• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

使用 Fitbit 设备监测缺血性脑卒中患者的身体活动:前瞻性队列可行性研究。

Physical Activity Monitoring Using a Fitbit Device in Ischemic Stroke Patients: Prospective Cohort Feasibility Study.

机构信息

Neurological Institute Center for Outcomes Research and Evaluation, Cleveland Clinic, Cleveland, OH, United States.

Cerebrovascular Center, Cleveland Clinic, Cleveland, OH, United States.

出版信息

JMIR Mhealth Uhealth. 2021 Jan 19;9(1):e14494. doi: 10.2196/14494.

DOI:10.2196/14494
PMID:33464213
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7854036/
Abstract

BACKGROUND

Continuous tracking of ambulatory activity in real-world settings using step activity monitors has many potential uses. However, feasibility, accuracy, and correlation with performance measures in stroke patients have not been well-established.

OBJECTIVE

The primary study objective was to determine adherence with wearing a consumer-grade step activity monitor, the Fitbit Charge HR, in home-going ischemic stroke patients during the first 90 days after hospital discharge. Secondary objectives were to (1) determine accuracy of step counts of the Fitbit Charge HR compared with a manual tally; (2) calculate correlations between the Fitbit step counts and the mobility performance scores at discharge and 30 days after stroke; (3) determine variability and change in weekly step counts over 90 days; and (4) evaluate patient experience with using the Fitbit Charge HR poststroke.

METHODS

A total of 15 participants with recent mild ischemic stroke wore a Fitbit Charge HR for 90 days after discharge and completed 3 mobility performance tests from the National Institutes of Health Toolbox at discharge and Day 30: (1) Standing Balance Test, (2) 2-Minute Walk Endurance Test, and (3) 4-Meter Walk Gait Speed Test. Accuracy of step activity monitors was assessed by calculating differences in steps recorded on the step activity monitor and a manual tally during 2-minute walk tests.

RESULTS

Participants had a mean age of 54 years and a median modified Rankin scale score of 1. Mean daily adherence with step activity monitor use was 83.6%. Mean daily step count in the first week after discharge was 4376. Daily step counts increased slightly during the first 30 days after discharge (average increase of 52.5 steps/day; 95% CI 32.2-71.8) and remained stable during the 30-90 day period after discharge. Mean step count difference between step activity monitor and manual tally was -4.8 steps (-1.8%). Intraclass correlation coefficients for step counts and 2-minute walk, standing balance, and 4-meter gait speed at discharge were 0.41 (95% CI -0.14 to 0.75), -0.12 (95% CI -0.67 to 0.64), and 0.17 (95% CI -0.46 to 0.66), respectively. Values were similarly poor at 30 days.

CONCLUSIONS

The use of consumer-grade Fitbit Charge HR in patients with recent mild stroke is feasible with reasonable adherence and accuracy. There was poor correlation between step counts and gait speed, balance, and endurance. Further research is needed to evaluate the association between step counts and other outcomes relevant to patients, including patient-reported outcomes and measures of physical function.

摘要

背景

在真实环境中使用计步器连续跟踪日常活动有许多潜在用途。然而,在中风患者中,其可行性、准确性以及与性能测量的相关性尚未得到很好的证实。

目的

主要研究目的是确定在出院后 90 天内,居家缺血性中风患者佩戴消费级计步器 Fitbit Charge HR 的依从性。次要目的是:(1)确定 Fitbit Charge HR 的计步准确性与手动计数的差异;(2)计算 Fitbit 计步与出院时和中风后 30 天的移动性能评分之间的相关性;(3)确定 90 天内每周计步数的变化和差异;(4)评估中风后患者使用 Fitbit Charge HR 的体验。

方法

共 15 名近期轻度缺血性中风患者出院后佩戴 Fitbit Charge HR 90 天,并在出院和第 30 天完成了国家卫生研究院工具包中的 3 项移动性能测试:(1)站立平衡测试;(2)2 分钟步行耐力测试;(3)4 米步行速度测试。通过计算在 2 分钟步行测试期间计步器和手动计数记录的步数之间的差异来评估计步器的准确性。

