Centre for Neuroscience Studies, Queen's University, Botterell Hall, 18 Stuart St, Kingston, ON, K7L 3N6, Canada.
Department of Physical Medicine and Rehabilitation, Queen's University, Kingston, ON, Canada.
J Neuroeng Rehabil. 2023 Oct 11;20(1):137. doi: 10.1186/s12984-023-01262-0.
A key motor skill is the ability to rapidly interact with our dynamic environment. Humans can generate goal-directed motor actions in response to sensory stimulus within ~ 60-200ms. This ability can be impaired after stroke, but most clinical tools lack any measures of rapid feedback processing. Reaching tasks have been used as a framework to quantify impairments in generating motor corrections for individuals with stroke. However, reaching may be inadequate as an assessment tool as repeated reaching can be fatiguing for individuals with stroke. Further, reaching requires many trials to be completed including trials with and without disturbances, and thus, exacerbate fatigue. Here, we describe a novel robotic task to quantify rapid feedback processing in healthy controls and compare this performance with individuals with stroke to (more) efficiently identify impairments in rapid feedback processing.
We assessed a cohort of healthy controls (n = 135) and individuals with stroke (n = 40; Mean 41 days from stroke) in the Fast Feedback Interception Task (FFIT) using the Kinarm Exoskeleton robot. Participants were instructed to intercept a circular white target moving towards them with their hand represented as a virtual paddle. On some trials, the arm could be physically perturbed, the target or paddle could abruptly change location, or the target could change colour requiring the individual to now avoid the target.
Most participants with stroke were impaired in reaction time (85%) and end-point accuracy (83%) in at least one of the task conditions, most commonly with target or paddle shifts. Of note, this impairment was also evident in most individuals with stroke when performing the task using their unaffected arm (75%). Comparison with upper limb clinical measures identified moderate correlations with the FFIT.
The FFIT was able to identify a high proportion of individuals with stroke as impaired in rapid feedback processing using either the affected or unaffected arms. The task allows many different types of feedback responses to be efficiently assessed in a short amount of time.
一项关键的运动技能是快速与动态环境交互的能力。人类可以在大约 60-200 毫秒内对感官刺激做出目标导向的运动反应。这种能力在中风后可能会受损,但大多数临床工具都没有任何快速反馈处理的衡量标准。伸手任务已被用作量化中风患者产生运动矫正能力受损的框架。然而,由于中风患者重复伸手可能会感到疲劳,因此伸手可能不足以作为评估工具。此外,伸手需要完成许多试验,包括有和没有干扰的试验,因此会加剧疲劳。在这里,我们描述了一种新的机器人任务,以量化健康对照者的快速反馈处理,并将这种表现与中风患者进行比较,以便更有效地识别快速反馈处理受损。
我们使用 Kinarm Exoskeleton 机器人评估了一组健康对照者(n=135)和中风患者(n=40;中风后平均 41 天)在快速反馈拦截任务(FFIT)中的表现。参与者被指示用手代表虚拟桨来拦截向他们移动的圆形白色目标。在某些试验中,手臂可能会受到物理干扰,目标或桨可能会突然改变位置,或者目标可能会改变颜色,要求个体避开目标。
大多数中风患者在至少一种任务条件下的反应时间(85%)和终点准确性(83%)受到损害,最常见的是目标或桨的移位。值得注意的是,即使在使用未受影响的手臂执行任务时,大多数中风患者也表现出这种损伤(75%)。与上肢临床测量指标的比较表明,与 FFIT 存在中度相关性。
FFIT 能够识别出相当一部分中风患者在使用受影响或未受影响的手臂进行快速反馈处理时存在受损。该任务可以在短时间内有效地评估许多不同类型的反馈反应。