| 摘要: |
| 用户睡眠状态下的睡眠行为识别是睡眠质量检测的基础.提出了一种非觉察式的睡眠行为识别技术,该技术使用薄膜压力传感器作为采集设备,根据统计模式识别理论建立用户个性化模型,并通过最大相似度算法识别用户行为.其优点在于系统运行时不会干扰用户正常的生活,并且部署简单,安全性高.实现了基于该理论的原型系统SmartSleepDetector.实验结果表明,系统睡眠行为的识别正确率达到80%以上.该理论方法具备可行性及实用价值. |
| 关键词: 睡眠行为 压力传感器 活动检测 行为识别 |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60803044, 60903125 (国家自然科学基金); the
National High-Tech Research and Development Plan of China under Grant No.2009AA011903 (国家高技术研究发展计划(863)); the
Program for New Century Excellent Talents in University of China under Grant No.NCET-09-0079 (新世纪优秀人才支持计划); the
Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No.20070699014 (教育部高等学校博士学科点专项科研基金); the Shaanxi Provincial Natural Science Basic Research Program of China under Grant No.2010JM8033 (陕西省自然科学基础研究计划) |
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| Unobtrusive Method for Sleeping Behavior Recognition in Bed |
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MIAO Qiang, ZHOU Xing-She, YU Zhi-Wen, NI Hong-Bo
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School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, China
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| Abstract: |
| Recognition of movements during sleeping is the foundation of sleep quality assessment. This paper proposes an unobtrusive system for activity detection in bed, which collects data by using force sensors, develops user’s individualized model according to the theory of statistical pattern recognition, and identifies the user’s activity through algorithm of maximum similarity at last. This system does not interfere with the normal life and is easy to deploy. The prototype was implemented and the results showed that the recognition accuracy of sleeping behaviors is above 80%, which illustrates the feasibility and practical value of the system. |
| Key words: sleeping behavior, force sensor, activity detection, behavior recognition |
