Machine-learned wearable sensors for real-time hand-motion recognition:toward practical applications

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外文摘要：Soft electromechanical sensors have led to a new paradigm of electronic devices for novel motion-based wearable applications in our daily lives.However,the vast amount of random and unidentified signals generated by complex body motions has hindered the precise recognition and practical application of this technology.Recent advancements in artificial-intelligence technology have enabled significant strides in extracting features from massive and intricate data sets,thereby presenting a breakthrough in utilizing wearable sensors for practical applications.Beyond traditional machine-learning techniques for classifying simple gestures,advanced machine-learning algorithms have been developed to handle more complex and nuanced motion-based tasks with restricted training data sets.Machine-learning techniques have improved the ability to perceive,and thus machine-learned wearable soft sensors have enabled accurate and rapid human-gesture recognition,providing real-time feedback to users.This forms a crucial component of future wearable electronics,contributing to a robust human-machine interface.In this review,we provide a comprehensive summary covering materials,structures and machine-learning algorithms for hand-gesture recognition and possible practical applications through machine-learned wearable electromechanical sensors.

外文关键词：

wearable sensorsoft electronicsartificial intelligencemachine learninghuman-machine interfacesgesture recognition

作者：

Kyung RokPyun、Kangkyu Kwon、Myung Jin Yoo、Kyun Kyu Kim、Dohyeon Gong、Woon-Hong Yeo、Seungyong Han、Seung Hwan Ko

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作者单位：

Department of Mechanical Engineering,Seoul National University,Seoul 08826,South Korea

IEN Center for Human-Centric Interfaces and Engineering,Institute for Electronics and Nanotechnology,Georgia Institute of Technology,Atlanta,GA 30332,USA

School of Electrical and Computer Engineering,Georgia Institute of Technology,Atlanta,GA 30332,USA

Departmentof Chemical Engineering,Stanford University,Stanford,CA 94305,USA

Department of Mechanical Engineering,Ajou University,Suwon-si 16499,South Korea

George W.Woodruff School of Mechanical Engineering,Georgia Institute of Technology,Atlanta,GA 30332,USA

Institute of Advanced Machinery and Design(SNU-IAMD),Seoul National University,Seoul 08826,South Korea

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基金：

National Research Foundation of KoreaNational Research Foundation of Korea

项目编号：

2021R1A2B5B03001691RS-2023-00208052

出版年：

2024

DOI：

10.1093/nsr/nwad298

国家科学评论(英文版)

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ISSN：

年,卷(期)：2024.11(2)

参考文献量184