Fusing GPS, Activity Monitors, and Self-Report to Improve Assessment of Walking Activity and Community Participation After Stroke.

IF 2.6 3区 医学 Q2 CLINICAL NEUROLOGY
George D Fulk, Karen Klingman, Emily N Peterson
{"title":"Fusing GPS, Activity Monitors, and Self-Report to Improve Assessment of Walking Activity and Community Participation After Stroke.","authors":"George D Fulk, Karen Klingman, Emily N Peterson","doi":"10.1097/NPT.0000000000000518","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and purpose: </strong>Walking and participation in the community are important goals for people post-stroke (PPS). These constructs are challenging to measure given limitations in current data collection methodologies. The purpose of this study was to (1) develop a data fusion approach that combined data from global positioning system (GPS), activity monitor (AM), and daily trip log to identify walking activity and participation in the community, and (2) to examine the construct validity of the data fusion method.</p><p><strong>Methods: </strong>At 60 days post-stroke, PPS wore a GPS and AM and completed a daily trip log for 7 days. Using a combination of a density-based spatial clustering algorithm and geocoding GPS, AM, and daily trip log data were time synched and fused to identify total trips taken outside the home; locations visited per trip; number of steps taken in the home, in the community, at each location visited, and in total. Associations between stroke outcomes and the data fusion metrics were determined to support the construct validity of the data fusion method.</p><p><strong>Results: </strong>Forty-four PPS took a mean of 2,541 steps/day, of which 56% were in the community, and took a mean of 0.39 trips/day outside the home and visited a mean of 0.42 locations. A social visit was the most common reason for going into the community. There were fair associations between number of trips outside the home and gait speed (GS), r = 0.49, Berg Balance Scale (BBS), r = 0.48, modified Rankin Scale (mRS), r = -0.47, and Stroke Impact Scale participation subscale (SIS-P) (0.45). There were moderate associations between steps taken in the community and GS, r = 0.63, BBS, r = 0.51, mRS, r = -0.61, and SIS-P, r = 0.43.</p><p><strong>Discussion and conclusions: </strong>Participants did not often access their community. Fusing GPS, AM, and trip log data may provide a comprehensive method to identify walking activity and community participation in PPS.</p><p><strong>Video abstract available: </strong>for more insights from the authors (see the Video, Supplemental Digital Content, available at: http://links.lww.com/JNPT/A529).</p>","PeriodicalId":49030,"journal":{"name":"Journal of Neurologic Physical Therapy","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neurologic Physical Therapy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/NPT.0000000000000518","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Background and purpose: Walking and participation in the community are important goals for people post-stroke (PPS). These constructs are challenging to measure given limitations in current data collection methodologies. The purpose of this study was to (1) develop a data fusion approach that combined data from global positioning system (GPS), activity monitor (AM), and daily trip log to identify walking activity and participation in the community, and (2) to examine the construct validity of the data fusion method.

Methods: At 60 days post-stroke, PPS wore a GPS and AM and completed a daily trip log for 7 days. Using a combination of a density-based spatial clustering algorithm and geocoding GPS, AM, and daily trip log data were time synched and fused to identify total trips taken outside the home; locations visited per trip; number of steps taken in the home, in the community, at each location visited, and in total. Associations between stroke outcomes and the data fusion metrics were determined to support the construct validity of the data fusion method.

Results: Forty-four PPS took a mean of 2,541 steps/day, of which 56% were in the community, and took a mean of 0.39 trips/day outside the home and visited a mean of 0.42 locations. A social visit was the most common reason for going into the community. There were fair associations between number of trips outside the home and gait speed (GS), r = 0.49, Berg Balance Scale (BBS), r = 0.48, modified Rankin Scale (mRS), r = -0.47, and Stroke Impact Scale participation subscale (SIS-P) (0.45). There were moderate associations between steps taken in the community and GS, r = 0.63, BBS, r = 0.51, mRS, r = -0.61, and SIS-P, r = 0.43.

Discussion and conclusions: Participants did not often access their community. Fusing GPS, AM, and trip log data may provide a comprehensive method to identify walking activity and community participation in PPS.

Video abstract available: for more insights from the authors (see the Video, Supplemental Digital Content, available at: http://links.lww.com/JNPT/A529).

融合GPS、活动监测和自我报告以改善卒中后步行活动和社区参与的评估。
背景与目的:散步和参与社区活动是脑卒中后患者的重要目标。考虑到当前数据收集方法的局限性,这些结构很难测量。本研究的目的是:(1)建立一种结合全球定位系统(GPS)、活动监测仪(AM)和日常出行日志数据的数据融合方法,以识别社区的步行活动和参与情况;(2)检验数据融合方法的构建有效性。方法:在中风后60天,PPS佩戴GPS和AM,完成7天的每日行程记录。结合基于密度的空间聚类算法和地理编码,将GPS、AM和每日旅行日志数据进行时间同步和融合,以确定外出的总行程;每次行程访问的地点;在家里、在社区、在每个访问地点采取的步数,以及总共采取的步数。确定脑卒中结果与数据融合指标之间的关联,以支持数据融合方法的构建有效性。结果:44名PPS平均每天走2541步,其中56%在社区,平均每天走出家门0.39次,平均访问0.42个地点。社交访问是进入社区最常见的原因。出门次数与步态速度(GS) (r = 0.49)、Berg平衡量表(BBS) (r = 0.48)、改良Rankin量表(mRS) (r = -0.47)和卒中影响量表参与子量表(SIS-P)(0.45)之间存在良好的相关性。社区步数与GS (r = 0.63)、BBS (r = 0.51)、mRS (r = -0.61)、SIS-P (r = 0.43)存在中度相关。讨论和结论:参与者不经常访问他们的社区。融合GPS、AM和旅行日志数据可以提供一种综合的方法来识别步行活动和社区参与PPS。视频摘要:更多作者的见解(见视频,补充数字内容,可在:http://links.lww.com/JNPT/A529)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Neurologic Physical Therapy
Journal of Neurologic Physical Therapy CLINICAL NEUROLOGY-REHABILITATION
CiteScore
5.70
自引率
2.60%
发文量
63
审稿时长
>12 weeks
期刊介绍: The Journal of Neurologic Physical Therapy (JNPT) is an indexed resource for dissemination of research-based evidence related to neurologic physical therapy intervention. High standards of quality are maintained through a rigorous, double-blinded, peer-review process and adherence to standards recommended by the International Committee of Medical Journal Editors. With an international editorial board made up of preeminent researchers and clinicians, JNPT publishes articles of global relevance for examination, evaluation, prognosis, intervention, and outcomes for individuals with movement deficits due to neurologic conditions. Through systematic reviews, research articles, case studies, and clinical perspectives, JNPT promotes the integration of evidence into theory, education, research, and practice of neurologic physical therapy, spanning the continuum from pathophysiology to societal participation.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信