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Mobile Networks and Applications

, Volume 23, Issue 4, pp 797–805 | Cite as

Gesture Recognition Based on Kinect and sEMG Signal Fusion

  • Ying Sun
  • Cuiqiao Li
  • Gongfa Li
  • Guozhang Jiang
  • Du Jiang
  • Honghai Liu
  • Zhigao Zheng
  • Wanneng Shu
Article

Abstract

A weighted fusion method of D-S evidence theory in decision making is proposed to aim at the problem of lacking in the distribution of trust, data processing and precision in D-S evidential theory. The method of gesture recognition based on Kinect and sEMG signal are established. Weighted D-S evidence theory is used to fuse Kinect and sEMG signals and the simulation experiment is made respectively. The stimulation results show that comparing with other experimental methods, the decision fusion method based on weighted D-S evidence theory has higher utilization efficiency and recognition rate.

Keywords

Gesture recognition D-S evidence theory sEMG Kinect signal fusion 

Notes

Acknowledgments

This work was supported by grants of National Natural Science Foundation of China (Grant No. 51575407, 51575338, 61273106, 51575412 and 61603420) and the Grants of National Defense Pre-Research Foundation of Wuhan University of Science and Technology (GF201705).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of EducationWuhan University of Science and TechnologyWu HanChina
  2. 2.Hubei Key Laboratory of Mechanical Transmission and Manufacturing EngineeringWuhan University of Science and TechnologyWuhanChina
  3. 3.School of ComputingUniversity of PortsmouthPortsmouthUK
  4. 4.School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhanChina
  5. 5.College of Computer ScienceSouth-Central University for NationalitiesWuhanChina

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