结果

参与者的平均年龄为 54 岁,中位改良 Rankin 量表评分为 1 分。平均每日的计步器使用率为 83.6%。出院后第一周的平均每日步数为 4376 步。出院后 30 天内,每日步数略有增加(平均每天增加 52.5 步;95%CI 32.2-71.8),出院后 30-90 天期间保持稳定。计步器与手动计数之间的平均步数差异为-4.8 步(-1.8%)。出院时,计步与 2 分钟步行、站立平衡和 4 米步态速度之间的组内相关系数分别为 0.41(95%CI-0.14 至 0.75)、-0.12(95%CI-0.67 至 0.64)和 0.17(95%CI-0.46 至 0.66)。30 天时的数值也同样较差。

结论

在近期轻度中风患者中使用消费级 Fitbit Charge HR 是可行的,具有合理的依从性和准确性。计步与步态速度、平衡和耐力之间相关性较差。需要进一步研究以评估计步与其他与患者相关的结果之间的关联,包括患者报告的结果和身体功能的测量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55ab/7854036/5f90392aa2fb/mhealth_v9i1e14494_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55ab/7854036/35aa9fd52621/mhealth_v9i1e14494_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55ab/7854036/8cc78f63061a/mhealth_v9i1e14494_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55ab/7854036/5f90392aa2fb/mhealth_v9i1e14494_fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55ab/7854036/35aa9fd52621/mhealth_v9i1e14494_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55ab/7854036/8cc78f63061a/mhealth_v9i1e14494_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55ab/7854036/5f90392aa2fb/mhealth_v9i1e14494_fig3.jpg

相似文献

1
Physical Activity Monitoring Using a Fitbit Device in Ischemic Stroke Patients: Prospective Cohort Feasibility Study.使用 Fitbit 设备监测缺血性脑卒中患者的身体活动:前瞻性队列可行性研究。
JMIR Mhealth Uhealth. 2021 Jan 19;9(1):e14494. doi: 10.2196/14494.
2
Formative Evaluation of Consumer-Grade Activity Monitors Worn by Older Adults: Test-Retest Reliability and Criterion Validity of Step Counts.老年人佩戴的消费级活动监测器的形成性评估:步数的重测信度和效标效度。
JMIR Form Res. 2020 Aug 18;4(8):e16537. doi: 10.2196/16537.
3
Validation of Fitbit-Flex as a measure of free-living physical activity in a community-based phase III cardiac rehabilitation population.验证Fitbit-Flex作为基于社区的三期心脏康复人群日常身体活动测量工具的有效性。
Eur J Prev Cardiol. 2016 Sep;23(14):1476-85. doi: 10.1177/2047487316634883. Epub 2016 Feb 23.
4
Accuracy of step count measured by physical activity monitors: The effect of gait speed and anatomical placement site.通过身体活动监测器测量步数的准确性:步态速度和解剖学放置部位的影响。
Gait Posture. 2017 Sep;57:199-203. doi: 10.1016/j.gaitpost.2017.06.012. Epub 2017 Jun 21.
5
Validity of Different Activity Monitors to Count Steps in an Inpatient Rehabilitation Setting.不同活动监测器在住院康复环境中计数步数的有效性。
Phys Ther. 2017 May 1;97(5):581-588. doi: 10.1093/ptj/pzx010.
6
Step count accuracy and reliability of two activity tracking devices in people after stroke.两种活动追踪设备在中风患者中的步数计数准确性和可靠性。
Physiother Theory Pract. 2017 Oct;33(10):788-796. doi: 10.1080/09593985.2017.1354412. Epub 2017 Aug 4.
7
Accuracy of 2 activity monitors in detecting steps in people with stroke and traumatic brain injury.两种活动监测器在检测脑卒中及颅脑损伤患者步数方面的准确性。
Phys Ther. 2014 Feb;94(2):222-9. doi: 10.2522/ptj.20120525. Epub 2013 Sep 19.
8
The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study.自由生活条件下佩戴的消费者级活动监测器在健康成年人中的有效性:一项横断面研究。
Int J Behav Nutr Phys Act. 2015 Mar 27;12:42. doi: 10.1186/s12966-015-0201-9.
9
Physical activity among children: objective measurements using Fitbit One and ActiGraph.儿童的身体活动:使用Fitbit One和ActiGraph进行客观测量
BMC Res Notes. 2017 Apr 20;10(1):161. doi: 10.1186/s13104-017-2476-1.
10
Comparison of wrist-worn Fitbit Flex and waist-worn ActiGraph for measuring steps in free-living adults.腕戴式Fitbit Flex与腰戴式ActiGraph在测量自由生活成年人步数方面的比较。
PLoS One. 2017 Feb 24;12(2):e0172535. doi: 10.1371/journal.pone.0172535. eCollection 2017.

