logo

SCIENCE CHINA Information Sciences, Volume 64 , Issue 8 : 189204(2021) https://doi.org/10.1007/s11432-018-9816-4

GPR and SPSO-CG based gait pattern generation for subject-specific training

More info
  • ReceivedNov 1, 2018
  • AcceptedMar 1, 2019
  • PublishedJun 2, 2020

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported in part by National Key RD Program of China (Grant No. 2018YFB1307800), National Natural Science Foundation of China (Grant Nos. 91648208, 61720106012), and Strategic Priority Research Program of Chinese Academy of Science (Grant No. XDB32000000).


References

[1] Koopman B, van Asseldonk E H F, van der Kooij H. Speed-dependent reference joint trajectory generation for robotic gait support.. J BioMech, 2014, 47: 1447-1458 CrossRef PubMed Google Scholar

[2] Luu T P, Lim H B, Qu X, et al. Subject-specific lower limb waveforms planning via artificial neural network. In: Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics(ICORR), Switzerland, 2011. 1--6. Google Scholar

[3] Luu T P, Low K H, Qu X. An individual-specific gait pattern prediction model based on generalized regression neural networks.. Gait Posture, 2014, 39: 443-448 CrossRef PubMed Google Scholar

[4] Yun Y, Kim H C, Shin S Y. Statistical method for prediction of gait kinematics with Gaussian process regression.. J BioMech, 2014, 47: 186-192 CrossRef PubMed Google Scholar

[5] Williams C K I, Rasmussen C E. Gaussian processes for machine learning. Cambridge: MIT Press, 2006. Google Scholar

[6] Ren S, Wang W, Hou Z G, et al. Anthropometric features based gait pattern prediction using random forest for patient-specific gait training. In: Proceedings of the International Conference on Neural Information Processing, Springer, 2018. 15--26. Google Scholar