Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
The article presents a general concept of a bionic hand control system using multichannel EMG signal, being under development at present. The method of acquisition and processing of multi-channel EMG signal and feature extraction for machine learning were described. Moreover, the design of the control system implementation in the real-time embedded system was discussed.
Czasopismo
Rocznik
Tom
Strony
26--34
Opis fizyczny
Bibliogr. 20 poz., rys., tab.
Twórcy
autor
- University of Applied Sciences in Tarnow, Department of Computer Sciences, Mickiewicza 8, 33-100 Tarnow, Poland
autor
- University of Applied Sciences in Tarnow, Department of Computer Sciences, Mickiewicza 8, 33-100 Tarnow, Poland
Bibliografia
- 1. Błaszczyk J.W. Biomechanika kliniczna. Warszawa: PZWL; 2014.
- 2. Murray R.K., Granner D.K., Rodwell V.W. Biochemia Harpera. Warszawa: PZWL; 2008.
- 3. Chandra R. hhrun - Hodgkin Huxley model simulation for user defined input current. MATLAB Central File Exchange, [Online]. Available: https://www.mathworks.com/matlabcentral/fileexchange/46740-hhrun-hodgkin-huxley-model-simulation-for-user-defined-input-current. (accessed 10.12.2019).
- 4. Wołczowski A., Błędowski M., Witkowski J. System do rejestracji sygnałów EMG i MMG dla sterowania bioprotezą dłoni. Prace Naukowe Politechniki Warszawskiej. Elektronika. 2016;195(1);167-178.
- 5. DFRobot Bionic Robot Hand, DFRobot, [Online]. Available: https://www.dfrobot.com/product-1623.html. (accessed 2019.12.11).
- 6. Saebo, [Online]. Available: https://www.saebo.com/shop/saeboglove/. (accessed 2019.12.11).
- 7. Recommendations for sensor locations on individual muscles, SENIAM, [Online]. Available: www.seniam.org/sensor_location.htm. (accessed 07.06.2020).
- 8. Yoo H.J., Park H., Lee B. Myoelectric Signal Classification of Targeted Muscles Using Dictionary Learning. Sensors. 2019;19(2370):1-19. doi: https://doi.org/10.3390/s19102370.
- 9. NXP Semiconductors, [Online]. Available: https://www. nxp.com/design/microcontrollers-developer-resources/ lpc-microcontroller-utilities/lpcxpresso-board-for-lpc1347:OM13045. (accessed 07.06.2020).
- 10. QT Company. Qt Framework - One framework to rule all! [Online]. Available: https://www.qt.io/product/framework. (accessed 07.06.2020).
- 11. eIQ™ for Arm® CMSIS-NN, [Online]. Available: https:// www.nxp.com/design/software/development-software/ eiq-ml-development-environment/eiq-for-arm-cmsis-nn:eIQArmCMSISNN. (accessed 07.06.2020).
- 12. Geron A. Uczenie maszynowe z użyciem Scikit-Learn i Tensorflow. Gliwice: Helion; 2018.
- 13. Zieliński T.P. Cyfrowe przetwarzanie sygnałów. Warszawa: WKŁ; 2007.
- 14. Gawędzki W., Socha M., Sławik P. Dekompozycja sygnałów EEG w dziedzinie czasu przy zastosowaniu transformacji Hilberta-Huanga HHT. Przegląd Elektrotechniczny. 2015;91(5):33-36.
- 15. Huang N.E., Shen Z., Long S.R., Wu M.J., Shih H.H., Zheng Q., Yen N.C., Tung C.C., Liu H.H. The Empirical mode decomposition and the Hilbert Spectrum for nonlinear and non-stationary time series analysis. Royal Society of London Proceedings Series A. 1998; 454(1971):903-998. doi: https://doi. org/10.1098/rspa.1998.0193.
- 16. Feldman M. Hilbert Transform Application in Mechanical Vibration. Wiley; 2011.
- 17. Huang N.E., Shen S.S.P. Hilbert-Huang Transform and Its Applications. Singgapore: World Scientific; 2005.
- 18. Kukker A., Sharma R., Malik H. Forearm movements classification of EMG signals using Hilbert Huang transform and artificial neural networks. Materiały konferencyjne 2016 IEEE 7th Power India International Conference (PIICON); 2016 Nov 25-27; Bikaner, India: IEEE; 2016. doi: https://doi. org/10.1109/POWERI.2016.8077417.
- 19. Ruiz-Olaya A.F., López-Delis A. Surface EMG Signal Analysis Based on the Empirical Mode Decomposition for Human-Robot Interaction. Materiały konferencyjne Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013; 2013 Sep 11-13; Bogota, Colombia; 2013. doi: 10.1109/ STSIVA.2013.6644943.
- 20. Tan A. Hilbert-Huang Transform. MATLAB Central File Exchange, [Online]. Available: https://www.mathworks.com/ matlabcentral/fileexchange/19681-hilbert-huang-transform. (accessed: 31.12.2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fdc683eb-ef68-4a5c-b66f-5f7a11daa74b