家电科技 ›› 2023, Vol. 0 ›› Issue (6): 38-41.doi: 10.19784/j.cnki.issn1672-0172.2023.06.005

• 论文 • 上一篇    下一篇

基于CSI特征信息的人体运动检测方法

付雄, 李云涛, 尚靖, 陈峰峰   

  1. 四川虹美智能科技有限公司 四川绵阳 621011
  • 出版日期:2023-12-01 发布日期:2024-04-17
  • 通讯作者: 李云涛,E-mail:yuntao.li@changhong.com。
  • 作者简介:付雄,硕士学位。研究方向:机器学习及智能检测。地址:四川省绵阳市涪城区四川虹美智能科技有限公司。E-mail:xiong.fu@changhong.com。

Human motion detection method based on CSI feature information

FU Xiong, LI Yuntao, SHANG Jing, CHEN Fengfeng   

  • Online:2023-12-01 Published:2024-04-17

摘要: 针对人机交互智能化需求的日益增长,基于家电传感设备的人体检测方法便捷性差且成本高的问题,提出一种基于Wi-Fi信道状态信息的人体检测技术,充分运用家电Wi-Fi模组实现无接触检测。该方法利用子载波幅值信息,在算法离线阶段进行离群值过滤,提取静态环境相关特征,训练指纹库进行参数存储;在在线阶段提取实时信号幅值,与训练阶段阈值对比输出有人或无人结果。该方法提取时域和子载波域多类特征信息,能够实现人体运动,无人和人体微动的区分检测,在真实场景测试中达到了良好的准确度,对智能化检测在家电中的应用具有一定参考价值。

关键词: 信道状态信息, 子载波, 人体检测, Wi-Fi

Abstract: In response to the increasing demand for intelligent human-computer interaction and the problem of poor convenience and high cost of human detection methods based on sensing devices of home appliance, a human detection technology based on Wi-Fi channel state information is proposed, which fully utilizes home appliance Wi-Fi modules to achieve contactless detection. This method utilizes subcarrier amplitude information to filter outliers and extract static environment related features in the offline stage of the algorithm. It trains a fingerprint library for parameter storage, and extracts real-time signal amplitude in the online stage. The results are compared with the training stage threshold to output results with or without people. This method extracts multiple types of feature information in the time domain and subcarrier domain, and can achieve differential detection of human motion, unmanned and human micro motion. It has achieved accuracy in real-world experiments and has certain value for the application of intelligent detection in household appliances.

Key words: Sichuan Hongmei Intelligent Technology Co., Ltd. Mianyang 621011

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