Abstract
Electric signal analysis from live organism is an old area that was documented by Francesco Redi dated from 1666, Walsh 1773, and Galvani 1792 [1]. Contraction of muscular fibers by electric impulses was recorded by Debois-Raymmod 1849 [1]. Electric impulses known as myolectric signal and their recording are named electromyographic signals or EMG [2-8]. The first clinical use of EMG signals was reported in 1966 by Harddyck. It is not until the 1980´s that clinical methods to monitor EMG of several muscles were achieved [1].
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References
Reaz, M.B.I., Hussain, M.S., Mohd-Yasin, F.: Techniques of EMG Signal Analysis: Detection, Processing, Classification and Applications. Biol. Proced. Online 8(1), 11–35 (2006)
Kamen, G.: Frequently Asked Questions About Electromyography (EMG). In: Non-invasive Investigation of the Neuromuscular System, An Official Interest Group of ACSM. University of Massachusetts at Amherst, 25 de October del (2006), http://vuiis.vanderbilt.edu/~nins/EMG_FAQ.htm
Betancourt, O.A., Suárez, E.G., Franco, J.F.: Movement Recognition from EMG Signals. Scientia et Técnica,Universidad Tecnológica de Pereira 10(26), 53–58 (2004)
Berne, R.M., Levy, M.N.: Physiology: Section 1: Cellular Physiology. In: Ionic Equilibrium and Membrane Rest Potentia, Medica Panamericana, Buenos Aires Argentina, ch. 2, pp. 32–41 (1987)
Merletti, R.: Standards for Reporting EMG Data, International Society of Electrophysiology and Kinesiology. Journal of Electromyography and Kinesiology, Politecnico di Torino, Italy (1999)
Abbink, J.H., van der Bilt, A., van der Glas, H.W.: Detection of Onset and Termination of Muscle Activity in Surface Electromyograms. Journal of Oral Rehabilitation 25(5), 365–369 (1998)
Merlo, A., Farina, D., Merletti, R.: A fast and reliable technique for muscle activity detection from surface EMG signals. IEEE Transactions on Biomedical Engineering 50(3), 316–323 (2003)
Gazzoni, M., Farina, D., Merletti, R.: A New Method for the Extraction and Classification of Single Motor Unit Action Potentials From Surface EMG Signals. Journal of Neuroscience Methods 136(2), 165–177 (2004)
Kiguchi, K., Tanaka, T., Fukuda, T.: Neuro-Fuzzy Control of a Robotic Exoskeleton With EMG Signals. IEEE Trans. Fuzzy Syst. 12(4), 481–490 (2004)
Strang, G., Nguyen, T.: Wavelets and Filter Bank. Wellesley – Cambridge Press, USA (1996)
Schrader, C.B., Roberson, D.: Using Rank Order Filters to Decompose the Electromyogram. In: Electronic Proceedings of 15th International Symposium on the Mathematical Theory of Networks and Systems, University of Notre Dame, South Bend, Indiana, USA, August 12-16 (2002)
Liand, X., Aruin, A.S.: Muscle activity onset time detection using Teager-Kaiser energy operator. In: Proceedings of the 2005 IEEE Engineering in Medicine and Biology, 27th Annual Conference, September 2005, pp. 7549–7552 (2005)
Linand, W., Chitrapu, P.: Time-Frequency Distributions Based on Teager-Kaiser Energy Function. In: Proceedings of 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1996, May 1996, vol. 3, pp. 1818–1821 (1996)
Vakman, D.: On the Analytic Signal, the Teager-Kaiser Energy Algorithm, and Other Methods for Defining Amplitude and Frequency. IEEE Transactions on Signal Processing 44(4), 791–797 (1996)
Bezdek, J., Pal, K.: Fuzzy Models for Pattern Recognition. In: Methods that Search for Structures in Data. IEEE Press, Los Alamitos (1991)
Pappas, T.: An adaptive Clustering Algorithm for Image Segmentation. IEEE Trans. Signal Processing 40, 901–914 (1992)
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Murguia, M.I.C., Olvera, L.V., Reyes, A.D. (2009). EMG Hand Burst Activity Detection Study Based on Hard and Soft Thresholding. In: Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition. Studies in Computational Intelligence, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04516-5_12
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DOI: https://doi.org/10.1007/978-3-642-04516-5_12
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