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Design of high-accuracy eight-channel surface electromyography acquisition system and its application

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Abstract

The surface electromyography (sEMG) acquisition system has the advantages of small size, high precision, low power consumption and easy operation. We have developed a low-cost and portable eight-channel sEMG acquisition system, in which consists of the related analog front end (AFE), main control unit (MCU) and power supply system. The AFE circuit converts the sEMG signal to the digital signal after filtering the direct current and the two stage amplification. The MCU controls the analog-to-digital converter (ADC) using serial peripheral interface (SPI), packages the data and sends the data to the android through a high-speed wireless module. The power supply system provides stable voltage source and can be powered by battery. Experimental results show that the designed eight-channel sEMG acquisition system exhibits an excellent electrical performance with the amplifier resolution of 8.1 μV, the system noise of lower than 15.3 μV, the sampling rate of 1000 Hz and power consumption of about 30.7 mW. The recognition rate is as high as 98% using support vector machines when detecting normal and fatigue state. This device can be applied in the fields of family health monitoring and the detection of the muscle state in daily life and work.

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References

  1. K. Heinrichs, Physiotherapy 84, 405 (1998)

    Google Scholar 

  2. R. Hu, Y. Li, W. Xu, L. Cheng, H. Ren, J. Voice Found. 31, 126.e1 (2015)

    Article  Google Scholar 

  3. M. Dasog, K. Koirala, P. Liu, E.A. Clancy, IEEE Trans. Neural Syst. Rehabil. Eng. 22, 664 (2014)

    Article  Google Scholar 

  4. F. Duan, L. Dai, IEEE Trans. Ind. Electron. 64, 4276 (2017)

    Article  ADS  Google Scholar 

  5. P. Pavitra, P. Sadasivan, IEEE Eng. Med. Biol. Soc. 26, 608 (2004)

    Google Scholar 

  6. M. Liang, C. Damien, B. Fouad, Z. Wei, H. Bo, G. Francois, Int. J. Ind. Ergon. 41, 10 (2011)

    Article  Google Scholar 

  7. P.K. Edwards, J.R. Ebert, C. Littlewood, T. Ackland, A. Wang, J. Orthop. Sports Phys. Therapy 1, 1 (2017)

    Google Scholar 

  8. C. Huang, X. Chen, S. Cao, B. Qiu, X. Zhang, J. Neural Eng. 14, 046005 (2017)

    Article  ADS  Google Scholar 

  9. A.C.M.V. Rijn, A. Peper, C.A. Grimbergen, Med. Biol. Eng. Comput. 28, 389 (1990)

    Article  Google Scholar 

  10. Y. Zhang, L. Dai, Y.H. Luo, S. Huo, IEEE Int. Conf. Electron. Meas. Instrum. 10, 132 (2011)

    Google Scholar 

  11. A. Dutta, R. Kobetic, R. Triolo, ASME J. Devices 2, 027565 (2008)

    Article  Google Scholar 

  12. E. Koutsos, P. Georgiou, IEEE Int. Symp. Circuits Syst. 10, 1388 (2014)

    Google Scholar 

  13. Datasheet, ADS1278, quad/octal, simultaneous sampling, 24bit analogto-digital converters. Texas Instruments, 2009

  14. F.N. Guerrero, E.M. Spinelli, M.A. Haberman, IEEE Transact. Biomed. Circuits Syst. 10, 787 (2016)

    Article  Google Scholar 

  15. YY/T 1095-2015, Myoelectric biofeedback equipment

  16. T. Muehlemann, D. Haensse, M. Wolf, Opt. Express 16, 10323 (2008)

    Article  ADS  Google Scholar 

  17. N.L. Everdell, D. Airantzis, C. Kolvya, T. Suzuki, C.E. Elwell, Med. Eng. Phys. 35, 1692 (2013)

    Article  Google Scholar 

  18. D.R. Rogers, D.T. MacIsaac, J. Electromyogr. Kinesiol. 21, 811 (2011)

    Article  Google Scholar 

  19. Z. Ju, G. Ouyang, K. Wilamowska, H. Liu, IEEE Sens. J. 13, 3302 (2013)

    Article  ADS  Google Scholar 

  20. X. Xi, M. Tang, S.M. Miran, Z. Luo, Sensors 17, 1229 (2017)

    Article  Google Scholar 

Download references

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Author notes

  1. Chao Mi and Tiantong Zhou are co-first authors.

Authors and Affiliations

  1. School of Information Science and Engineering, Changzhou University, 1 Gehu Road, Changzhou, 213164, P.R. China

    Chao Mi, Tiantong Zhou & Ling Zou

  2. School of Mechatronic Engineering and Automation, Shanghai University, 149 Yanchang Road, Shanghai, 200072, P.R. China

    Bin Wei

  3. University of Plymouth, Plymouth, PL4 8AA, UK

    Yi Wang

Authors
  1. Chao Mi
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  2. Tiantong Zhou
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  3. Bin Wei
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  4. Yi Wang
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  5. Ling Zou
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Corresponding author

Correspondence to Ling Zou.

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Mi, C., Zhou, T., Wei, B. et al. Design of high-accuracy eight-channel surface electromyography acquisition system and its application. Eur. Phys. J. Spec. Top. 227, 933–942 (2018). https://doi.org/10.1140/epjst/e2018-800001-8

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  • DOI: https://doi.org/10.1140/epjst/e2018-800001-8

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