RESEARCH ON GAIT PREDICTION BASED ON LSTM

Bofan Liang, Qili Chen
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Abstract

With an aging population that continues to grow, the protection and assistance of the older persons has become a very important issue. Falls are 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. 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. The proposed method can predict the gait trend well.
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基于LSTM的步态预测研究
随着老龄化人口的持续增长,老年人的保护和帮助已经成为一个非常重要的问题。跌倒是老年人的主要安全问题,因此对跌倒进行预测是非常重要的。本文提出了一种步态预测方法。首先利用加速度陀螺仪测量人体的腰部姿态作为步态特征,然后利用LSTM网络对步态进行预测。实验结果表明,该方法预测的步态趋势与实际步态趋势的RMSE可达到0.06±0.01的水平。该方法能较好地预测步态趋势。
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