Suppr超能文献

上肢位置觉和运动辨别力的机器人测试表明,在健康个体中,它们各自具有高度可重复性,但彼此之间没有相关性。

Robotic tests for position sense and movement discrimination in the upper limb reveal that they each are highly reproducible but not correlated in healthy individuals.

机构信息

Laboratory of Integrative Motor Behaviour, Centre for Neuroscience Studies, Queen's University, 18 Stuart St., Kingston, ON, K7L 3N6, Canada.

BioEngineering and Innovation in Neuroscience, University Paris Descartes, Paris, France.

出版信息

J Neuroeng Rehabil. 2020 Jul 25;17(1):103. doi: 10.1186/s12984-020-00721-2.

Abstract

BACKGROUND

Robotic technologies for neurological assessment provide sensitive, objective measures of behavioural impairments associated with injuries or disease such as stroke. Previous robotic tasks to assess proprioception typically involve single limbs or in some cases both limbs. The challenge with these approaches is that they often rely on intact motor function and/or working memory to remember/reproduce limb position, both of which can be impaired following stroke. Here, we examine the feasibility of a single-arm Movement Discrimination Threshold (MDT) task to assess proprioception by quantifying thresholds for sensing passive limb movement without vision. We use a staircase method to adjust movement magnitude based on subject performance throughout the task in order to reduce assessment time. We compare MDT task performance to our previously-designed Arm Position Matching (APM) task. Critically, we determine test-retest reliability of each task in the same population of healthy controls.

METHOD

Healthy participants (N = 21, age = 18-22 years) completed both tasks in the End-Point Kinarm robot. In the MDT task the robot moved the dominant arm left or right and participants indicated the direction moved. Movement displacement was systematically adjusted (decreased after correct answers, increased after incorrect) until the Discrimination Threshold was found. In the APM task, the robot moved the dominant arm and participants "mirror-matched" with the non-dominant arm.

RESULTS

Discrimination Threshold for direction of arm displacement in the MDT task ranged from 0.1-1.3 cm. Displacement Variability ranged from 0.11-0.71 cm. Test-retest reliability of Discrimination Threshold based on ICC confidence intervals was moderate to excellent (range, ICC = 0.78 [0.52-0.90]). Interestingly, ICC values for Discrimination Threshold increased to 0.90 [0.77-0.96] (good to excellent) when the number of trials was reduced to the first 50. Most APM parameters had ICC's above 0.80, (range, ICC = [0.86-0.88]) with the exception of variability (ICC = 0.30). Importantly, no parameters were significantly correlated across tasks as Spearman rank correlations across parameter-pairings ranged from - 0.27 to 0.30.

CONCLUSIONS

The MDT task is a feasible and reliable task, assessing movement discrimination threshold in ~ 17 min. Lack of correlation between the MDT and a position-matching task (APM) indicates that these tasks assess unique aspects of proprioception that are not strongly related in young, healthy individuals.

摘要

背景

用于神经评估的机器人技术提供了与损伤或疾病(如中风)相关的行为障碍的敏感、客观的测量方法。以前评估本体感受的机器人任务通常涉及单肢,或者在某些情况下涉及四肢。这些方法的挑战在于,它们通常依赖于完整的运动功能和/或工作记忆来记住/再现肢体位置,而这两者在中风后都可能受损。在这里,我们通过量化在没有视觉的情况下感知被动肢体运动的阈值来检查单臂运动辨别阈值 (MDT) 任务评估本体感受的可行性。我们使用阶梯法根据整个任务中受试者的表现调整运动幅度,以减少评估时间。我们将 MDT 任务的性能与我们之前设计的手臂位置匹配 (APM) 任务进行比较。至关重要的是,我们确定了每个任务在相同健康对照组中的测试-重测可靠性。

方法

健康参与者(N=21,年龄 18-22 岁)在 End-Point Kinarm 机器人中完成了这两个任务。在 MDT 任务中,机器人移动主导手臂向左或向右,参与者指示移动方向。运动位移被系统地调整(正确答案后减小,错误答案后增大),直到找到辨别阈值。在 APM 任务中,机器人移动主导手臂,参与者用非主导手臂“镜像匹配”。

结果

MDT 任务中手臂位移方向的辨别阈值范围为 0.1-1.3cm。位移变异性范围为 0.11-0.71cm。基于 ICC 置信区间的辨别阈值的测试-重测可靠性为中等至优秀(范围 ICC=0.78[0.52-0.90])。有趣的是,当将试验次数减少到前 50 次时,基于 ICC 的辨别阈值值增加到 0.90[0.77-0.96](良好至优秀)。大多数 APM 参数的 ICC 值大于 0.80(范围 ICC=[0.86-0.88]),除了变异性(ICC=0.30)。重要的是,由于参数对之间的 Spearman 等级相关系数范围为-0.27 至 0.30,因此没有参数在任务之间呈显著相关性。

结论

MDT 任务是一种可行且可靠的任务,大约需要 17 分钟即可评估运动辨别阈值。MDT 与位置匹配任务 (APM) 之间缺乏相关性表明,这些任务评估的是在年轻健康个体中没有强烈关联的本体感受的不同方面。

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