• 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

将可穿戴技术融入髋关节和膝关节置换术后的康复监测中。

Incorporating Wearable Technology for Enhanced Rehabilitation Monitoring after Hip and Knee Replacement.

机构信息

moveUp, 1000 Brussels, Belgium.

Department of PXL-Healthcare, PXL University of Applied Sciences and Arts, 3500 Hasselt, Belgium.

出版信息

Sensors (Basel). 2024 Feb 10;24(4):1163. doi: 10.3390/s24041163.

DOI:10.3390/s24041163
PMID:38400321
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10892564/
Abstract

Osteoarthritis (OA) poses a growing challenge for the aging population, especially in the hip and knee joints, contributing significantly to disability and societal costs. Exploring the integration of wearable technology, this study addresses the limitations of traditional rehabilitation assessments in capturing real-world experiences and dynamic variations. Specifically, it focuses on continuously monitoring physical activity in hip and knee OA patients using automated unsupervised evaluations within the rehabilitation process. We analyzed data from 1144 patients who used a mobile health application after surgery; the activity data were collected using the Garmin Vivofit 4. Several parameters, such as the total number of steps per day, the peak 6-minute consecutive cadence (P6MC) and peak 1-minute cadence (P1M), were computed and analyzed on a daily basis. The results indicated that cadence-based measurements can effectively, and earlier, differ among patients with hip and knee conditions, as well as in the recovery process. Comparisons based on recovery status and type of surgery reveal distinctive trajectories, emphasizing the effectiveness of P6MC and P1M in detecting variations earlier than total steps per day. Furthermore, cadence-based measurements showed a lower inter-day variability (40%) compared to the total number of steps per day (80%). Automated assessments, including P1M and P6MC, offer nuanced insights into the patients' dynamic activity profiles.

摘要

骨关节炎(OA)给老龄化人口带来了日益严峻的挑战,尤其是髋关节和膝关节,极大地导致了残疾和社会成本。本研究探索了可穿戴技术的整合,以解决传统康复评估在捕捉真实世界体验和动态变化方面的局限性。具体来说,它侧重于在康复过程中使用自动化无监督评估来持续监测髋关节和膝关节 OA 患者的身体活动。我们分析了 1144 名手术后使用移动健康应用程序的患者的数据;活动数据是使用 Garmin Vivofit 4 收集的。每天计算和分析了几个参数,如每天的总步数、6 分钟连续最大步频(P6MC)和 1 分钟最大步频(P1M)。结果表明,基于步频的测量可以有效地、更早地区分髋关节和膝关节疾病患者以及康复过程中的患者。基于恢复状态和手术类型的比较揭示了独特的轨迹,强调了 P6MC 和 P1M 在检测变化方面比每天的总步数更早的有效性。此外,基于步频的测量比每天的总步数(80%)具有更低的日内变异性(40%)。包括 P1M 和 P6MC 在内的自动化评估为患者的动态活动特征提供了细致的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/31b4eacaf0f2/sensors-24-01163-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/ad053c4db9fa/sensors-24-01163-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/0e925119f8da/sensors-24-01163-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/b5db6f3706f4/sensors-24-01163-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/703f42817832/sensors-24-01163-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/95e3e41308f6/sensors-24-01163-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/418cafcbf3b0/sensors-24-01163-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/31b4eacaf0f2/sensors-24-01163-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/ad053c4db9fa/sensors-24-01163-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/0e925119f8da/sensors-24-01163-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/b5db6f3706f4/sensors-24-01163-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/703f42817832/sensors-24-01163-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/95e3e41308f6/sensors-24-01163-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/418cafcbf3b0/sensors-24-01163-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f1d/10892564/31b4eacaf0f2/sensors-24-01163-g007.jpg

相似文献

1
Incorporating Wearable Technology for Enhanced Rehabilitation Monitoring after Hip and Knee Replacement.将可穿戴技术融入髋关节和膝关节置换术后的康复监测中。
Sensors (Basel). 2024 Feb 10;24(4):1163. doi: 10.3390/s24041163.
2
Remote Patient Monitoring Using Mobile Health for Total Knee Arthroplasty: Validation of a Wearable and Machine Learning-Based Surveillance Platform.基于移动医疗的全膝关节置换术后远程患者监测:一种可穿戴设备和基于机器学习的监测平台的验证。
J Arthroplasty. 2019 Oct;34(10):2253-2259. doi: 10.1016/j.arth.2019.05.021. Epub 2019 May 16.
3
Independent and sensitive gait parameters for objective evaluation in knee and hip osteoarthritis using wearable sensors.使用可穿戴传感器进行膝关节和髋关节骨关节炎的客观评估的独立且敏感的步态参数。
BMC Musculoskelet Disord. 2021 Mar 3;22(1):242. doi: 10.1186/s12891-021-04074-2.
4
Cost, time savings and effectiveness of wearable devices for remote monitoring of patient rehabilitation after total knee arthroplasty: study protocol for a randomized controlled trial.可穿戴设备远程监测全膝关节置换术后患者康复的成本、时间节省和效果:一项随机对照试验的研究方案。
J Orthop Surg Res. 2023 Jun 27;18(1):461. doi: 10.1186/s13018-023-03898-z.
5
Concurrent validity and inter trial reliability of a single inertial measurement unit for spatial-temporal gait parameter analysis in patients with recent total hip or total knee arthroplasty.近期全髋关节或全膝关节置换术后患者单惯性测量单元进行时空步态参数分析的同时效度和试验间信度。
Gait Posture. 2020 Feb;76:175-181. doi: 10.1016/j.gaitpost.2019.12.014. Epub 2019 Dec 13.
6
Assessing Site Specificity of Osteoarthritic Gait Kinematics with Wearable Sensors and Their Association with Patient Reported Outcome Measures (PROMs): Knee versus Hip Osteoarthritis.评估可穿戴传感器对骨关节炎步态运动学的特定部位的特异性及其与患者报告的结局测量(PROMs)的相关性:膝关节与髋关节骨关节炎。
Sensors (Basel). 2021 Aug 10;21(16):5363. doi: 10.3390/s21165363.
7
Validation of a Wearable System for Lower Extremity Assessment.下肢评估可穿戴系统的验证。
Orthop Surg. 2023 Nov;15(11):2911-2917. doi: 10.1111/os.13836. Epub 2023 Aug 6.
8
Recovery Curve for Patient Reported Outcomes and Objective Physical Activity After Primary Total Knee Arthroplasty-A Multicenter Study Using Wearable Technology.患者报告的术后结局和客观体力活动的恢复曲线:一项使用可穿戴技术的多中心研究。
J Arthroplasty. 2023 Jun;38(6S):S94-S102. doi: 10.1016/j.arth.2023.03.060. Epub 2023 Mar 28.
9
Evaluation of gait recovery after total knee arthroplasty using wearable inertial sensors: A systematic review.使用可穿戴惯性传感器评估全膝关节置换术后的步态恢复:系统评价。
Knee. 2023 Mar;41:190-203. doi: 10.1016/j.knee.2023.01.006. Epub 2023 Jan 30.
10
Physical activity patterns, adherence to using a wearable activity tracker during a 12-week period and correlation between self-reported function and physical activity in working age individuals with hip and/or knee osteoarthritis.体力活动模式、在 12 周期间使用可穿戴活动追踪器的依从性,以及髋和/或膝关节骨关节炎的工作年龄个体中自我报告的功能与体力活动之间的相关性。
BMC Musculoskelet Disord. 2021 May 15;22(1):450. doi: 10.1186/s12891-021-04338-x.

