Regression models for the quantification of Parkinsonian bradykinesia
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Ji-Won | - |
dc.contributor.author | Kwon, Yuri | - |
dc.contributor.author | Yun, Ju-Seok | - |
dc.contributor.author | Heo, Jae-Hoon | - |
dc.contributor.author | Eom, Gwang-Moon | - |
dc.contributor.author | Tack, Gye-Rae | - |
dc.contributor.author | Lim, Tae-Hong | - |
dc.contributor.author | Koh, Seong-Beom | - |
dc.date.accessioned | 2021-09-05T00:58:04Z | - |
dc.date.available | 2021-09-05T00:58:04Z | - |
dc.date.created | 2021-06-15 | - |
dc.date.issued | 2015 | - |
dc.identifier.issn | 0959-2989 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/96217 | - |
dc.description.abstract | The aim of this study was to develop regression models for the quantification of parkinsonian bradykinesia. Forty patients with Parkinson's disease participated in this study. Angular velocity was measured using gyro sensor during finger tapping, forearm-rotation, and toe tapping tasks and the severity of bradykinesia was rated by two independent neurologists. Various characteristic variables were derived from the sensor signal. Stepwise multiple linear regression analysis was performed to develop models predicting the bradykinesia score with the characteristic variables as input. To evaluate the ability of the regression models to discriminate different bradykinesia scores, ANOVA and post hoc test were performed. Major determinants of the bradykinesia score differed among clinical tasks and between raters. The regression models were better than any single characteristic variable in terms of the ability to differentiate bradykinesia scores. Specifically, the regression models could differentiate all pairs of the bradykinesia scores (p<0.05) except for one pair in the finger tapping task and one pair in the toe tapping task. In contrast, any single characteristic variable was found not sensitive enough to discriminate many of the pairs, especially in case of the toe tapping task. The results suggest that the multiple regression models reflecting these differences would be beneficial for the quantification of bradykinesia because the cardinal features included in the determination of bradykinesia score differ among tasks as well as among the raters. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IOS PRESS | - |
dc.subject | DEEP BRAIN-STIMULATION | - |
dc.subject | FINE MOTOR | - |
dc.subject | DISEASE | - |
dc.subject | IMPROVEMENT | - |
dc.subject | MOVEMENTS | - |
dc.subject | AMPLITUDE | - |
dc.subject | SPEED | - |
dc.subject | LIMB | - |
dc.title | Regression models for the quantification of Parkinsonian bradykinesia | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Koh, Seong-Beom | - |
dc.identifier.doi | 10.3233/BME-151531 | - |
dc.identifier.scopusid | 2-s2.0-84979093685 | - |
dc.identifier.wosid | 000360012700028 | - |
dc.identifier.bibliographicCitation | BIO-MEDICAL MATERIALS AND ENGINEERING, v.26, pp.S2249 - S2258 | - |
dc.relation.isPartOf | BIO-MEDICAL MATERIALS AND ENGINEERING | - |
dc.citation.title | BIO-MEDICAL MATERIALS AND ENGINEERING | - |
dc.citation.volume | 26 | - |
dc.citation.startPage | S2249 | - |
dc.citation.endPage | S2258 | - |
dc.type.rims | ART | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Materials Science | - |
dc.relation.journalWebOfScienceCategory | Engineering, Biomedical | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Biomaterials | - |
dc.subject.keywordPlus | DEEP BRAIN-STIMULATION | - |
dc.subject.keywordPlus | FINE MOTOR | - |
dc.subject.keywordPlus | DISEASE | - |
dc.subject.keywordPlus | IMPROVEMENT | - |
dc.subject.keywordPlus | MOVEMENTS | - |
dc.subject.keywordPlus | AMPLITUDE | - |
dc.subject.keywordPlus | SPEED | - |
dc.subject.keywordPlus | LIMB | - |
dc.subject.keywordAuthor | Bradykinesia | - |
dc.subject.keywordAuthor | quantification | - |
dc.subject.keywordAuthor | stepwise multiple regression | - |
dc.subject.keywordAuthor | Parkinson&apos | - |
dc.subject.keywordAuthor | s disease | - |
dc.subject.keywordAuthor | clinical rating | - |
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.