Knowledge Commons of Institute of Automation,CAS
Anthropometric Features Based Gait Pattern Prediction Using Random Forest for Patient-Specific Gait Training | |
Shixin Ren![]() ![]() ![]() ![]() ![]() ![]() | |
2018 | |
会议名称 | International Conference on Neural Information Processing |
会议录名称 | Neural Information Processing |
卷号 | Volume 11304 |
期号 | Part IV |
页码 | 15-26 |
会议日期 | December 13-16, 2018 |
会议地点 | Siem Reap, Cambodia |
会议录编者/会议主办者 | Long ChengAndrew Chi Sing LeungSeiichi Ozawa |
出版地 | Siem Reap, Cambodia |
出版者 | Springer, Cham |
摘要 | Using lower limb rehabilitation robots to help stroke patients recover their walking ability is becoming more and more popular presently. The natural and personalized gait trajectories designed for robot assisted gait training are very important for improving the therapeutic results. Meanwhile, it has been proved that human gaits are closely related to anthropometric features, which however has not been well researched. Therefore, a method based on anthropometric features for prediction of patient-specific gait trajectories is proposed in this paper. Firstly, Fourier series are used to fit gait trajectories, hence, gait patterns can be represented by the obtained Fourier coefficients. Then, human age, gender and 12 body parameters are used to design the gait prediction model. For the purpose of easy application on lower limb rehabilitation robots, the anthropometric features are simplified by an optimization method based on the minimal-redundancy-maximal-relevance criterion. Moreover, the relationship between the simplified features and human gaits is modeled by using a random forest algorithm, based on which the patient-specific gait trajectories can be predicted. Finally, the performance of the designed gait prediction method is validated on a dataset. |
关键词 | Patient-specific gait, Anthropometric features, Random forest, Gait prediction |
学科门类 | 工学 |
DOI | https://doi.org/10.1007/978-3-030-04212-7_2 |
URL | 查看原文 |
收录类别 | EI |
语种 | 英语 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/41454 |
专题 | 复杂系统认知与决策实验室_先进机器人 中国科学院自动化研究所 |
通讯作者 | Weiqun Wang |
作者单位 | Institute of Automation of Chinese Academy of Science |
推荐引用方式 GB/T 7714 | Shixin Ren,Weiqun Wang,Zeng-Guang Hou,et al. Anthropometric Features Based Gait Pattern Prediction Using Random Forest for Patient-Specific Gait Training[C]//Long ChengAndrew Chi Sing LeungSeiichi Ozawa. Siem Reap, Cambodia:Springer, Cham,2018:15-26. |
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