涂亚庆,陈鹏,陈宝欣,童俊平,赵运勇.基于离散特征的跌倒检测智能方法及应用[J].仪器仪表学报,2017,38(3):629-634
基于离散特征的跌倒检测智能方法及应用
Intelligent fall detection method based on discrete feature and its application
  
DOI:
中文关键词:  跌倒检测  离散特征  智能方法
英文关键词:fall detection  discrete feature  intelligent method
基金项目:国家自然科学基金(61271449,61302175)、重庆市自然科学重点基金(CSTC2015jcyjBX0017)项目资助基于离散特征的跌倒检测智能方法及应用
作者单位
涂亚庆 后勤工程学院后勤信息与军事物流工程系重庆401331 
陈鹏 后勤工程学院后勤信息与军事物流工程系重庆401331 
陈宝欣 后勤工程学院后勤信息与军事物流工程系重庆401331 
童俊平 重庆市软汇科技有限公司重庆400039 
赵运勇 重庆市软汇科技有限公司重庆400039 
AuthorInstitution
Tu Yaqing Military Logistics & Information Engineering Department, Logistical Engineering University, Chongqing 401331, China 
Chen Peng Military Logistics & Information Engineering Department, Logistical Engineering University, Chongqing 401331, China 
Chen Baoxin Military Logistics & Information Engineering Department, Logistical Engineering University, Chongqing 401331, China 
Tong Junping Chongqing Ruanhui Technology Co., Ltd, Chongqing 400039, China 
Zhao Yunyong Chongqing Ruanhui Technology Co., Ltd, Chongqing 400039, China 
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中文摘要:
      随着人口老龄化现象加剧,对老年人跌倒的检测与报警越来越重要。为提高跌倒检测的准确率,提出一种基于离散特征的跌倒检测智能方法。通过对人体运动数据的分析,提出7类人体运动特征;并建立了以BP神经网络为基础的跌倒检测模型,将提取的离散特征作为模型的输入,模型的输出作为跌倒检测结果;通过对模型的学习与训练后,实现跌倒检测。方法验证和产品应用结果表明:采用基于离散特征的跌倒检测智能方法能够有效地区分跌倒与非跌倒,提高了跌倒检测正确率,降低了误报率和漏报率。
英文摘要:
      As the population aging is aggravated, the detection and alarm of falls in elderly people are becoming more and more important. In order to improve the accuracy of fall detection, an intelligent fall detection method based on discrete feature is proposed. Through analyzing the human motion data, seven kinds of discrete features of human motion are proposed. A fall detection model based on BP neural network is established. The extracted discrete features are used as the inputs of the fall detection model, and the output of the model is the result of fall detection. Through the learning and training of the model, fall detection is achieved. The method verification and product application results indicate that the intelligent fall detection method based on discrete features can effectively distinguish fall and non fall, improve the fall detection accuracy and reduce the false alarm rate and missing alarm rate.
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