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首页> 外文期刊>Sensors Journal, IEEE >Mobile Human Airbag System for Fall Protection Using MEMS Sensors and Embedded SVM Classifier
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Mobile Human Airbag System for Fall Protection Using MEMS Sensors and Embedded SVM Classifier

机译:使用MEMS传感器和嵌入式SVM分类器的移动人气囊系统,用于坠落防护

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摘要

This paper introduces a mobile human airbag system designed for fall protection for the elderly. A Micro Inertial Measurement Unit ( muIMU) of 56 mm times 23 mm times 15 mm in size is built. This unit consists of three dimensional MEMS accelerometers, gyroscopes, a Bluetooth module and a Micro Controller Unit (MCU). It records human motion information, and, through the analysis of falls using a high-speed camera, a lateral fall can be determined by gyro threshold. A human motion database that includes falls and other normal motions (walking, running, etc.) is set up. Using a support vector machine (SVM) training process, we can classify falls and other normal motions successfully with a SVM filter. Based on the SVM filter, an embedded digital signal processing (DSP) system is developed for real-time fall detection. In addition, a smart mechanical airbag deployment system is finalized. The response time for the mechanical trigger is 0.133 s, which allows enough time for compressed air to be released before a person falls to the ground. The integrated system is tested and the feasibility of the airbag system for real-time fall protection is demonstrated.
机译:本文介绍了一种用于老年人跌倒保护的移动式人用安全气囊系统。制作了尺寸为56毫米x 23毫米x 15毫米的微惯性测量单元(muIMU)。该单元由三维MEMS加速度计,陀螺仪,蓝牙模块和微控制器单元(MCU)组成。它记录了人类的运动信息,并且通过使用高速相机对跌倒进行分析,可以通过陀螺仪阈值确定横向跌倒。建立包括跌倒和其他正常运动(步行,跑步等)的人体运动数据库。使用支持向量机(SVM)训练过程,我们可以使用SVM过滤器成功分类跌倒和其他正常运动。基于SVM滤波器,开发了用于实时跌倒检测的嵌入式数字信号处理(DSP)系统。此外,智能机械安全气囊展开系统已完成。机械触发器的响应时间为0.133 s,这允许在人跌倒之前有足够的时间释放压缩空气。测试了集成系统,并演示了用于实时跌倒保护的安全气囊系统的可行性。

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