A Comparative Study of LSTM and Phased LSTM for Gait Prediction

Qili Chen, Bofan Liang, Jiuhe Wang
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引用次数: 8

Abstract

With an aging population that continues to grow, the protection and assistance of the older persons has become a very important issue. Fallsare the main safety problems of the elderly people, so it is very important to predict the falls. In this paper, a gait prediction method is proposed based on two kinds of LSTM. Firstly, the lumbar posture of the human body is measured by the acceleration gyroscope as the gait feature, and then the gait is predicted by the LSTM network. The experimental results show that the RMSE between the gait trend predicted by the method and the actual gait trend can be reached a level of 0.06 ± 0.01. And the Phased LSTM has a shorter training time. The proposed method can predict the gait trend well.
LSTM与相位LSTM在步态预测中的比较研究
随着人口老龄化的持续增长,保护和援助老年人已成为一个非常重要的问题。跌倒是老年人的主要安全问题,因此预测跌倒情况非常重要。本文提出了一种基于两种LSTM的步态预测方法。首先,通过加速度陀螺仪测量人体的腰部姿态作为步态特征,然后通过LSTM网络预测步态。实验结果表明,该方法预测的步态趋势与实际步态趋势之间的RMSE可以达到0.06±0.01的水平。并且分阶段LSTM的训练时间更短。该方法能够很好地预测步态的变化趋势。
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