引用本文的文献

1
Continuous Movement Monitoring at Home Through Wearable Devices: A Systematic Review.通过可穿戴设备进行家庭连续运动监测:一项系统综述。
Sensors (Basel). 2025 Aug 8;25(16):4889. doi: 10.3390/s25164889.
2
Quantitative Evaluation of Postural SmartVest's Multisensory Feedback for Affordable Smartphone-Based Post-Stroke Motor Rehabilitation.基于经济实惠的智能手机的中风后运动康复中姿势智能背心多感官反馈的定量评估
Int J Environ Res Public Health. 2025 Jun 28;22(7):1034. doi: 10.3390/ijerph22071034.
3
Wearable Smartphone-Based Multisensory Feedback System for Torso Posture Correction: Iterative Design and Within-Subjects Study.

本文引用的文献

1
Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association.《心脏病与卒中统计-2020 更新:来自美国心脏协会的报告》。
Circulation. 2020 Mar 3;141(9):e139-e596. doi: 10.1161/CIR.0000000000000757. Epub 2020 Jan 29.
2
Consumer Wearable Devices for Activity Monitoring Among Individuals After a Stroke: A Prospective Comparison.用于中风后个体活动监测的消费级可穿戴设备:一项前瞻性比较研究
JMIR Cardio. 2018 Jan 4;2(1):e1. doi: 10.2196/cardio.8199.
3
Individual Patient-reported Activity Levels Before and After Joint Arthroplasty Are Neither Accurate nor Reproducible.
基于可穿戴智能手机的躯干姿势矫正多感官反馈系统:迭代设计与受试者内研究
JMIR Aging. 2025 Jan 22;8:e55455. doi: 10.2196/55455.
4
Use of commercially available wearable devices for physical rehabilitation in healthcare: a systematic review.商业可用可穿戴设备在医疗保健中的物理康复应用:系统评价。
BMJ Open. 2024 Nov 7;14(11):e084086. doi: 10.1136/bmjopen-2024-084086.
5
Impact of automated data flow and reminders on adherence and resource utilization for remotely monitoring physical activity in individuals with stroke or chronic obstructive pulmonary disease.自动化数据流和提醒对中风或慢性阻塞性肺疾病患者远程监测身体活动的依从性和资源利用的影响。
medRxiv. 2024 Apr 18:2024.04.15.24305852. doi: 10.1101/2024.04.15.24305852.
6
Exploring the Major Barriers to Physical Activity in Persons With Multiple Sclerosis: Observational Longitudinal Study.探索多发性硬化症患者身体活动的主要障碍:观察性纵向研究
JMIR Rehabil Assist Technol. 2024 Mar 18;11:e52733. doi: 10.2196/52733.
7
Sequential multiple assignment randomised trial to develop an adaptive mobile health intervention to increase physical activity in people poststroke in the community setting in Ireland: TAPAS trial protocol.序贯多项分配随机试验,旨在开发一种适应性移动健康干预措施,以增加爱尔兰社区中风后人群的身体活动量:TAPAS 试验方案。
BMJ Open. 2024 Jan 18;14(1):e072811. doi: 10.1136/bmjopen-2023-072811.
8
Exploring Variations in Sleep Perception: Comparative Study of Chatbot Sleep Logs and Fitbit Sleep Data.探索睡眠感知的变化:聊天机器人睡眠记录与 Fitbit 睡眠数据的比较研究。
