Recognition of palm finger movements on the basis of EMG signals with the application of wavelets

• Autorzy: Krysztoforski K. , Wolczowski A. , Będziński R. , Helt K.
• Konferencja: Computers in Medical Applications: XIIIth Biocybernetics and Biomedical Engineering Conference (10-13 September 2003, Gdańsk, Poland)
• Języki publikacji: EN

Abstrakty

EN

The paper describes an EMG signal analysis based on the wavelet transform, applied for the hand prosthesis control. Signal features are represented by wavelet coefficients. A cross-validation method is applied for the feature selection process. The classification algorithm uses multistage recognition. The information about finger posture provided by a data glove is recorded concurrently with forearm EMG signals. The acquired data are used to train the classification algorithm.

Słowa kluczowe

EN

multistage pattern recognition; EMG signal processing; wavelet transform; dexterous prosthesis control

• Wydawca: Politechnika Gdańska
• Czasopismo: TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk
• Rocznik: 2004
• Tom: Vol. 8, No 2
• Strony: 269--280
• Opis fizyczny: Bibliogr. 13 poz., rys., tab.

Twórcy

autor

Krysztoforski K.

• Biomedical Engineering and Experimental Mechanics Division, Wroclaw University of Technology, Wyb. Wyspiańskiego 27, 50-370 Wroclaw, Poland

autor

Wolczowski A.

• 2Institute of Engineering Cybernetics, Wroclaw University of Technology, Wyb. Wyspiańskiego 27, 50-370 Wroclaw, Poland

autor

Będziński R.

• Biomedical Engineering and Experimental Mechanics Division, Wroclaw University of Technology, Wyb. Wyspiańskiego 27, 50-370 Wroclaw, Poland

autor

Helt K.

• 2Institute of Engineering Cybernetics, Wroclaw University of Technology, Wyb. Wyspiańskiego 27, 50-370 Wroclaw, Poland

• Biomedical Engineering and Experimental Mechanics Division, Wroclaw University of Technology, Wyb. Wyspiańskiego 27, 50-370 Wrocław, Poland

Bibliografia

• [1] Wolczowski A, Krysztoforski K and Będziński R 2001 Proc. 12 th National Biocybernetic and Biomedical Engineering Conf., Warsaw, Poland, pp. 419–423
• [2] Wolczowski A and Krysztoforski K 2001 Proc. 7 th National Robotic Conf., Ladek Zdroj, Poland, pp. 239–246 (in Polish)
• [3] Wolczowski A and Krysztoforski K 2002 Acta of Bioengng. and Biomech. 4 (1) 576
• [4] Hudgins B, Parker P and Scott R N 1993 IEEE BME 40 (1) 82
• [5] Englehart K, Hudgins B and Parker P A 2000 Proc. 22 nd Annual Int. Conf. IEEE Engineering in Medicine and Biology Society, Chicago, USA
• [6] Englehart K, Hudgins B and Parker P A 2001 IEEE Trans. on Biomed. Engng. 48 (3) 302
• [7] Yu W, Yokoi H and Nishikawa D 1998 Intelligent Autonomous Systems, IOS Press, Kitahiroshima,pp. 266–271
• [8] Fujii S, Nishikawa D and Yokoi H 1998 Development of Prosthetic Hand Using Adaptable Control Method for Human Characteristic, IAS-5, IOS Press, Sapporo, pp. 360–367
• [9] Nishikawa D, Ishikawa Y, Yu W, Maruishi M, Watanabe I, Pokoi H, Mano Y and Kakazu Y 2000 Proc. 13 th Congress of Int. Society of Electrophysiology and Kinesiology (ISEK2000), Sapporo, Japan, pp. 575–580
• [10] Moshou D, Hostens I, Papaioannou G and Ramon H 2000 Wavelets and Self-organising Maps in Electromyogram (EMG) Analysis, ESIT, Aachen, Germany
• [11] Han J S, Song W K, Kim J S, Bang W C, Lee H and Bien Z 2000 Proc. 6 th Int. Conf. on Soft Computing (IIZUKA2000), Japan, pp. 890–897
• [12] Helt K 2003 Application of the Wavelets for Pattern Recognition, PhD Thesis, ICT Wroclaw University of Technology (in Polish)
• [13] Kurzyński M 1997 Pattern Recognition, Wroclaw University of Technology Publishing, Wroclaw (in Polish)