Deep-Learning-Assisted Noncontact Gesture-Recognition System for Touchless Human-Machine Interfaces

Hao Zhou; Wei Huang; Zhuo XiaoShichuan ZhangWangzhan LiJinhui HuTianxing FengJing WuPengcheng Zhuand Yanchao Mao

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Deep-Learning-Assisted Noncontact Gesture-Recognition System for Touchless Human-Machine Interfaces

机译：Deep-Learning-Assisted Noncontact Gesture-Recognition System for Touchless Human-Machine Interfaces

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Human-machine interfaces (HMIs) play important role in the communicationbetween humans and robots. Touchless HMIs with high hand dexterityand hygiene hold great promise in medical applications, especially during thepandemic of coronavirus disease 2019 (COVID-19) to reduce the spread ofvirus. However, current touchless HMIs are mainly restricted by limited typesof gesture recognition, the requirement of wearing accessories, complexsensing platforms, light conditions, and low recognition accuracy, obstructingtheir practical applications. Here, an intelligent noncontact gesture-recognitionsystem is presented through the integration of a triboelectric touchlesssensor (TTS) and deep learning technology. Combined with a deep-learningbasedmultilayer perceptron neural network, the TTS can recognize 16different types of gestures with a high average accuracy of 96.5%. The intelligentnoncontact gesture-recognition system is further applied to controla robot for collecting throat swabs in a noncontact mode. Compared withpresent touchless HMIs, the proposed system can recognize diverse complexgestures by utilizing charges naturally carried on human fingers without theneed of wearing accessories, complicated device structures, adequate lightconditions, and achieves high recognition accuracy. This system could provideexciting opportunities to develop a new generation of touchless medicalequipment, as well as touchless public facilities, smart robots, virtual reality,metaverse, etc.

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来源
《Advanced functional materials》 |2022年第49期|2208271.1-2208271.10|共10页
作者
Hao Zhou; Wei Huang; Zhuo XiaoShichuan ZhangWangzhan LiJinhui HuTianxing FengJing WuPengcheng Zhuand Yanchao Mao;
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Key Laboratory of Materials PhysicsMinistry of EducationSchool of Physics and MicroelectronicsZhengzhou UniversityZhengzhou 450001, P. R. China;

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原文格式 PDF
正文语种英语
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deep learning; human-machine interfaces; noncontact gesture recognitions; triboelectric sensors;

Deep-Learning-Assisted Noncontact Gesture-Recognition System for Touchless Human-Machine Interfaces

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