Computer Science ›› 2014, Vol. 41 ›› Issue (10): 42-44.doi: 10.11896/j.issn.1002-137X.2014.10.009

Previous Articles     Next Articles

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

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

[1] 杨灿军,陈鹰,路甬祥.人机一体化智能系统理论及应用研究探索[J].机械工程学报,2000,36(6):42-47
[2] Kazerooni H,Racine J L,Huang L,et al.On the control of the berkeley lower extremity exoskeleton (BLEEX)[C]∥Procee-dings of the 2005 IEEE International Conference on Robotics and Automation(ICRA 2005).IEEE,2005:4353-4360
[3] Strausser K A,Kazerooni H.The development and testing of a human machine interface for a mobile medical exoskeleton[C]∥2011 IEEE/RSJ International Conference on Intelligent Robot and System.San Francisco,CA,USA,Sep.2011:4911-4916
[4] 王楠,王建华,周民伟.人体下肢外骨骼机器人的步态研究现状[J].中国骨科临床与基础研究杂志,2012,4(1):62-67
[5] 蔡付文,王人成,李广庆,等.低成本人体步态分析系统的研究[J].中国康复医学杂志,2008,3(1):49-53
[6] Zhang Xiao-dong,Choi H.Pattern Recognition of HumanGrasping Operations Based on EEG[J].International Journal of Control Automation and Systems,2006,4(5):592-600
[7] Ferris D P,Czerniecki J M,Hannaford B.An Ankle-Foot Orthosis Powered by Artificial Pneumatic Muscles[J].Journal of Applied Biomechanics,2005,21(2):189-197
[8] 蔡春风.人体表面肌电信号处理及其在人机智能系统中的应用研究[D].杭州:浙江大学,2006
[9] 吴剑锋,吴群,孙守迁.简约支持向量机分类算法在下肢动作识别中的应用研究[J].中国机械工程,2011,2(4):433-438
[10] Kawamoto H,Lee S,Kanbe S,et al.Power assist method for HAL-3 using EMG-based feedback controller[C]∥IEEE International Conference on Systems,Man and Cybernetics,2003.2003:1648-1653
[11] 孙建,余永,葛云建.基于接触力信息的可穿戴下肢助力机器人传感系统研究[J].中国科学技术大学学报,2008,8(12):1432-1438
[12] Pratt J,Krupp B,Morse P G,et al.The RoboKnee:an exoskeleton for enhancing strength endurance during walking[C]∥Proceedings of the IEEE International Conference,ICRA 2004.Robotics and Automation,2004:2430-2435
[13] CorderoaA F B,Koopmana H J F M, van der Helm F C T.Use of pressure insoles to calculate the complete ground reaction forces[J].Journal of Biomechanics,2004,7:1427-1432
[14] Savelberg H,De Lange A L.Assessment of the horizontal,fore-aft component of the ground reaction force from insole pressure patterns by using artificial neural networks[J].Clinical Biomechanics,1999,4(8):585-592
[15] ortolero X,Masani K,Popovic M R.Step Prediction During Perturbed Standing Using Center of Pressure Measurements[J].Sensors,2007,7(4):459-472
[16] Zhang Kuan,Sun Ming,Lester D K,et al.Assessment of human locomotion by using an insole measurement system and artificial neural networks[J].Journal of Biomechanics,2005,8(11):2276-2287
[17] 郑成闻.基于柔性双足信息的助力机器人行走控制方法研究[D].合肥:中国科学技术大学,2011
[18] Candidia F.Gene Expression programming:mathematical modeling by an artificial intelligence[M].Springer-Verlag,2006
[19] 张立佑.成人足底压力中心前进路径模式之建立[D].台湾朝阳科技大学,2009

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!