• 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

相似文献

1
A low-cost body inertial-sensing network for practical gait discrimination of hemiplegia patients.一种低成本的人体惯性传感网络,用于偏瘫患者的实用步态判别。
Telemed J E Health. 2012 Dec;18(10):748-54. doi: 10.1089/tmj.2012.0014. Epub 2012 Mar 26.
2
Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention.量化自我与人体运动:关于可穿戴传感及反馈对步态分析与干预的临床影响的综述
Gait Posture. 2014;40(1):11-9. doi: 10.1016/j.gaitpost.2014.03.189. Epub 2014 Apr 6.
3
Balance and knee extensibility evaluation of hemiplegic gait using an inertial body sensor network.使用惯性体传感器网络评估偏瘫步态的平衡和膝关节伸展性。
Biomed Eng Online. 2013 Aug 29;12:83. doi: 10.1186/1475-925X-12-83.
4
Validation of wearable visual feedback for retraining foot progression angle using inertial sensors and an augmented reality headset.使用惯性传感器和增强现实头戴设备验证可穿戴视觉反馈在重新训练足部前进角度中的作用。
J Neuroeng Rehabil. 2018 Aug 15;15(1):78. doi: 10.1186/s12984-018-0419-2.
5
Inertial sensing algorithms for long-term foot angle monitoring for assessment of idiopathic toe-walking.用于特发性趾行步态评估的长期足部角度监测的惯性感应算法。
Gait Posture. 2014;39(1):485-9. doi: 10.1016/j.gaitpost.2013.08.021. Epub 2013 Aug 31.
6
Foot progression angle estimation using a single foot-worn inertial sensor.基于单足部穿戴惯性传感器的足进角估计
J Neuroeng Rehabil. 2021 Feb 17;18(1):37. doi: 10.1186/s12984-021-00816-4.
7
Side to side kinematic gait differences within patients and spatiotemporal and kinematic gait differences between patients with severe knee osteoarthritis and controls measured with inertial sensors.使用惯性传感器测量严重膝关节骨关节炎患者与对照组患者之间的侧向运动学步态差异和时空步态差异。
Gait Posture. 2021 Feb;84:24-30. doi: 10.1016/j.gaitpost.2020.11.015. Epub 2020 Nov 18.
8
Ankle-foot orthosis with dorsiflexion resistance using spring-cam mechanism increases knee flexion in the swing phase during walking in stroke patients with hemiplegia.使用弹簧凸轮机构的踝足矫形器具有背屈阻力,可增加偏瘫中风患者行走时摆动相的膝关节屈曲。
Gait Posture. 2020 Sep;81:27-32. doi: 10.1016/j.gaitpost.2020.06.029. Epub 2020 Jul 2.
9
Effects of ankle foot orthosis in stiff knee gait in adults with hemiplegia.踝足矫形器对偏瘫成人僵直膝步态的影响。
J Biomech. 2012 Oct 11;45(15):2658-61. doi: 10.1016/j.jbiomech.2012.08.015. Epub 2012 Sep 12.
10
Gait Kinematic Analysis in Water Using Wearable Inertial Magnetic Sensors.使用可穿戴惯性磁传感器进行水中步态运动学分析。
PLoS One. 2015 Sep 14;10(9):e0138105. doi: 10.1371/journal.pone.0138105. eCollection 2015.

引用本文的文献

1
A multi-sensor approach to improve interpretability of the 6-min walk test as an outcome in muscular dystrophies: an observational study.一种多传感器方法以提高6分钟步行试验作为肌营养不良症结局指标的可解释性:一项观察性研究。
Brain Commun. 2025 Jun 5;7(3):fcaf205. doi: 10.1093/braincomms/fcaf205. eCollection 2025.
2
Gait metrics analysis utilizing single-point inertial measurement units: a systematic review.利用单点惯性测量单元的步态指标分析:一项系统综述
Mhealth. 2022 Jan 20;8:9. doi: 10.21037/mhealth-21-17. eCollection 2022.
3
Evaluating the Impact of IMU Sensor Location and Walking Task on Accuracy of Gait Event Detection Algorithms.评估 IMU 传感器位置和行走任务对步态事件检测算法准确性的影响。
Sensors (Basel). 2021 Jun 9;21(12):3989. doi: 10.3390/s21123989.
4
Optimization of IMU Sensor Placement for the Measurement of Lower Limb Joint Kinematics.优化 IMU 传感器放置位置以测量下肢关节运动学。
Sensors (Basel). 2020 Oct 22;20(21):5993. doi: 10.3390/s20215993.
5
Kinematic gait analysis using inertial sensors with subjects after stroke in two different arteries.使用惯性传感器对两条不同动脉中风后患者进行运动步态分析。
J Phys Ther Sci. 2014 Aug;26(8):1307-11. doi: 10.1589/jpts.26.1307. Epub 2014 Aug 30.
6
Seamless tracing of human behavior using complementary wearable and house-embedded sensors.利用互补的可穿戴传感器和嵌入房屋的传感器对人类行为进行无缝追踪。
Sensors (Basel). 2014 Apr 29;14(5):7831-56. doi: 10.3390/s140507831.

