基于FDC2214电容传感器的手势识别装置的设计与实现

巢湖学院学报 ›› 2018, Vol. 20 ›› Issue (6): 84-90.

基于FDC2214电容传感器的手势识别装置的设计与实现

本装置以STM32 单片机作为控制核心，实现了基于FDC2214 为主模块的手势训练与识别。利用四块极板进行比例区域划分判别，从而利于手势判定，减少随机性误差，增强可靠性。装置中使用卡尔曼滤波算法进行波形滤波处理，缓解测量波形的毛躁并采用冒泡排序法等算法，判断差异值，加强测量精度。搭建了手势测试平台，并进行了相应的数据测试，结果表明所设计的手势识别装置能够训练、判别手势，完成题目的要求。

安徽师范大学皖江学院，安徽芜湖 241000

收稿日期:2018-09-01 出版日期:2018-11-25 发布日期:2018-11-25
作者简介:张辉（1984-），男，江苏泰兴人。安徽师范大学皖江学院电子工程系，讲师。研究方向：单片机、嵌入式系统。
基金资助:
安徽省高校优秀青年人才支持计划一般项目（项目编号：gxyq2017140）

DESIN AND IMPLEMENTTATION OF GESTURE RECOGNITION DEVICE BASED ON FDC2214 CAPACITIVE SENSER

This device takes STM32 MCU as the control core and realizes gesture training and recognition based on FDC2214 as the main module. The four plates are used to divide the proportional region for judgment, which is helpful for gesture judgment,reducing randomness error and enhancing reliability. In the device, Kalman filter algorithm is used for waveform filtering processing to alleviate the roughness of waveform measurement and bubble sorting algorithm is adopted to judge the difference value and strengthen the measurement accuracy. A gesture testing platform is built and corresponding data is tested. The results show that the designed gesture recognition device can train and distinguish gestures and complete the requirements of the question.

Wanjiang College of Anhui Normal University, Wuhu Anhui 241000

Received:2018-09-01 Online:2018-11-25 Published:2018-11-25

摘要/Abstract

摘要： 本装置以STM32 单片机作为控制核心，实现了基于FDC2214 为主模块的手势训练与识别。利用四块极板进行比例区域划分判别，从而利于手势判定，减少随机性误差，增强可靠性。装置中使用卡尔曼滤波算法进行波形滤波处理，缓解测量波形的毛躁并采用冒泡排序法等算法，判断差异值，加强测量精度。搭建了手势测试平台，并进行了相应的数据测试，结果表明所设计的手势识别装置能够训练、判别手势，完成题目的要求。

关键词: STM32, FDC2214, 卡尔曼滤波, 手势识别

Abstract: This device takes STM32 MCU as the control core and realizes gesture training and recognition based on FDC2214 as the main module. The four plates are used to divide the proportional region for judgment, which is helpful for gesture judgment,reducing randomness error and enhancing reliability. In the device, Kalman filter algorithm is used for waveform filtering processing to alleviate the roughness of waveform measurement and bubble sorting algorithm is adopted to judge the difference value and strengthen the measurement accuracy. A gesture testing platform is built and corresponding data is tested. The results show that the designed gesture recognition device can train and distinguish gestures and complete the requirements of the question.

Key words: STM32, FDC2214, Kalman filtering, gesture recognition

中图分类号:

TP391.4

张辉, 卜雯意, 施豪. 基于FDC2214电容传感器的手势识别装置的设计与实现[J]. 巢湖学院学报, 2018, 20(6): 84-90.

ZHANG Hui, BU Wen-yi, SHI Hao. DESIN AND IMPLEMENTTATION OF GESTURE RECOGNITION DEVICE BASED ON FDC2214 CAPACITIVE SENSER[J]. Journal of Chaohu University, 2018, 20(6): 84-90.