电子学报 ›› 2021, Vol. 49 ›› Issue (1): 85-89.DOI: 10.12263/DZXB.20200069

• 学术论文 • 上一篇    下一篇

基于软件定义智能的睡眠动作识别

汪成亮, 郑诚, 曾卓   

  1. 重庆大学计算机学院, 重庆 400044
  • 收稿日期:2020-01-09 修回日期:2020-05-12 出版日期:2021-01-25 发布日期:2021-01-25
  • 通讯作者: 汪成亮
  • 作者简介:郑诚 男,1995年4月出生,江西南昌人.重庆大学在读硕士研究生,主要研究方向为智能环境、物联网.E-mail:zhengchengyy@qq.com
  • 基金资助:
    国家自然科学基金(No.61672115);重庆市研究生科研创新专项(No.CYS19049)

Sleep Action Recognition Based on Software-Defined Intelligence

WANG Cheng-liang, ZHENG Cheng, ZENG Zhuo   

  1. College of Computer Science and Technology, Chongqing University, Chongqing 400044, China
  • Received:2020-01-09 Revised:2020-05-12 Online:2021-01-25 Published:2021-01-25
  • Supported by:
     

摘要: 基于软件定义智能层次化模型设计了一种睡眠动作识别系统,该系统可通过规则推理来应对智能环境中的各种变化因素.设计了一种时间队列实时提取动作特征来训练模型,提出了一种规则提取算法从该模型中提取系统所需规则.该系统基于这些规则可识别9种睡眠动作,每种动作的识别精确率均可达到96%以上,总识别准确率达到98.9%,且比其它系统适应性更强.实验结果表明,该系统通过更新规则可快速应对节点位置、节点数量和用户需求的变化.

 

关键词: 智能环境, 软件定义智能, 睡眠动作识别, 规则推理

Abstract: Based on the hierarchical model of SDI(Software-Defined Intelligence),a system for action recognition during sleep is designed to deal with various changing factors in smart environment through rule-based reasoning.A time queue is designed to extract the characteristics of actions in real-time to train the model,and a rule extraction algorithm is proposed to extract the rules required by the system from the model.Depending on these rules,the proposed system can recognize nine types of sleep actions:the recognition precision of each type can exceed 96%;the total recognition accuracy can reach 98.9%.Importantly,it has more robust adaptability than other systems.Experimental results show that the system can update rules for quickly adapting to changes in node position,the number of nodes,and user requirements.

Key words: smart environment, software-defined intelligence, sleep action recognition, rule-based reasoning

中图分类号: