Personalized gait trajectory generation based on anthropometric features using Random Forest | |
Shixin Ren1,2; Weiqun Wang1,2; Zeng-Guang Hou1,3; Badong Chen4; Xu Liang1,2; Liang Peng1,2 | |
发表期刊 | Journal of Ambient Intelligence and Humanized Computing |
2019-07 | |
期号 | 1页码:1-12 |
摘要 | Using lower limb rehabilitation robots (LLRRs) to help stroke patients recover their walking ability is attracting more and more attention presently. Previous studies have shown that gait rehabilitation training with natural gait pattern can improve the therapeutic outputs. However, how to generate the personalized gait trajectory has not been well researched. In this paper, a personalized gait generation method based anthropometric features is proposed. Firstly, gait trajectories are fitted and simplified into Fourier coefficient vectors, which are used to represent gait trajectories. Secondly, fourteen body features are used to generate the personalized gait trajectories and the feature set is further optimized based on the minimal redundancy maximal relevance criterion for easy application on the LLRR. Then, the relationship between the optimized feature set and gait trajectories is modeled by using the RF algorithm. Finally, the performance of the proposed method is demonstrated |
关键词 | Personalized gait Gait generation Random Forest Anthropometric features Rehabilitation training |
收录类别 | SCI |
语种 | 英语 |
七大方向——子方向分类 | 多模态智能 |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/45037 |
专题 | 复杂系统管理与控制国家重点实验室_先进机器人 |
通讯作者 | Weiqun Wang |
作者单位 | 1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, 2.University of Chinese Academy of Sciences, 3.The CAS Center for Excellence in Brain Science and Intelligence Technology, 4.Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Shixin Ren,Weiqun Wang,Zeng-Guang Hou,et al. Personalized gait trajectory generation based on anthropometric features using Random Forest[J]. Journal of Ambient Intelligence and Humanized Computing,2019(1):1-12. |
APA | Shixin Ren,Weiqun Wang,Zeng-Guang Hou,Badong Chen,Xu Liang,&Liang Peng.(2019).Personalized gait trajectory generation based on anthropometric features using Random Forest.Journal of Ambient Intelligence and Humanized Computing(1),1-12. |
MLA | Shixin Ren,et al."Personalized gait trajectory generation based on anthropometric features using Random Forest".Journal of Ambient Intelligence and Humanized Computing .1(2019):1-12. |
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