论文标题
使用智能手表进行中风患者的上限自动运动评估
Towards Stroke Patients' Upper-limb Automatic Motor Assessment Using Smartwatches
论文作者
论文摘要
在康复情景中评估身体状况是一个具有挑战性的问题，因为它涉及人类活动识别（HAR）和运动学分析方法。此外，不受约束的康复场景的困难增加了，这些情况更接近实际用例。特别是，我们的目的是为使用智能手表的中风患者设计上LIMB评估管道。我们专注于HAR任务，因为它是评估管道的第一部分。我们的主要目标是自动检测并识别受FUGL-MEYER评估量表启发的四个关键运动，这些运动均在受约束和不受约束的情况下进行。除了应用程序协议和数据集外，我们还提出了两种检测和分类基线方法。我们认为，拟议的框架，数据集和基线结果将有助于促进这一研究领域。
Assessing the physical condition in rehabilitation scenarios is a challenging problem, since it involves Human Activity Recognition (HAR) and kinematic analysis methods. In addition, the difficulties increase in unconstrained rehabilitation scenarios, which are much closer to the real use cases. In particular, our aim is to design an upper-limb assessment pipeline for stroke patients using smartwatches. We focus on the HAR task, as it is the first part of the assessing pipeline. Our main target is to automatically detect and recognize four key movements inspired by the Fugl-Meyer assessment scale, which are performed in both constrained and unconstrained scenarios. In addition to the application protocol and dataset, we propose two detection and classification baseline methods. We believe that the proposed framework, dataset and baseline results will serve to foster this research field.
