Two ways for early detection of a stroke through a wearable smart helmet: Signal processing vs. electromagnetism

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.