计算机科学 ›› 2014, Vol. 41 ›› Issue (10): 42-44.doi: 10.11896/j.issn.1002-137X.2014.10.009

• 2013’和谐人机环境联合学术会议 • 上一篇    下一篇

面向外骨骼机器人人机交互的步态数据获取系统及识别模型

高增桂,孙守迁,张克俊,佘铎淳,杨钟亮   

  1. 浙江大学计算机科学与技术学院 杭州310027;浙江大学计算机科学与技术学院 杭州310027;浙江大学计算机科学与技术学院 杭州310027;浙江大学计算机科学与技术学院 杭州310027;东华大学机械工程学院 上海201620
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金项目:基于云模型的音乐情感表示与识别算法研究(61303137),基于基因表达式编程的动漫情感化配乐技术研究(61070075),基于嵌套随机集的产品意象认知模型研究(61003147),生物启发设计中产品创意造型生成机制及其演化模型研究(51305077),广东省产学研项目基于人体行为模型的智能助行机器人研究与开发(00411420124671038)资助

Gait Data System and Joint Movement Recognition Model for Human-exoskeleton Interaction

GAO Zeng-gui,SUN Shou-qian,ZHANG Ke-jun,SHE Duo-chun and YANG Zhong-liang   

  • Online:2018-11-14 Published:2018-11-14

摘要: 外骨骼机器人人机交互是当前的研究热点,通常需要获取人体相关运动信息作为控制信号源。为了采集人体步态数据,研究了生理信号与关节运动之间的关联机制,设计了一种步态数据获取系统,其利用鞋内薄膜压力传感器和关节角度传感器组成测试设备,成功采集了15组健康男子在3km/h、4km/h和5km/h 3种速率下自然行走的步态数据。提出采用基因表达式编程建立膝关节运动识别模型,并使用所采集的步态数据进行训练和验证。结果显示,利用此模型可有效进行关节运动的识别和预测,验证了本系统作为外骨骼人机接口的可行性。

关键词: 人机交互,人机接口,步态分析,基因表达式编程,外骨骼

Abstract: Human-machine interaction plays a great role in control of exoskeletons,and usually it is required to obtain the relevant information about body motion as control signal sources.In order to collect human gait data and find the association between the physiological signals and the joint movement mechanism,we designed a Gait Data Acquisition System(GDS) which consists of eight thin-film pressure sensors and a joint angle sensor.After gait experiments,we obtained 15 groups of gait data of health male objects with natural walking under three rates in 3km/h,4km/h and 5km/h.We also proposed establishment of recognition model of the knee joint motion using GEP.The gait data was used to train and validate the recognition model.The result shows that the model can effectively identify and predict knee joint motion and the GDS is feasible as a human-machine interface in exoskeletons.

Key words: Human-computer interaction,Human-machine interface,Gait analysis,GEP,Exoskeleton

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