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
by several comparison experiments.

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.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
JAIHC.pdf(2042KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Shixin Ren]的文章
[Weiqun Wang]的文章
[Zeng-Guang Hou]的文章
百度学术
百度学术中相似的文章
[Shixin Ren]的文章
[Weiqun Wang]的文章
[Zeng-Guang Hou]的文章
必应学术
必应学术中相似的文章
[Shixin Ren]的文章
[Weiqun Wang]的文章
[Zeng-Guang Hou]的文章
相关权益政策
暂无数据
收藏/分享
文件名: JAIHC.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。