计算机科学 ›› 2020, Vol. 47 ›› Issue (6A): 242-246.doi: 10.11896/JsJkx.191000077
周立鹏1, 孟利民1, 周磊1, 蒋维2, 董建平3
ZHOU Li-peng1, MENG Li-min1, ZHOU Lei1, JIANG Wei2 and DONG Jian-ping3
摘要： 摔倒对于老年人来说是一个十分严重的问题,实时检测老年人是否摔倒对于减轻摔倒造成的伤害具有重要意义。为此,文中提出了一种基于BP神经网络的摔倒检测算法。该算法采用佩戴于腰部的六轴传感器(MPU6050)来采集人体运动数据,使用简单的统计学方法对数据进行特征提取,并以提取到的特征为BP神经网络的输入神经元,用Levenberg-Marquardt算法训练神经网络模型,使其能够实现摔倒检测的功能。实验结果表明,该算法可以较好地识别摔倒,其准确率可以达到99.55%。
中图分类号:
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