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

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, August 2012
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141 Mendeley
Title
A novel walking speed estimation scheme and its application to treadmill control for gait rehabilitation.
Published in
Journal of NeuroEngineering and Rehabilitation, August 2012
DOI 10.1186/1743-0003-9-62
Pubmed ID
Authors

Yoon J, Park HS, Damiano DL

Abstract

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.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 141 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Czechia 1 <1%
Austria 1 <1%
Italy 1 <1%
Netherlands 1 <1%
Spain 1 <1%
United States 1 <1%
Luxembourg 1 <1%
Unknown 132 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 35 25%
Student > Ph. D. Student 33 23%
Student > Bachelor 15 11%
Student > Doctoral Student 12 9%
Researcher 10 7%
Other 25 18%
Unknown 11 8%
Readers by discipline Count As %
Engineering 46 33%
Medicine and Dentistry 25 18%
Nursing and Health Professions 9 6%
Sports and Recreations 8 6%
Social Sciences 7 5%
Other 27 19%
Unknown 19 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 May 2013.
All research outputs
#3,078,091
of 4,507,211 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#255
of 336 outputs
Outputs of similar age
#61,066
of 89,291 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#18
of 23 outputs
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So far Altmetric has tracked 336 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
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