面向农业智能装备的表面肌电信号识别  

Surface Electromyograph(sEMG)Signal Recognition for Smart Agricultural Equipment

作　　者：孙洪颖 陈龙崇 郑传俊 黄劲龙 陈振国 钟丽芬 SUN Hongying;CHEN Longchong;ZHENG Chuanjun;HUANG Jinlong;CHEN Zhenguo;ZHONG Lifen

机构地区：[1]广东技术师范大学机电学院,广东广州510635

出　　处：《智慧农业导刊》2021年第1期1-5,共5页JOURNAL OF SMART AGRICULTURE

基　　金：广东省本科高校教学质量与教学改革工程建设项目(序号:30);广东省一流本科课程(粤教高函【2020】16号)。

摘　　要：农业智能装备是现代农业重要的发展方向之一,目前视觉、语音等是主要的交互方式,表面肌电信号的识别是当前人工智能与生物医学工程领域的研究热点之一,但肌电信号还较少应用于农业智能装备的交互。文章面向农业智能装备进行了表面肌电信号识别的研究工作,在对卷积神经网络与表面肌电信号识别技术分析的基础上,构建卷积神经网络对肌电信号进行识别,实现对人体动作的识别,探索表面肌电信号新的识别方法,为肌电信号应用于现代农业智能装备提供了技术参考。Smart agricultural equipment is one of the important results of development of modern agriculture.At present,vision and voice are the main methods of interaction.The recognition of sEMG signal is one of the research hotspots in the field of artificial intelligence and biomedical engineering.However,sEMG signal is rarely used in the interaction of smart agricultural equipment.Based on the analysis of convolutional neural network(CNN)and sEMG signal recognition technology,this paper constructs convolutional neural network to recognize the sEMG signal,realizes the recognition of human action,and explores a new recognition method of the sEMG signal,thus providing a technical reference for sEMG signals to be applied to smart agricultural equipment.

关 键 词：卷积神经网络(CNN) 表面肌电信号(sEMG) 农业智能装备 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]