Predictors of Step Length from Surface Electromyography and Body Impedance Analysis Parameters
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Jin-Woo | - |
dc.contributor.author | Baek, Seol-Hee | - |
dc.contributor.author | Sung, Joo Hye | - |
dc.contributor.author | Kim, Byung-Jo | - |
dc.date.accessioned | 2022-09-24T01:40:53Z | - |
dc.date.available | 2022-09-24T01:40:53Z | - |
dc.date.created | 2022-09-23 | - |
dc.date.issued | 2022-08 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/143817 | - |
dc.description.abstract | Step length is a critical hallmark of health status. However, few studies have investigated the modifiable factors that may affect step length. An exploratory, cross-sectional study was performed to evaluate the surface electromyography (sEMG) and body impedance analysis (BIA) parameters, combined with individual demographic data, to predict the individual step length using the GAITRite (R) system. Healthy participants aged 40-80 years were prospectively recruited, and three models were built to predict individual step length. The first model was the best-fit model (R-2 = 0.244, p < 0.001); the root mean square (RMS) values at maximal knee flexion and height were included as significant variables. The second model used all candidate variables, except sEMG variables, and revealed that age, height, and body fat mass (BFM) were significant variables for predicting the average step length (R-2 = 0.198, p < 0.001). The third model, which was used to predict step length without sEMG and BIA, showed that only age and height remained significant (R-2 = 0.158, p < 0.001). This study revealed that the RMS value at maximal strength knee flexion, height, age, and BFM are important predictors for individual step length, and possibly suggesting that strengthening knee flexor function and reducing BFM may help improve step length. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.subject | GAIT PERFORMANCE | - |
dc.subject | FAT MASS | - |
dc.subject | WALKING PERFORMANCE | - |
dc.subject | WHOLE-BODY | - |
dc.subject | ADULTS | - |
dc.subject | ACCURACY | - |
dc.subject | STRENGTH | - |
dc.subject | MUSCLE | - |
dc.subject | TRUNK | - |
dc.subject | WOMEN | - |
dc.title | Predictors of Step Length from Surface Electromyography and Body Impedance Analysis Parameters | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Byung-Jo | - |
dc.identifier.doi | 10.3390/s22155686 | - |
dc.identifier.scopusid | 2-s2.0-85136342686 | - |
dc.identifier.wosid | 000839795600001 | - |
dc.identifier.bibliographicCitation | SENSORS, v.22, no.15 | - |
dc.relation.isPartOf | SENSORS | - |
dc.citation.title | SENSORS | - |
dc.citation.volume | 22 | - |
dc.citation.number | 15 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | Y | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.subject.keywordPlus | ACCURACY | - |
dc.subject.keywordPlus | ADULTS | - |
dc.subject.keywordPlus | FAT MASS | - |
dc.subject.keywordPlus | GAIT PERFORMANCE | - |
dc.subject.keywordPlus | MUSCLE | - |
dc.subject.keywordPlus | STRENGTH | - |
dc.subject.keywordPlus | TRUNK | - |
dc.subject.keywordPlus | WALKING PERFORMANCE | - |
dc.subject.keywordPlus | WHOLE-BODY | - |
dc.subject.keywordPlus | WOMEN | - |
dc.subject.keywordAuthor | body impedance analysis | - |
dc.subject.keywordAuthor | step length | - |
dc.subject.keywordAuthor | surface electromyography | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.