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Gesture Recognition Based on Kinect and sEMG Signal Fusion

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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.

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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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Correspondence to Gongfa Li or Zhigao Zheng.

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Sun, Y., Li, C., Li, G. et al. Gesture Recognition Based on Kinect and sEMG Signal Fusion. Mobile Netw Appl 23, 797–805 (2018). https://doi.org/10.1007/s11036-018-1008-0

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