Design of gesture recognition system based on capacitive sensing

GE Haijiang

doi:10.13873/J.1000-9787(2020)04-0080-03

Chinese

您当前的位置：

首页 >

文章列表页 >

Design of gesture recognition system based on capacitive sensing

更新时间：2025-09-11

- Design of gesture recognition system based on capacitive sensing
- Issue 4, Pages: 80-82(2020)
- 作者机构：
  
  1. 浙江工业大学计算机科学与技术学院
  2. 杭州职业技术学院信息工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2020)04-0080-03
  CLC： TP212;TP391.41
- Published：2020
- 稿件说明：
移动端阅览
GE Haijiang. Design of gesture recognition system based on capacitive sensing[J]. 2020, (4): 80-82.
DOI：

GE Haijiang. Design of gesture recognition system based on capacitive sensing[J]. 2020, (4): 80-82. DOI： 10.13873/J.1000-9787(2020)04-0080-03.

摘要

研究了一种基于电容式传感器FDC2214的手势识别系统。为提高手势识别的准确率

设计了基于手型分布的电容感应测试方法

提出了多通道传感器的数据采集策略;在手势训练和识别算法设计上

采用冒泡排序法来优化采集的手势数据

并对新、旧数据进行Delta差值和绝对值的累加操作

获得权值最小的识别手势。该手势识别装置分别在猜拳和划拳游戏中经过百余次的实验测试

猜拳游戏的识别成功率为100%

划拳游戏的识别成功率达99. 2%以上

且两种游戏的单个手势的识别时间不超过427. 9 ms

达到了较好的实时手势识别效果。

Abstract

A gesture recognition system based on capacitive sensor FDC2214 is studied. In order to improve the accuracy of gesture recognition

the capacitance induction test method based on hand distribution is designed and the data acquisition strategy of multi-channel sensor is proposed. In the design of gesture training and recognition algorithm

bubble sorting method is proposed to optimize acquired gesture data. Using the method of the Delta difference operation of the new and old data and the absolute value accumulating

the gesture with the smallest weight is obtained. Gesture recognition device is tested for hundreds of times in the guessing and rowing games

respectively. The recognition success rate of the guessing games is 100 %

the recognition success rate of the rowing games is over 99. 2 %

and the recognition time of a single gesture is not more than 427. 9 ms

which achieves better real-time gesture recognition effect.

关键词

Keywords

references

Views

383

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Design and fabrication of flexible pressure sensors for motion monitoring

Research on sEMG gesture recognition based on DenseNet and multidomain features fusion

Fine-grained finger motion recognition algorithm based on wearable devices

Design of capacitive 3D flexible tactile sensing array system

Gesture recognition based on multi-channel surface electromyography sensor

Related Author

ZHANG Binzhen

ZHAO Kaiming

LIU Yanchen

ZHANG Jie

ZHOU Yang

QU Ningyu

GUO Yina

LIAN Dashan

Related Institution

School of Sport and Physical Education,North University of China

National Key Laboratory of Extreme Environment Optoelectronic Dynamic Testing Technology and Instrument,North University of China

School of Electronic Information Engineering,Taiyuan University of Science and Technology

School of Computer Science and Artificial Intelligence,Foshan University

School of Electronic,Electrical,and Communication Engineering,University of Chinese Academy of Sciences

⁰