引用本文的文献

1
High-dimensional item response theory analysis of patient-reported outcomes in total knee arthroplasty.全膝关节置换术中患者报告结局的高维项目反应理论分析
NPJ Digit Med. 2025 Jul 1;8(1):391. doi: 10.1038/s41746-025-01783-z.
2
Animals as Architects: Building the Future of Technology-Supported Rehabilitation with Biomimetic Principles.动物作为建筑师:运用仿生原理构建技术支持康复的未来。
Biomimetics (Basel). 2024 Nov 22;9(12):723. doi: 10.3390/biomimetics9120723.

本文引用的文献

1
Outcomes Vary by Pre-Operative Physical Activity Levels in Total Knee Arthroplasty Patients.全膝关节置换术患者的术后结果因术前身体活动水平而异。
J Clin Med. 2023 Dec 25;13(1):125. doi: 10.3390/jcm13010125.
2
The validity of smartphone-based spatiotemporal gait measurements during walking with and without head turns: Comparison with the GAITRite® system.基于智能手机的空间时间步态测量在头部有和没有转动时行走的有效性:与 GAITRite ® 系统的比较。
J Biomech. 2024 Jan;162:111899. doi: 10.1016/j.jbiomech.2023.111899. Epub 2023 Dec 13.
3
Device-Measured Physical Activity in 3506 Individuals with Knee or Hip Arthroplasty.
对3506名接受膝关节或髋关节置换术患者的设备测量身体活动情况
Med Sci Sports Exerc. 2024 May 1;56(5):805-812. doi: 10.1249/MSS.0000000000003365. Epub 2023 Dec 18.
4
Maximal daily stepping cadence partially explains functional capacity of individuals with end-stage knee osteoarthritis.最大日常步伐频率部分解释了终末期膝骨关节炎患者的功能能力。
PM R. 2024 Jun;16(6):532-542. doi: 10.1002/pmrj.13082. Epub 2023 Nov 27.
5
Automatic Assessment of the 2-Minute Walk Distance for Remote Monitoring of People with Multiple Sclerosis.自动评估 2 分钟步行距离,用于远程监测多发性硬化症患者。
Sensors (Basel). 2023 Jun 29;23(13):6017. doi: 10.3390/s23136017.
6
The effect of digital interventions on related health literacy and skills for individuals living with chronic diseases: A systematic review and meta-analysis.数字干预对慢性病患者相关健康素养和技能的影响:系统评价和荟萃分析。
Int J Med Inform. 2023 Sep;177:105114. doi: 10.1016/j.ijmedinf.2023.105114. Epub 2023 Jun 8.
7
Early post-operative walking bouts are associated with improved gait speed and symmetry at 90 days.早期术后行走与 90 天内步态速度和对称性的改善相关。
Gait Posture. 2024 Jan;107:130-135. doi: 10.1016/j.gaitpost.2023.05.014. Epub 2023 May 20.
8
Stepping Closer to Precision Rehabilitation.迈向精准康复
JAMA Neurol. 2023 Apr 1;80(4):339-341. doi: 10.1001/jamaneurol.2023.0044.
9
Mobile health solutions: An opportunity for rehabilitation in low- and middle income countries?移动医疗解决方案:在中低收入国家康复的机会?
Front Public Health. 2023 Jan 24;10:1072322. doi: 10.3389/fpubh.2022.1072322. eCollection 2022.
10
A Systematic Review of the Use of Commercial Wearable Activity Trackers for Monitoring Recovery in Individuals Undergoing Total Hip Replacement Surgery.一项关于使用商用可穿戴活动追踪器监测全髋关节置换手术患者康复情况的系统评价。
Cyborg Bionic Syst. 2022 Oct 26;2022:9794641. doi: 10.34133/2022/9794641. eCollection 2022.