Suppr超能文献

使用目标跟踪测试对颈椎疾病患者手部运动功能进行定量评估。

Quantitative assessment of hand motor function in cervical spinal disorder patients using target tracking tests.

作者信息

Lee Sunghoon I, Huang Alex, Mortazavi Bobak, Li Charles, Hoffman Haydn A, Garst Jordan, Lu Derek S, Getachew Ruth, Espinal Marie, Razaghy Mehrdad, Ghalehsari Nima, Paak Brian H, Ghavam Amir A, Afridi Marwa, Ostowari Arsha, Ghasemzadeh Hassan, Lu Daniel C, Sarrafzadeh Majid

机构信息

Computer Science Department, University of California Los Angeles (UCLA), Los Angeles, CA.

Department of Neurosurgery, UCLA, Los Angeles, CA.

出版信息

J Rehabil Res Dev. 2016;53(6):1007-1022. doi: 10.1682/JRRD.2014.12.0319.

Abstract

Cervical spondylotic myelopathy (CSM) is a chronic spinal disorder in the neck region. Its prevalence is growing rapidly in developed nations, creating a need for an objective assessment tool. This article introduces a system for quantifying hand motor function using a handgrip device and target tracking test. In those with CSM, hand motor impairment often interferes with essential daily activities. The analytic method applied machine learning techniques to investigate the efficacy of the system in (1) detecting the presence of impairments in hand motor function, (2) estimating the perceived motor deficits of CSM patients using the Oswestry Disability Index (ODI), and (3) detecting changes in physical condition after surgery, all of which were performed while ensuring test-retest reliability. The results based on a pilot data set collected from 30 patients with CSM and 30 nondisabled control subjects produced a c-statistic of 0.89 for the detection of impairments, Pearson r of 0.76 with p < 0.001 for the estimation of ODI, and a c-statistic of 0.82 for responsiveness. These results validate the use of the presented system as a means to provide objective and accurate assessment of the level of impairment and surgical outcomes.

摘要

脊髓型颈椎病(CSM)是一种颈部慢性脊柱疾病。在发达国家,其患病率正在迅速上升,因此需要一种客观的评估工具。本文介绍了一种使用握力装置和目标跟踪测试来量化手部运动功能的系统。在患有CSM的患者中,手部运动障碍常常会干扰基本的日常活动。该分析方法应用机器学习技术来研究该系统在以下方面的有效性:(1)检测手部运动功能障碍的存在;(2)使用奥斯威斯利功能障碍指数(ODI)估计CSM患者的感知运动缺陷;(3)检测手术后身体状况的变化,所有这些都是在确保重测信度的情况下进行的。基于从30例CSM患者和30例非残疾对照受试者收集的试点数据集得出的结果显示,用于检测损伤的c统计量为0.89,用于估计ODI的Pearson相关系数r为0.76,p<0.001,用于反应性的c统计量为0.82。这些结果验证了所提出的系统可作为一种手段,用于对手部损伤程度和手术结果进行客观准确的评估。

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