农业机械学报2024，Vol.55Issue(6)：451-458,8.DOI:10.6041/j.issn.1000-1298.2024.06.046
基于柔性应变传感器的数据手套手势识别研究
Data Glove Gesture Recognition Based on Flexible Strain Sensors
摘要
Abstract
In response to the problems of low recognition rate and unstable response in traditional gesture recognition systems,a flexible strain sensor data glove gesture recognition system was developed,which included flexible sensors,signal acquisition systems,and gesture recognition algorithms.The system can accurately capture the motion information of each finger joint,and had the characteristics of high degree of freedom,low cost and high recognition rate.Carbon black(CB)and carbon nanotubes(CNTs)were doped into soft silica gel,and a resistive sensor with good linearity and high sensitivity was designed by extension technology.The experimental results showed that the sensor had good static and dynamic response characteristics,and the sensor calibration was completed.Using multiple flexible sensors to prepare data gloves and build a signal acquisition system,a gesture recognition method combining BP neural network and template matching technology was further proposed to improve the recognition rate of similar gestures,and the recognition rate of the algorithm was 98.5％.Gesture recognition experiments were carried out for different groups of people.The results showed that the accuracy of the gesture recognition system reached 92.8％,and the response time was about 40 ms.The data glove had good application potential.关键词
柔性传感器/模板匹配法/BP神经网络/手势识别/数据手套Key words
flexible sensors/template matching method/BP neural network/gesture recognition/data glove分类
信息技术与安全科学引用本文复制引用
朱银龙,沈宏骏,吴杰,王旭,刘英..基于柔性应变传感器的数据手套手势识别研究[J].农业机械学报,2024,55(6):451-458,8.基金项目
国家自然科学基金项目(51305209)、江苏省高等学校自然科学研究项目(18KJA4600050、21KJB460010)、江苏省"六大人才高峰"高层次人才项目(GDZB-024)和机器人学国家重点实验室开放项目(2018-O16) （51305209）
