factor: 1.972

5.  Task-specific stability of multifinger steady-state action.

Authors:  Sasha Reschechtko; Vladimir M Zatsiorsky; Mark L Latash
Journal:  J Mot Behav       Date:  2015-01-07       Impact factor: 1.328

Review 6.  Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review.

Authors:  Roland Sigrist; Georg Rauter; Robert Riener; Peter Wolf
Journal:  Psychon Bull Rev       Date:  2013-02

7.  Robotic loading during treadmill training enhances locomotor recovery in rats spinally transected as neonates.

Authors:  Pamela Anne See; Ray D de Leon
Journal:  J Neurophysiol       Date:  2013-05-15       Impact factor: 2.714

8.  Design and Validation of a Lower-Limb Haptic Rehabilitation Robot.

Authors:  Alexander R Dawson-Elli; Peter G Adamczyk
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2020-07       Impact factor: 3.802

9.  The effect of haptic guidance and visual feedback on learning a complex tennis task.

Authors:  Laura Marchal-Crespo; Mark van Raai; Georg Rauter; Peter Wolf; Robert Riener
Journal:  Exp Brain Res       Date:  2013-09-08       Impact factor: 1.972

10.  Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training.

Authors:  Alexander Duschau-Wicke; Andrea Caprez; Robert Riener
Journal:  J Neuroeng Rehabil       Date:  2010-09-10       Impact factor: 4.262

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