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| 基于时序分析的人体摔倒预测方法 | |
| 引用本文： | 佟丽娜,宋全军,葛运建.基于时序分析的人体摔倒预测方法[J].模式识别与人工智能,2012,25(2):273-279. |
| 作者姓名： | 佟丽娜 宋全军 葛运建 |
| 作者单位： | 1。中国科学院合肥智能机械研究所机器人传感器与人机交互实验室合肥230031 2。中国科学技术大学信息科学与技术学院自动化系合肥230027 |
| 基金项目： | 国家自然科学基金项目(No.60874097,60875047);国家863计划项目(No.2008AA040202,2006AA040204);安徽省优秀青年科技基金项目(No.10040606Y06)资助 |
| 摘 要： | 提出一种基于人体动作状态序列时序分析法的人体摔倒预测方法。融合特征部位加速度信息为时间序列，选取摔倒过程中人体与低势物体碰撞前的过程序列段作为样本训练隐马尔可夫模型(HMM)，通过分析输入序列与HMM的匹配程度实时分析当前时刻人体摔倒的风险。实验证明该方法取得良好的预测效果，并且可有效区分摔倒过程与其它日常生活行为过程。 |
| 关 键 词： | 摔倒预测 时间序列 隐马尔可夫模型 |
| 收稿时间： | 2011-01-07 |
Time Series Analysis Based Human Fall Prediction Method |
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| TONG Li-Na , SONG Quan-Jun , GE Yun-Jian.Time Series Analysis Based Human Fall Prediction Method[J].Pattern Recognition and Artificial Intelligence,2012,25(2):273-279. | |
| Authors: | TONG Li-Na SONG Quan-Jun GE Yun-Jian |
| Affiliation: | 1.Laboratory of Robot Sensor and Human-Machine Interaction,Institute of Intelligent Machines,Chinese Academy of Sciences,Hefei 230031 2.Department of Automation,School of Information Science and Technology,University of Science and Technology of China,Hefei 230027 |
| Abstract: | A method for human fall prediction based on time series of human action states is proposed.Firstly,the acceleration time series in characteristic body region is got by information fusion procedure.Secondly,the segments before the collision of body with lower objects in fall processes is chosen as samples to train hidden Markov model(HMM).Then,the current-time fall risk is analyzed by the real-time matching degree between input series and HMM.The experimental result shows that the proposed method gets good result in predicting falls,and the fall events and other daily life activities can be distinguished effectively by it. |
| Keywords: | Fall Prediction Time Series Hidden Markov Model |
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