A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation

<p>Abstract</p> <p>Background</p> <p>Virtual reality (VR) technology along with treadmill training (TT) can effectively provide goal-oriented practice and promote improved motor learning in patients with neurological disorders. Moreover, the VR + TT scheme may enhance c...

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Main Authors: Yoon Jungwon, Park Hyung-Soon, Damiano Diane
Format: Article
Language:English
Published: BMC 2012-08-01
Series:Journal of NeuroEngineering and Rehabilitation
Subjects:
Online Access:http://www.jneuroengrehab.com/content/9/1/62
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spelling doaj-b75eff081ce947b09e3e22d25e8495712020-11-24T21:04:44ZengBMCJournal of NeuroEngineering and Rehabilitation1743-00032012-08-01916210.1186/1743-0003-9-62A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitationYoon JungwonPark Hyung-SoonDamiano Diane<p>Abstract</p> <p>Background</p> <p>Virtual reality (VR) technology along with treadmill training (TT) can effectively provide goal-oriented practice and promote improved motor learning in patients with neurological disorders. Moreover, the VR + TT scheme may enhance cognitive engagement for more effective gait rehabilitation and greater transfer to over ground walking. For this purpose, we developed an individualized treadmill controller with a novel speed estimation scheme using swing foot velocity, which can enable user-driven treadmill walking (UDW) to more closely simulate over ground walking (OGW) during treadmill training. OGW involves a cyclic acceleration-deceleration profile of pelvic velocity that contrasts with typical treadmill-driven walking (TDW), which constrains a person to walk at a preset constant speed. In this study, we investigated the effects of the proposed speed adaptation controller by analyzing the gait kinematics of UDW and TDW, which were compared to those of OGW at three pre-determined velocities.</p> <p>Methods</p> <p>Ten healthy subjects were asked to walk in each mode (TDW, UDW, and OGW) at three pre-determined speeds (0.5 m/s, 1.0 m/s, and 1.5 m/s) with real time feedback provided through visual displays. Temporal-spatial gait data and 3D pelvic kinematics were analyzed and comparisons were made between UDW on a treadmill, TDW, and OGW.</p> <p>Results</p> <p>The observed step length, cadence, and walk ratio defined as the ratio of stride length to cadence were not significantly different between UDW and TDW. Additionally, the average magnitude of pelvic acceleration peak values along the anterior-posterior direction for each step and the associated standard deviations (variability) were not significantly different between the two modalities. The differences between OGW and UDW and TDW were mainly in swing time and cadence, as have been reported previously. Also, step lengths between OGW and TDW were different for 0.5 m/s and 1.5 m/s gait velocities, and walk ratio between OGS and UDW was different for 1.0 m/s gait velocities.</p> <p>Conclusions</p> <p>Our treadmill control scheme implements similar gait biomechanics of TDW, which has been used for repetitive gait training in a small and constrained space as well as controlled and safe environments. These results reveal that users can walk as stably during UDW as TDW and employ similar strategies to maintain walking speed in both UDW and TDW. Furthermore, since UDW can allow a user to actively participate in the virtual reality (VR) applications with variable walking velocity, it can induce more cognitive activities during the training with VR, which may enhance motor learning effects.</p> http://www.jneuroengrehab.com/content/9/1/62Body-weight supported treadmill trainingWalking velocity estimationSelf-selected treadmill speed controlGait analysisTemporal-spatial gait parameters
collection DOAJ
language English
format Article
sources DOAJ
author Yoon Jungwon
Park Hyung-Soon
Damiano Diane
spellingShingle Yoon Jungwon
Park Hyung-Soon
Damiano Diane
A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation
Journal of NeuroEngineering and Rehabilitation
Body-weight supported treadmill training
Walking velocity estimation
Self-selected treadmill speed control
Gait analysis
Temporal-spatial gait parameters
author_facet Yoon Jungwon
Park Hyung-Soon
Damiano Diane
author_sort Yoon Jungwon
title A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation
title_short A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation
title_full A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation
title_fullStr A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation
title_full_unstemmed A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation
title_sort novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation
publisher BMC
series Journal of NeuroEngineering and Rehabilitation
issn 1743-0003
publishDate 2012-08-01
description <p>Abstract</p> <p>Background</p> <p>Virtual reality (VR) technology along with treadmill training (TT) can effectively provide goal-oriented practice and promote improved motor learning in patients with neurological disorders. Moreover, the VR + TT scheme may enhance cognitive engagement for more effective gait rehabilitation and greater transfer to over ground walking. For this purpose, we developed an individualized treadmill controller with a novel speed estimation scheme using swing foot velocity, which can enable user-driven treadmill walking (UDW) to more closely simulate over ground walking (OGW) during treadmill training. OGW involves a cyclic acceleration-deceleration profile of pelvic velocity that contrasts with typical treadmill-driven walking (TDW), which constrains a person to walk at a preset constant speed. In this study, we investigated the effects of the proposed speed adaptation controller by analyzing the gait kinematics of UDW and TDW, which were compared to those of OGW at three pre-determined velocities.</p> <p>Methods</p> <p>Ten healthy subjects were asked to walk in each mode (TDW, UDW, and OGW) at three pre-determined speeds (0.5 m/s, 1.0 m/s, and 1.5 m/s) with real time feedback provided through visual displays. Temporal-spatial gait data and 3D pelvic kinematics were analyzed and comparisons were made between UDW on a treadmill, TDW, and OGW.</p> <p>Results</p> <p>The observed step length, cadence, and walk ratio defined as the ratio of stride length to cadence were not significantly different between UDW and TDW. Additionally, the average magnitude of pelvic acceleration peak values along the anterior-posterior direction for each step and the associated standard deviations (variability) were not significantly different between the two modalities. The differences between OGW and UDW and TDW were mainly in swing time and cadence, as have been reported previously. Also, step lengths between OGW and TDW were different for 0.5 m/s and 1.5 m/s gait velocities, and walk ratio between OGS and UDW was different for 1.0 m/s gait velocities.</p> <p>Conclusions</p> <p>Our treadmill control scheme implements similar gait biomechanics of TDW, which has been used for repetitive gait training in a small and constrained space as well as controlled and safe environments. These results reveal that users can walk as stably during UDW as TDW and employ similar strategies to maintain walking speed in both UDW and TDW. Furthermore, since UDW can allow a user to actively participate in the virtual reality (VR) applications with variable walking velocity, it can induce more cognitive activities during the training with VR, which may enhance motor learning effects.</p>
topic Body-weight supported treadmill training
Walking velocity estimation
Self-selected treadmill speed control
Gait analysis
Temporal-spatial gait parameters
url http://www.jneuroengrehab.com/content/9/1/62
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