振动
数码产品
计算机科学
宽带
信号处理
信号(编程语言)
声学
声传感器
过程(计算)
材料科学
电子工程
工程类
数字信号处理
电气工程
电信
计算机硬件
物理
程序设计语言
操作系统
作者
Jeng‐Hun Lee,Kanghyuk Cho,Kilwon Cho
标识
DOI:10.1002/adma.202209673
摘要
Abstract In the last decade, soft acoustic/vibration sensors have gained tremendous research interest due to their unique ability to detect broadband acoustic/vibration stimuli, potentializing futuristic applications including voice biometrics, voice‐controlled human–machine‐interfaces, electronic skin, and skin‐mountable healthcare devices. Importantly, to benefit most from these sensors, it is inevitable to use machine learning (ML) to process their output signals; with ML, a more accurate and efficient interpretation of original data is possible. This paper is dedicated to offering an overview of recent advances empowering the development of soft acoustic/vibration sensors and their signal processing using ML. First, the key performance parameters of the sensors are discussed. Second, popular transduction mechanisms for the sensors are addressed, followed by an in‐depth overview of each type, covering materials used, structural designs, and sensing performances. Third, potential applications of the sensors are elaborated and fourth, a thorough discussion on ML is conducted, exploring different types of ML, specific ML algorithms suitable for processing acoustic/vibration signals, and current trends in ML‐assisted applications. Finally, the challenges and potential opportunities in soft acoustic/vibration sensor and ML research are revealed to offer new insights into future prospects in these fields.
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