Literature DB >> 23366571

A user-driven treadmill control scheme for simulating overground locomotion.

Jonghyun Kim1, Christopher J Stanley, Lindsey A Curatalo, Hyung-Soon Park.   

Abstract

Treadmill-based locomotor training should simulate overground walking as closely as possible for optimal skill transfer. The constant speed of a standard treadmill encourages automaticity rather than engagement and fails to simulate the variable speeds encountered during real-world walking. To address this limitation, this paper proposes a user-driven treadmill velocity control scheme that allows the user to experience natural fluctuations in walking velocity with minimal unwanted inertial force due to acceleration/deceleration of the treadmill belt. A smart estimation limiter in the scheme effectively attenuates the inertial force during velocity changes. The proposed scheme requires measurement of pelvic and swing foot motions, and is developed for a treadmill of typical belt length (1.5 m). The proposed scheme is quantitatively evaluated here with four healthy subjects by comparing it with the most advanced control scheme identified in the literature.

Entities:  

Mesh:

Year:  2012        PMID: 23366571      PMCID: PMC3701800          DOI: 10.1109/EMBC.2012.6346610

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


  10 in total

1.  A feedback-controlled treadmill (treadmill-on-demand) and the spontaneous speed of walking and running in humans.

Authors:  Alberto E Minetti; Lorenzo Boldrini; Laura Brusamolin; Paola Zamparo; Tom McKee
Journal:  J Appl Physiol (1985)       Date:  2003-04-11

2.  A kinematic and kinetic comparison of overground and treadmill walking in healthy subjects.

Authors:  Patrick O Riley; Gabriele Paolini; Ugo Della Croce; Kate W Paylo; D Casey Kerrigan
Journal:  Gait Posture       Date:  2006-08-14       Impact factor: 2.840

3.  The evolution of walking-related outcomes over the first 12 weeks of rehabilitation for incomplete traumatic spinal cord injury: the multicenter randomized Spinal Cord Injury Locomotor Trial.

Authors:  B Dobkin; H Barbeau; D Deforge; J Ditunno; R Elashoff; D Apple; M Basso; A Behrman; S Harkema; M Saulino; M Scott
Journal:  Neurorehabil Neural Repair       Date:  2007 Jan-Feb       Impact factor: 3.919

4.  A Feedback-Controlled Interface for Treadmill Locomotion in Virtual Environments.

Authors:  Lee Lichtenstein; James Barabas; Russell L Woods; Eli Peli
Journal:  ACM Trans Appl Percept       Date:  2007-01       Impact factor: 1.550

5.  An analysis of overground and treadmill sprinting.

Authors:  B A Frishberg
Journal:  Med Sci Sports Exerc       Date:  1983       Impact factor: 5.411

6.  The integrated virtual environment rehabilitation treadmill system.

Authors:  Jeff Feasel; Mary C Whitton; Laura Kassler; Frederick P Brooks; Michael D Lewek
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2011-06       Impact factor: 3.802

7.  Virtual reality for gait training: can it induce motor learning to enhance complex walking and reduce fall risk in patients with Parkinson's disease?

Authors:  Anat Mirelman; Inbal Maidan; Talia Herman; Judith E Deutsch; Nir Giladi; Jeffrey M Hausdorff
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2010-11-24       Impact factor: 6.053

8.  A new approach to retrain gait in stroke patients through body weight support and treadmill stimulation.

Authors:  M Visintin; H Barbeau; N Korner-Bitensky; N E Mayo
Journal:  Stroke       Date:  1998-06       Impact factor: 7.914

9.  A novel method for automatic treadmill speed adaptation.

Authors:  Joachim von Zitzewitz; Michael Bernhardt; Robert Riener
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2007-09       Impact factor: 3.802

10.  Gait rehabilitation with body weight-supported treadmill training for a blast injury survivor with traumatic brain injury.

Authors:  Matthew Scherer
Journal:  Brain Inj       Date:  2007-01       Impact factor: 2.311

  10 in total
  10 in total

1.  Biomechanical Evaluation of Virtual Reality-based Turning on a Self-Paced Linear Treadmill.

Authors:  Keonyoung Oh; Christopher J Stanley; Diane L Damiano; Jonghyun Kim; Jungwon Yoon; Hyung-Soon Park
Journal:  Gait Posture       Date:  2018-07-24       Impact factor: 2.840

2.  Dynamic structure of variability in joint angles and center of mass position during user-driven treadmill walking.

Authors:  Kelley M Kempski; Nicole T Ray; Brian A Knarr; Jill S Higginson
Journal:  Gait Posture       Date:  2019-05-01       Impact factor: 2.840

3.  User-driven control increases cortical activity during treadmill walking: an EEG study.

Authors:  Thomas C Bulea; Diane L Damiano; Christopher J Stanley
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2014

4.  Reliability of a Feedback-Controlled Treadmill Algorithm Dependent on the User's Behavior.

Authors:  Casey Wiens; Will Denton; Molly Schieber; Ryan Hartley; Vivien Marmelat; Sara Myers; Jennifer Yentes
Journal:  IEEE Int Conf Electro Inf Technol       Date:  2017-10-02

5.  Walking speed changes in response to novel user-driven treadmill control.

Authors:  Nicole T Ray; Brian A Knarr; Jill S Higginson
Journal:  J Biomech       Date:  2018-07-29       Impact factor: 2.712

6.  Speed-related but not detrended gait variability increases with more sensitive self-paced treadmill controllers at multiple slopes.

Authors:  Cesar R Castano; Helen J Huang
Journal:  PLoS One       Date:  2021-05-07       Impact factor: 3.240

7.  Prefrontal, posterior parietal and sensorimotor network activity underlying speed control during walking.

Authors:  Thomas C Bulea; Jonghyun Kim; Diane L Damiano; Christopher J Stanley; Hyung-Soon Park
Journal:  Front Hum Neurosci       Date:  2015-05-12       Impact factor: 3.169

8.  Validating attentive locomotion training using interactive treadmill: an fNIRS study.

Authors:  Seunghue Oh; Minsu Song; Jonghyun Kim
Journal:  J Neuroeng Rehabil       Date:  2018-12-20       Impact factor: 4.262

9.  Novel velocity estimation for symmetric and asymmetric self-paced treadmill training.

Authors:  Santiago Canete; Daniel A Jacobs
Journal:  J Neuroeng Rehabil       Date:  2021-02-05       Impact factor: 4.262

10.  Outdoor walking exhibits peak ankle and knee flexion differences compared to fixed and adaptive-speed treadmills in older adults.

Authors:  Sheridan M Parker; Jeremy Crenshaw; Nathaniel H Hunt; Christopher Burcal; Brian A Knarr
Journal:  Biomed Eng Online       Date:  2021-10-15       Impact factor: 2.819

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.