[1]魏文钊,何清波.基于超声波的手势识别设备的研究[J].机械与电子,2018,(05):54-57,61.
 WEI Wenzhao,HE Qingbo.Research on Ultrasound-Based Gesture Recognition Device[J].Machinery & Electronics,2018,(05):54-57,61.
点击复制

基于超声波的手势识别设备的研究
分享到:

《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2018年05期
页码:
54-57,61
栏目:
自动控制与检测
出版日期:
2018-05-24

文章信息/Info

Title:
Research on Ultrasound-Based Gesture Recognition Device
文章编号:
1001-2257(2018)05-0054-04
作者:
魏文钊何清波
(中国科学技术大学精密机械与精密仪器系,安徽 合肥 230026)
Author(s):
WEI Wenzhao HE Qingbo
(Department of Precision Machinery and Precision Instrumentation,University of Science and Technology of China,Hefei 230026, China)
关键词:
超声波 多普勒效应 STM32 频率估计 手势识别
Keywords:
ultrasound doppler effect STM32 frequency estimation gesture recognition
分类号:
TP274.2
文献标志码:
A
摘要:
设计了一套基于主动超声技术的低成本、低功耗的手势识别装置,可以用来实现无接触式的人机交互。采用STM32为主控核心,发射超声波并使用4通道超声性能稳定的麦克风接收经过物体反射后的回波信号。在单片机内使用改进的过零检测法估算回波频率,并将回波的频率和幅值作为手势识别的特征,使用USB或串口传输至上位机。经验证,特征信息可反映用户手在垂直方向和水平方向的运动。
Abstract:
A low-cost and low-power gesture recognition device based on active ultrasound technology is designed to achieve non-contact human-computer interaction. The device uses STM32 as the microcontroller to transmit ultrasound signals to the target and receive the response by 4-channel ultra-stable MEMS microphone. A modified zero-crossing detection method is used to measure frequency on the microcontroller, and the frequency and amplitude of response signal are transmitted as the feature of gesture to upper computer through USB or serial port. The experimental results show that the feature can reflect the movement of target.

参考文献/References:

[1]许金鹏,张亚,吕铁钢,等. 基于MATLAB的静态手势分割与识别研究[J]. 机械与电子,2017,35(9):73-76.
[2]CHEN Y, DING Z, CHEN Y L, et al. Rapid recognition of dynamic hand gestures using leap motion[C]//Information and Automation, 2015 IEEE International Conference on. IEEE, 2015: 1419-1424.
[3]GUPTA S, MORRIS D, PATEL S, et al. Soundwave: using the doppler effect to sense gestures[C]//Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 2012: 1911-1914.
[4]杨晓东, 陈益强,于汉超,等. 面向可穿戴设备的超声波手势识别方法[J]. 计算机科学, 2015, 42(10):20-24.
[5]LI G, ZHANG R, RITCHIE M,et al. Sparsity-driven micro-doppler feature extraction for dynamic hand Gesture recognition[J]. IEEE Transactions on Aerospace and Electronic Systems, 2017.
[6]沈艳林,涂亚庆,刘鹏,等.非整周期采样信号频率估计的频匹配方法[J].仪器仪表学报,2015,36(6): 1221-1226.
[7]邓振淼,刘渝,王志忠. 正弦波频率估计的修正Rife 算法[J]. 数据采集与处理, 2006, 21(4): 473-477.

备注/Memo

备注/Memo:
收稿日期:2018-03-10
基金项目:国家自然科学基金资助项目(51475441)
作者简介:魏文钊(1992-),男,河北邯郸人,硕士研究生,研究方向为电路设计及智能信息处理;何清波(1980-),男,河南濮阳人,副教授,研究方向为机械系统动态监控、诊断与预知性维护等。
更新日期/Last Update: 2018-05-24