KINECAL

The field of human action recognition has made great strides in recent years, much helped by the availability of a wide variety of datasets that use Kinect to record human movement. Conversely, progress towards using Kinect in clinical practice has been hampered by the lack of appropriate data. In particular, datasets that contain clinically significant movements and appropriate metadata. This paper proposes a dataset to address this issue, namely KINECAL. It contains the recordings of 90 individuals carrying out 11 movements, commonly used in the clinical assessment of balance. The dataset contains relevant metadata, including clinical labelling, falls history and postural sway metrics. In addition, the recordings were made in both the lab and in informal settings.

近年来，人类动作识别领域取得了长足的进步，这一成就得益于大量使用 Kinect 记录人类动作的数据集的广泛可用性。相反，在临床实践中应用 Kinect 的进展受到了缺乏适当数据的制约，尤其是那些包含具有临床意义动作和相应元数据的集合。本文提出了一种数据集以解决这一问题，即 KINECAL 数据集。该数据集包含了 90 名个体进行 11 种运动的记录，这些运动在平衡的临床评估中普遍应用。数据集包含了相关的元数据，包括临床标注、跌倒史和姿势摇摆指标。此外，这些记录是在实验室和非正式环境中完成的。