Suppr超能文献

基于触觉和视觉设备的脑卒中后手测量系统。

Hand Measurement System Based on Haptic and Vision Devices towards Post-Stroke Patients.

机构信息

Institute of Machine Tools and Production Engineering, Lodz University of Technology, 90-537 Lodz, Poland.

Institute of Automatic Control, Lodz University of Technology, 90-537 Lodz, Poland.

出版信息

Sensors (Basel). 2022 Mar 7;22(5):2060. doi: 10.3390/s22052060.

Abstract

Diagnostics of a hand requires measurements of kinematics and joint limits. The standard tools for this purpose are manual devices such as goniometers which allow measuring only one joint simultaneously, making the diagnostics time-consuming. The paper presents a system for automatic measurement and computer presentation of essential parameters of a hand. Constructed software uses an integrated vision system, a haptic device for measurement, and has a web-based user interface. The system provides a simplified way to obtain hand parameters, such as hand size, wrist, and finger range of motions, using the homogeneous-matrix-based notation. The haptic device allows for active measurement of the wrist's range of motion and additional force measurement. A study was conducted to determine the accuracy and repeatability of measurements compared to the gold standard. The system functionality was confirmed on five healthy participants, with results showing comparable results to manual measurements regarding fingers' lengths. The study showed that the finger's basic kinematic structure could be measured by a vision system with a mean difference to caliper measurement of 4.5 mm and repeatability with the Standard Deviations up to 0.7 mm. Joint angle limits measurement achieved poorer results with a mean difference to goniometer of 23.6º. Force measurements taken by the haptic device showed the repeatability with a Standard Deviation of 0.7 N. The presented system allows for a unified measurement and a collection of important parameters of a human hand with therapist interface visualization and control with potential use for post-stroke patients' precise rehabilitation.

摘要

手的诊断需要测量运动学和关节限制。为此目的的标准工具是手动设备,如测角器,它只能同时测量一个关节,使诊断过程耗时。本文介绍了一种用于自动测量和计算机呈现手部基本参数的系统。构建的软件使用集成视觉系统、用于测量的触觉设备,并具有基于网络的用户界面。该系统提供了一种简化的方法来获得手部参数,例如手的大小、手腕和手指运动范围,使用基于齐次矩阵的符号表示。触觉设备允许主动测量手腕的运动范围和额外的力测量。进行了一项研究,以确定与黄金标准相比测量的准确性和可重复性。该系统在五名健康参与者中进行了功能验证,结果表明,与手动测量相比,手指长度的测量结果具有可比性。研究表明,可以通过视觉系统测量手指的基本运动结构,与卡尺测量的平均差异为 4.5 毫米,重复测量的标准偏差最高可达 0.7 毫米。关节角度限制测量的结果较差,与测角器的平均差异为 23.6 度。触觉设备测量的力显示出重复测量的标准偏差为 0.7 N。所提出的系统允许对人手的重要参数进行统一测量和收集,并具有治疗师界面可视化和控制功能,可用于中风后患者的精确康复。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f50e/8914655/9fe787659089/sensors-22-02060-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验