Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy.
Istituto Auxologico Italiano, IRCCS, Department of Neurology and Neurorehabilitation, S. Giuseppe Hospital, Strada Luigi Cadorna 90, 28824 Piancavallo, Italy.
Sensors (Basel). 2022 Jun 29;22(13):4910. doi: 10.3390/s22134910.
The aim of this review was to present an overview of the state of the art in the use of the Microsoft Kinect camera to assess gait in post-stroke individuals through an analysis of the available literature. In recent years, several studies have explored the potentiality, accuracy, and effectiveness of this 3D optical sensor as an easy-to-use and non-invasive clinical measurement tool for the assessment of gait parameters in several pathologies. Focusing on stroke individuals, some of the available studies aimed to directly assess and characterize their gait patterns. In contrast, other studies focused on the validation of Kinect-based measurements with respect to a gold-standard reference (i.e., optoelectronic systems). However, the nonhomogeneous characteristics of the participants, of the measures, of the methodologies, and of the purposes of the studies make it difficult to adequately compare the results. This leads to uncertainties about the strengths and weaknesses of this technology in this pathological state. The final purpose of this narrative review was to describe and summarize the main features of the available works on gait in the post-stroke population, highlighting similarities and differences in the methodological approach and primary findings, thus facilitating comparisons of the studies as much as possible.
本次综述旨在通过对现有文献的分析，介绍使用 Microsoft Kinect 摄像机评估脑卒中后个体步态的最新技术。近年来，已有多项研究探索了这种 3D 光学传感器作为一种易于使用且非侵入性的临床测量工具，用于评估多种疾病中的步态参数的潜力、准确性和有效性。特别关注脑卒中个体，一些现有的研究旨在直接评估和描述他们的步态模式。相比之下，其他研究则侧重于 Kinect 测量值与金标准参考（即光电系统）的验证。然而，参与者、测量方法、研究目的的非均一性特征使得难以充分比较结果。这导致了对这种技术在这种病理状态下的优缺点存在不确定性。本次叙述性综述的最终目的是描述和总结脑卒中后人群步态研究的主要特点，突出方法学方法和主要发现方面的异同，从而尽可能地促进研究之间的比较。