JMIR Mhealth Uhealth. 2023 Nov 21;11:e49144. doi: 10.2196/49144.
9
Remote Activity Monitoring and Electronic Patient-Reported Outcomes Collection During Radiotherapy for Head and Neck Cancer: A Pilot Study.头颈部癌症放疗期间的远程活动监测和电子患者报告结局采集:一项试点研究。
JCO Clin Cancer Inform. 2023 Apr;7:e2200132. doi: 10.1200/CCI.22.00132.
10
Deploying Digital Health Technologies for Remote Physical Activity Monitoring of Rural Populations With Chronic Neurologic Disease.利用数字健康技术对患有慢性神经疾病的农村人口进行远程身体活动监测。
Arch Rehabil Res Clin Transl. 2022 Dec 5;5(1):100250. doi: 10.1016/j.arrct.2022.100250. eCollection 2023 Mar.
关节置换术前和术后个体患者报告的活动水平既不准确也不可重现。
Clin Orthop Relat Res. 2019 Mar;477(3):536-544. doi: 10.1097/CORR.0000000000000591.
4
Validation of Activity Tracking Procedures in Elderly Patients after Operative Treatment of Proximal Femur Fractures.股骨近端骨折手术治疗后老年患者活动跟踪程序的验证
Rehabil Res Pract. 2018 Jun 19;2018:3521271. doi: 10.1155/2018/3521271. eCollection 2018.
5
Feedback From Activity Trackers Improves Daily Step Count After Knee and Hip Arthroplasty: A Randomized Controlled Trial.活动追踪器的反馈可改善膝关节和髋关节置换术后的日常步数:一项随机对照试验。
J Arthroplasty. 2018 Nov;33(11):3422-3428. doi: 10.1016/j.arth.2018.06.024. Epub 2018 Jun 28.
6
Level of physical activity in men and women with chronic stroke.男性和女性慢性中风患者的身体活动水平。
Physiother Theory Pract. 2019 Oct;35(10):947-955. doi: 10.1080/09593985.2018.1460646. Epub 2018 Apr 16.
7
Best practice guidelines for the measurement of physical activity levels in stroke survivors: a secondary analysis of an observational study.中风幸存者身体活动水平测量的最佳实践指南:一项观察性研究的二次分析
Int J Rehabil Res. 2018 Mar;41(1):14-19. doi: 10.1097/MRR.0000000000000253.
8
Physical Activity to Reduce Fatigue in Rheumatoid Arthritis: A Randomized Controlled Trial.体力活动减轻类风湿关节炎疲劳:一项随机对照试验。
Arthritis Care Res (Hoboken). 2018 Jan;70(1):1-10. doi: 10.1002/acr.23230. Epub 2017 Dec 6.
9
Impact of accelerometer and pedometer use on physical activity and glycaemic control in people with Type 2 diabetes: a systematic review and meta-analysis.加速度计和计步器的使用对2型糖尿病患者身体活动及血糖控制的影响:一项系统综述与荟萃分析
Diabet Med. 2017 May;34(5):612-620. doi: 10.1111/dme.13331. Epub 2017 Mar 19.
10
Predicting Home and Community Walking Activity Poststroke.预测中风后家庭及社区步行活动情况
Stroke. 2017 Feb;48(2):406-411. doi: 10.1161/STROKEAHA.116.015309. Epub 2017 Jan 5.