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  • 标题:Research on gait prediction based on LSTM
  • 本地全文:下载
  • 作者:Bofan Liang ; Qili Chen
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2019
  • 卷号:9
  • 期号:6
  • 页码:1-7
  • DOI:10.5121/csit.2019.90603
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要: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.
  • 关键词:Elderly people fall; Acceleration gyro; Lumbar posture; Gait prediction; LSTM
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