Timely treatment of stroke is critical to minimize brain damage. Therefore, efforts are being made to educate the public on detecting stroke symptoms, e.g., face, arms, and speech test (FAST). In this position paper, we propose to perform the arm weakness test using the integrated video tracking from an iPhone - some general tests to assess the tracking quality and discuss potential critical points. The test has been performed on 4 stroke patients. The result is compared with the report of the clinician. Although presenting some limitations, the system proved to be able to detect arm weakness as a symptom of stroke. We envisage that introducing a portable body tracking system in such clinical tests will provide advantages in terms of objectivity, repeatability, and the possibility to record and compare groups of patients.

翻译：及时治疗中风对于最大程度减少脑损伤至关重要。因此，社会各界正致力于教育公众识别中风症状，例如面部、手臂和语言测试（FAST）。在本立场论文中，我们提出利用iPhone内置的视频追踪系统进行手臂无力测试，通过若干常规测试评估追踪质量并讨论潜在关键问题。该测试已在4名中风患者身上进行，结果与临床医生的报告进行了对比。尽管存在一定局限性，但该系统被证实能够检测出作为中风症状的手臂无力。我们预期，在此类临床测试中引入便携式身体追踪系统将在客观性、可重复性以及记录和比较患者群体方面提供优势。