Literature DB >> 28642437

Human-in-the-loop optimization of exoskeleton assistance during walking.

Juanjuan Zhang1,2, Pieter Fiers1, Kirby A Witte1, Rachel W Jackson1, Katherine L Poggensee1, Christopher G Atkeson3, Steven H Collins4,3.   

Abstract

Exoskeletons and active prostheses promise to enhance human mobility, but few have succeeded. Optimizing device characteristics on the basis of measured human performance could lead to improved designs. We have developed a method for identifying the exoskeleton assistance that minimizes human energy cost during walking. Optimized torque patterns from an exoskeleton worn on one ankle reduced metabolic energy consumption by 24.2 ± 7.4% compared to no torque. The approach was effective with exoskeletons worn on one or both ankles, during a variety of walking conditions, during running, and when optimizing muscle activity. Finding a good generic assistance pattern, customizing it to individual needs, and helping users learn to take advantage of the device all contributed to improved economy. Optimization methods with these features can substantially improve performance.
Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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Year:  2017        PMID: 28642437     DOI: 10.1126/science.aal5054

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  98 in total

1.  Comparison of the human-exosuit interaction using ankle moment and ankle positive power inspired walking assistance.

Authors:  Martin Grimmer; Brendan T Quinlivan; Sangjun Lee; Philippe Malcolm; Denise Martineli Rossi; Christopher Siviy; Conor J Walsh
Journal:  J Biomech       Date:  2018-11-20       Impact factor: 2.712

2.  Optimizing Exoskeleton Assistance for Faster Self-Selected Walking.

Authors:  Seungmoon Song; Steven H Collins
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2021-05-03       Impact factor: 3.802

3.  Evaluating physiological signal salience for estimating metabolic energy cost from wearable sensors.

Authors:  Kimberly A Ingraham; Daniel P Ferris; C David Remy
Journal:  J Appl Physiol (1985)       Date:  2019-01-10

4.  Interaction between step-to-step variability and metabolic cost of transport during human walking.

Authors:  Chase G Rock; Vivien Marmelat; Jennifer M Yentes; Ka-Chun Siu; Kota Z Takahashi
Journal:  J Exp Biol       Date:  2018-11-12       Impact factor: 3.312

5.  An Untethered Ankle Exoskeleton Improves Walking Economy in a Pilot Study of Individuals With Cerebral Palsy.

Authors:  Zachary F Lerner; Gian Maria Gasparri; Michael O Bair; Jenny L Lawson; Jason Luque; Taryn A Harvey; Andrea T Lerner
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2018-09-17       Impact factor: 3.802

6.  Predicting walking response to ankle exoskeletons using data-driven models.

Authors:  Michael C Rosenberg; Bora S Banjanin; Samuel A Burden; Katherine M Steele
Journal:  J R Soc Interface       Date:  2020-10-14       Impact factor: 4.118

7.  A System for Simple Robotic Walking Assistance With Linear Impulses at the Center of Mass.

Authors:  Arash Mohammadzadeh Gonabadi; Prokopios Antonellis; Philippe Malcolm
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2020-04-27       Impact factor: 3.802

8.  Closing the Loop on Exoskeleton Motor Controllers: Benefits of Regression-Based Open-Loop Control.

Authors:  Greg Orekhov; Jason Luque; Zachary F Lerner
Journal:  IEEE Robot Autom Lett       Date:  2020-07-22

9.  A hinge-free, non-restrictive, lightweight tethered exosuit for knee extension assistance during walking.

Authors:  Evelyn J Park; Tunc Akbas; Asa Eckert-Erdheim; Lizeth H Sloot; Richard W Nuckols; Dorothy Orzel; Lexine Schumm; Terry D Ellis; Louis N Awad; Conor J Walsh
Journal:  IEEE Trans Med Robot Bionics       Date:  2020-04-21

10.  A controller for walking derived from how humans recover from perturbations.

Authors:  Varun Joshi; Manoj Srinivasan
Journal:  J R Soc Interface       Date:  2019-08-14       Impact factor: 4.118

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