A Virtual Reality-Cycling Training System for Lower Limb Balance Improvement.
Stroke survivors might lose their walking and balancing abilities, but many studies pointed out that cycling is an effective means for lower limb rehabilitation. However, during cycle training, the unaffected limb tends to compensate for the affected one, which resulted in suboptimal rehabilitation....
| Published in: | BioMed Research International Vol. 2016; pp. 1 - 11 |
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| Main Authors: | , , , , |
| Format: | equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
3/6/2016
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=113511678&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 113511678 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 3/6/2016 vid: 2016 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 113511678 113511678 113511678 10.1155/2016/9276508 113511678 ppf: 1 ppct: 10 formats: fmt: @attributes: type: P tig: atl: A Virtual Reality-Cycling Training System for Lower Limb Balance Improvement. aug: au: Yin, Chieh Hsueh, Ya-Hsin Yeh, Chun-Yu Lo, Hsin-Chang Lan, Yi-Ting affil: Department of Electronic Engineering, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan sug: subj: Virtual Reality Methods Cycling Lower Extremity Balance Training, Physical Methods Stroke Rehabilitation Human Descriptive Statistics Questionnaires Data Analysis Software P-Value Paired T-Tests Male Female Middle Age Aged Adult Taiwan Pretest-Posttest Design Funding Source Middle Aged: 45-64 years Aged: 65+ years Adult: 19-44 years Male Female ab: Stroke survivors might lose their walking and balancing abilities, but many studies pointed out that cycling is an effective means for lower limb rehabilitation. However, during cycle training, the unaffected limb tends to compensate for the affected one, which resulted in suboptimal rehabilitation. To address this issue, we present a Virtual Reality-Cycling Training System (VRCTS), which senses the cycling force and speed in real-time, analyzes the acquired data to produce feedback to patients with a controllable VR car in a VR rehabilitation program, and thus specifically trains the affected side. The aim of the study was to verify the functionality of the VRCTS and to verify the results from the ten stroke patients participants and to compare the result of Asymmetry Ratio Index (ARI) between the experimental group and the control group, after their training, by using the bilateral pedal force and force plate to determine any training effect. The results showed that after the VRCTS training in bilateral pedal force it had improved by 0.22 (p=0.046) and in force plate the stand balance has also improved by 0.29 (p=0.031); thus both methods show the significant difference. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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