Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Department of Neurorehabilitation, Kliniken Schmieder, Allensbach, Germany.
J Neuroeng Rehabil. 2018 Jun 7;15(1):47. doi: 10.1186/s12984-018-0387-6.
Proprioceptive function can be affected after neurological injuries such as stroke. Severe and persistent proprioceptive impairments may be associated with a poor functional recovery after stroke. To better understand their role in the recovery process, and to improve diagnostics, prognostics, and the design of therapeutic interventions, it is essential to quantify proprioceptive deficits accurately and sensitively. However, current clinical assessments lack sensitivity due to ordinal scales and suffer from poor reliability and ceiling effects. Robotic technology offers new possibilities to address some of these limitations. Nevertheless, it is important to investigate the psychometric and clinimetric properties of technology-assisted assessments.
We present an automated robot-assisted assessment of proprioception at the level of the metacarpophalangeal joint, and evaluate its reliability, validity, and clinical feasibility in a study with 23 participants with stroke and an age-matched group of 29 neurologically intact controls. The assessment uses a two-alternative forced choice paradigm and an adaptive sampling procedure to identify objectively the difference threshold of angular joint position.
Results revealed a good reliability (ICC(2,1) = 0.73) for assessing proprioception of the impaired hand of participants with stroke. Assessments showed similar task execution characteristics (e.g., number of trials and duration per trial) between participants with stroke and controls and a short administration time of approximately 12 min. A difference in proprioceptive function could be found between participants with a right hemisphere stroke and control subjects (p<0.001). Furthermore, we observed larger proprioceptive deficits in participants with a right hemisphere stroke compared to a left hemisphere stroke (p=0.028), despite the exclusion of participants with neglect. No meaningful correlation could be established with clinical scales for different modalities of somatosensation. We hypothesize that this is due to their low resolution and ceiling effects.
This study has demonstrated the assessment's applicability in the impaired population and promising integration into clinical routine. In conclusion, the proposed assessment has the potential to become a powerful tool to investigate proprioceptive deficits in longitudinal studies as well as to inform and adjust sensorimotor rehabilitation to the patient's deficits.
神经损伤(如中风)后可能会影响本体感觉功能。严重且持续的本体感觉障碍可能与中风后功能恢复不良有关。为了更好地了解它们在恢复过程中的作用,并提高诊断、预后和治疗干预的设计水平,准确、敏感地量化本体感觉缺陷至关重要。然而,由于采用了等级量表,目前的临床评估缺乏敏感性,并且可靠性和上限效应较差。机器人技术为解决其中一些局限性提供了新的可能性。然而,重要的是要研究技术辅助评估的心理计量学和临床计量学特性。
我们提出了一种自动化机器人辅助评估掌指关节水平的本体感觉,并在一项包括 23 名中风患者和 29 名神经功能正常对照者的研究中评估了其可靠性、有效性和临床可行性。该评估使用二择一强迫选择范式和自适应采样程序来客观地确定关节位置角度的差异阈值。
结果显示,评估中风患者受损手的本体感觉的可靠性良好(ICC(2,1)=0.73)。评估结果显示,中风患者和对照组之间的任务执行特征相似(例如,试验次数和每次试验的持续时间),并且管理时间约为 12 分钟。在右半球中风患者和对照组之间可以发现本体感觉功能的差异(p<0.001)。此外,我们观察到与左半球中风相比,右半球中风患者的本体感觉缺陷更大(p=0.028),尽管排除了忽视的患者。我们没有发现与不同感觉模态的临床量表有意义的相关性。我们假设这是由于它们的分辨率低和上限效应。
本研究证明了该评估在受损人群中的适用性,并有望纳入临床常规。总之,该评估具有成为研究本体感觉缺陷的有力工具的潜力,以及为患者的缺陷提供信息并调整感觉运动康复的潜力。