Virtual reality assessment of reaching accuracy in patients with recent cerebellar stroke.

BMC digital health Pub Date : 2024-01-01 Epub Date: 2024-08-12 DOI:10.1186/s44247-024-00107-7
Khai Du, Leonardo R Benavides, Emily L Isenstein, Duje Tadin, Ania C Busza
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Abstract

Background: Dysmetria, the inability to accurately estimate distance in motor tasks, is a characteristic clinical feature of cerebellar injury. Even though subjective dysmetria can be quickly detected during the neurological examination with the finger-to-nose test, objective quantification of reaching accuracy for clinical assessment is still lacking. Emerging VR technology allows for the delivery of rich multisensory environmental stimuli with a high degree of control. Furthermore, recent improvements in the hand-tracking feature offer an opportunity to closely examine the speed, accuracy, and consistency of fine hand movements and proprioceptive function. This study aims to investigate the application of virtual reality (VR) with hand tracking in the rapid quantification of reaching accuracy at the bedside for patients with cerebellar stroke (CS).

Methods and results: Thirty individuals (10 CS patients and 20 age-matched neurologically healthy controls) performed a simple task that allowed us to measure reaching accuracy using a VR headset (Oculus Quest 2). During this task, the participant was asked to reach for a target placed along a horizontal sixty-degree arc. Once the fingertip passed through the arc, the target immediately extinguished. 50% of the trials displayed a visible, real-time rendering of the hand as the participant reached for the target (visible hand condition), while the remaining 50% only showed the target being extinguished (invisible hand condition). The invisible hand condition isolates proprioception-guided movements by removing the visibility of the participant's hand. Reaching error was calculated as the difference in degrees between the location of the target, and where the fingertip contacted the arc. Both CS patients and age-matched controls displayed higher average reaching error and took longer to perform a reaching motion in the invisible hand condition than in the visible hand condition. Reaching error was higher in CS than in controls in the invisible hand condition but not in the visible hand condition. Average time taken to perform each trial was higher in CS than in controls in the invisible hand conditions but not in the visible hand condition.

Conclusions: Reaching accuracy assessed by VR offers a non-invasive and rapid approach to quantifying fine motor functions in clinical settings. Furthermore, this technology enhances our understanding of proprioceptive function in patients with visuomotor disabilities by allowing the isolation of proprioception from vision. Future studies with larger cohorts and longitudinal designs will examine the quantitative changes in reaching accuracy after stroke and explore the long-term benefits of VR in functional recovery.

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对近期小脑卒中患者伸手准确性的虚拟现实评估
背景:测距障碍是指在运动任务中无法准确估计距离,是小脑损伤的一个特征性临床表现。尽管在神经系统检查中可以通过指鼻测试快速检测出主观的测距障碍,但仍缺乏用于临床评估的测距准确性的客观量化指标。新兴的虚拟现实技术可以在高度可控的情况下提供丰富的多感官环境刺激。此外,最近手部追踪功能的改进为仔细检查手部精细动作的速度、准确性和一致性以及本体感觉功能提供了机会。本研究旨在探讨虚拟现实(VR)与手部追踪技术在小脑卒中(CS)患者床边快速量化伸手准确性中的应用:30 人(10 名小脑中风患者和 20 名年龄匹配的神经健康对照组)完成了一项简单的任务,我们可以利用 VR 头显(Oculus Quest 2)测量伸手的准确性。在这项任务中,受试者被要求伸手去够一个沿水平 60 度弧线放置的目标。一旦指尖穿过弧线,目标就会立即熄灭。50%的试验显示了参与者伸手够目标时手的实时可见图像(可见手条件),而其余 50%的试验仅显示目标熄灭(不可见手条件)。隐形手条件通过消除被试手部的可见度来隔离本体感觉引导的动作。伸手误差的计算方法是目标位置与指尖接触弧线位置之间的度数差。在看不见手的条件下,CS 患者和年龄相匹配的对照组的平均伸手误差都比在看得见手的条件下高,而且完成伸手动作所需的时间也更长。在看不见手的条件下,CS 患者的伸手误差高于对照组,但在看得见手的条件下,CS 患者的伸手误差不高于对照组。在看不见手的条件下,CS 完成每次试验所需的平均时间高于对照组,但在看得见手的条件下则不然:通过虚拟现实技术评估伸手准确性为在临床环境中量化精细运动功能提供了一种非侵入性的快速方法。此外,这项技术还能将本体感觉与视觉分离开来,从而加深我们对视动障碍患者本体感觉功能的了解。未来的研究将采用更大规模的队列和纵向设计来检查中风后伸手准确性的定量变化,并探索 VR 对功能恢复的长期益处。
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