Is it possible to use Kinect sensor for lying position rehabilitation exercise? Kinect V2 versus Azure Kinect

Yehua Shi, Xiaoyi Wang, C. Lau, K. Tong
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Abstract

The availability of low-cost portable depth sensor camera brings opportunity to be applied in home-based rehabilitation exercise for stroke and other chronic disease patients. Kinect V2 seemed not feasible to easily track motion in a lying position, while the latest Microsoft Azure Kinect has improved the sensor. This paper experimentally explores the feasibility of Azure Kinect and Kinect V2 for lying position rehabilitation exercises and evaluate the tracking performance by changing the camera viewing angles. Two healthy subjects performed upper and lower limb rehabilitation exercise trial on the bed according to supine position and lateral position. The Kinect sensor was tested at 6 viewing angles in human body coronal plane and sagittal plane. Subject motion data and video were recorded and evaluated by two Kinect camera systems. The results showed that the hardware improvement such as resolution enhancement and the neural network motion tracking algorithm of the Azure Kinect depth camera led to higher performance in lying body motion recognition than Kinect v2 for most of the viewing angles. In conclusion, Azure Kinect could improve the lying position body tracking accuracy and it has great potential in the field of rehabilitation with lying position exercises.
是否可以使用Kinect传感器进行卧位康复练习?Kinect V2 vs Azure Kinect
低成本便携式深度传感器相机的出现,为中风等慢性疾病患者的居家康复训练提供了应用机会。Kinect V2似乎无法轻松追踪躺着时的运动,而最新的微软Azure Kinect改进了传感器。本文通过实验探索Azure Kinect和Kinect V2进行躺姿康复练习的可行性,并通过改变摄像机视角来评估跟踪性能。2名健康受试者按仰卧位和侧卧位在床上进行上肢和下肢康复运动试验。Kinect传感器在人体冠状面和矢状面6个视角下进行了测试。受试者运动数据和视频由两个Kinect摄像系统记录和评估。结果表明,Azure Kinect深度摄像头的硬件改进,如分辨率增强和神经网络运动跟踪算法,使得在大多数视角下,躺着的身体运动识别性能比Kinect v2更高。综上所述,Azure Kinect可以提高躺姿身体跟踪精度,在躺姿运动康复领域具有很大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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