工件(错误)
可穿戴计算机
材料科学
生物医学工程
喉部
医学
计算机科学
人工智能
外科
嵌入式系统
作者
Xiaopeng Yang,Menglun Zhang,Shaobo Gong,Mingchao Sun,Mengying Xie,Pengfei Niu,Wei Pang
标识
DOI:10.1002/admt.202201043
摘要
Abstract Assessment of the cough severity is essential when dealing with respiratory diseases such as chronic obstructive pulmonary disease and COVID‐19. Although a few wearable devices have been reported for cough detection, they mostly rely on microphones, accelerometers, or throat‐fixed flexible sensors, which suffer from key issues including privacy disclosure and speech/motion artifacts. This study presents a chest‐laminated electronic skin (e‐skin) for reliable cough detection. Mixed dumbbell‐like networks and through‐holes are engineered on hard‐to‐stretch composite films for high stretching force sensitivity and sweat permeation, respectively. The e‐skin can effectively reduce speech‐signal and motion artifacts owing to firm adhesion and conformal contact with the chest even on sweaty skin. Experimental results show that the specificity for cough identification is as high as 99.75% through machine learning of automated acoustic analysis, even in the presence of hard‐to‐distinguish daily activities such as throat clearing. The developed chest‐laminated e‐skin is a simple, comfortable, yet reliable method to detect cough for the primary diagnosis of respiratory diseases by extracting subtle acoustic information from cough.
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