本文引用的文献

1
A wearable respiratory biofeedback system based on generalized body sensor network.基于广义体域网的可穿戴呼吸生物反馈系统。
Telemed J E Health. 2011 Jun;17(5):348-57. doi: 10.1089/tmj.2010.0182. Epub 2011 May 5.
2
Alteration of the load-response mechanism of the knee joint during hemiparetic gait following stroke analyzed by 3-dimensional kinematic.通过三维运动学分析中风后偏瘫步态期间膝关节负荷-反应机制的改变。
Clinics (Sao Paulo). 2006 Aug;61(4):295-300. doi: 10.1590/s1807-59322006000400004.
3
A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes.一种基于加速度计和陀螺仪组合的精确测量单轴关节角度的新方法。
IEEE Trans Biomed Eng. 2005 Aug;52(8):1478-84. doi: 10.1109/TBME.2005.851475.
4
Discrimination of walking patterns using wavelet-based fractal analysis.基于小波的分形分析对行走模式的辨别
IEEE Trans Neural Syst Rehabil Eng. 2002 Sep;10(3):188-96. doi: 10.1109/TNSRE.2002.802879.
5
Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes.使用微型陀螺仪的动态系统测量的步态时空参数。
J Biomech. 2002 May;35(5):689-99. doi: 10.1016/s0021-9290(02)00008-8.
6
Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems.加速度计和速率陀螺仪对运动学的测量:一种替代光学运动分析系统的低成本方法。
J Biomech. 2002 Apr;35(4):537-42. doi: 10.1016/s0021-9290(01)00231-7.
7
A new ambulatory foot pressure device for patients with sensory impairment. A system for continuous measurement of plantar pressure and a feed-back alarm.
J Biomech. 2000 Sep;33(9):1135-8. doi: 10.1016/s0021-9290(00)00082-8.
8
Incidence and occurrence of total (first-ever and recurrent) stroke.全因(首次发生及复发)卒中的发病率和发生率。
Stroke. 1999 Dec;30(12):2523-8. doi: 10.1161/01.str.30.12.2523.
9
Hemiplegic gait of stroke patients: the effect of using a cane.中风患者的偏瘫步态:使用手杖的效果。
Arch Phys Med Rehabil. 1999 Jul;80(7):777-84. doi: 10.1016/s0003-9993(99)90227-7.
10
A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity.一种用于评估日常身体活动的三轴加速度计和便携式数据处理单元。
IEEE Trans Biomed Eng. 1997 Mar;44(3):136-47. doi: 10.1109/10.554760.

一种低成本的人体惯性传感网络,用于偏瘫患者的实用步态判别。

A low-cost body inertial-sensing network for practical gait discrimination of hemiplegia patients.

机构信息

Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen, China.

出版信息

Telemed J E Health. 2012 Dec;18(10):748-54. doi: 10.1089/tmj.2012.0014. Epub 2012 Mar 26.

DOI:10.1089/tmj.2012.0014
PMID:22449064
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3523244/
Abstract

Gait analysis is widely used in detecting human walking disorders. Current gait analysis methods like video- or optical-based systems are expensive and cause invasion of human privacy. This article presents a self-developed low-cost body inertial-sensing network, which contains a base station, three wearable inertial measurement nodes, and the affiliated wireless communication protocol, for practical gait discrimination between hemiplegia patients and asymptomatic subjects. Every sensing node contains one three-axis accelerometer, one three-axis magnetometer, and one three-axis gyroscope. Seven hemiplegia patients (all were abnormal on the right side) and 7 asymptomatic subjects were examined. The three measurement nodes were attached on the thigh, the shank, and the dorsum of the foot, respectively (all on the right side of the body). A new method, which does not need to obtain accurate positions of the sensors, was used to calculate angles of knee flexion/extension and foot in the gait cycle. The angle amplitudes of initial contact, toe off, and knee flexion/extension were extracted. The results showed that there were significant differences between the two groups in the three angle amplitudes examined (-0.52±0.98° versus 6.94±2.63°, 28.33±11.66° versus 47.34±7.90°, and 26.85±8.6° versus 50.91±6.60°, respectively). It was concluded that the body inertial-sensing network platform provided a practical approach for wearable biomotion acquisition and was effective for discriminating gait symptoms between hemiplegia and asymptomatic subjects.

摘要

步态分析广泛应用于检测人类行走障碍。目前的步态分析方法,如视频或基于光学的系统,价格昂贵且侵犯了人类的隐私。本文提出了一种自主开发的低成本体惯性传感网络,它包含一个基站、三个可穿戴惯性测量节点和相关的无线通信协议,用于实际区分偏瘫患者和无症状受试者的步态。每个传感节点包含一个三轴加速度计、一个三轴磁力计和一个三轴陀螺仪。检查了 7 名偏瘫患者(右侧均异常)和 7 名无症状受试者。三个测量节点分别附着在大腿、小腿和脚背部(均在身体右侧)。使用一种新的方法,不需要获得传感器的准确位置,来计算膝关节屈伸和脚部在步态周期中的角度。提取初始接触、足趾离地和膝关节屈伸的角度幅度。结果表明,在三个角度幅度上,两组之间存在显著差异(初始接触时为-0.52±0.98°对 6.94±2.63°,足趾离地时为 28.33±11.66°对 47.34±7.90°,膝关节屈伸时为 26.85±8.6°对 50.91±6.60°)。结论:体惯性传感网络平台为可穿戴生物运动获取提供了一种实用方法,对于区分偏瘫和无症状受试者的步态症状是有效的。