Brain stroke treatments are strongly time-dependent. Indeed, the literature stresses the need for quick diagnosis to guarantee the most effective therapy with the famous motto “time is brain” [1]. Numerically speaking, a crucial goal for strokes is trying to achieve a door-to-needle time shorter than 60 minutes, called The Golden Hour [2], within which patients have the highest probability of a full recovery. This article presents a prototype of a Smart Helmet, a wearable device originally introduced in [3], [4], thought to be employed on site, to efficiently recognize and detect a brain stroke in a patient when the first aid medical team arrives. This work presents two different but complementary approaches: signal-processing-based and electromagnetic (EM). The former aims at outputting a two-level diagnosis: the presence (or not) of a stroke and (if it is present) of which type (ischemic or hemorrhagic), while the latter provides an accurate imaging of the brain that must be interpreted by medical staff. Both approaches are analyzed and compared, showing their strengths and highlighting their weaknesses.

中文翻译：

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通过可穿戴智能头盔早期检测中风的两种方法：信号处理与电磁学

脑卒中治疗具有很强的时间依赖性。事实上，文献强调了快速诊断的必要性，以保证最有效的治疗，其著名的座右铭是“时间就是大脑”[1]。从数字上讲，中风治疗的一个关键目标是尝试实现小于 60 分钟的上门到针时间，称为黄金时段 [2]，在此期间患者完全康复的可能性最高。本文介绍了智能头盔的原型，这是一种最初在 [3]、[4] 中介绍的可穿戴设备，被认为可以在现场使用，以便在急救医疗团队到达时有效识别和检测患者的脑中风。这项工作提出了两种不同但互补的方法：基于信号处理和电磁 (EM)。前者旨在输出两级诊断：中风的存在（或不存在）以及（如果存在）属于哪种类型（缺血性或出血性），而后者提供了必须由医务人员解释的大脑的准确成像。对这两种方法进行了分析和比较，展示了它们的优点并突出了它们的缺点。