中文摘要：

针对移动终端设备的硬件局限性,研究了一种基于卡尔曼滤波的非特定人体状态识别算法,实时判断人体的运动、静止、状态转换情况.将装有三轴加速度传感器的蓝牙模块放置在人体的胸部,获得运动时的三维加速度信号.结合人体运动状态的特征和加速度信号变化的相关性,采用信号矢量幅值变化量的函数进行卡尔曼滤波,对人体状态进行判断.实验结果表明,该算法在运算和存储能力有限的移动设备上取得了较好的性能.

英文摘要：

Adapting to the limited resource of mobile device, a human state recognition algorithm based on Kalman filter was proposed, which could identify dynamic, static and state transition in real time. The Bluetooth module with a triaxial accelerometer was placed on the chest of body to collect three- dimensional acceleration data. The characteristic of human activity was associated with the features of the accelerometer signal, so the function of change of the signal vector magnitude （SVM） was processed by Kalman filter to identify human state. Experiment results show that the algorithm achieves high accuracy in identification of postural transition, meanwhile, the algorithm has displayed better performance with little overhead on the smartphone.