Analysis of surface myoelectric signals by linear prediction method
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Betts B J, Binsted K, Jorgensen Ch. Small-vocabulary speech recognition using surface electromyography. Interacting with Computers 2006; 18: 1242-59.
Codello I, Kuniszyk-Jóźkowiak W. Digital signals analysis with the LPC method. Annales UMCS Informatica 2006; A15: 315-21.
Codello I, Kuniszyk-Jóźkowiak W.’Wave Blaster’ – A comprehensive tool for speech analysis and its application for vowel recognition using wavelet continuous transform with bark scale. In: Proc. 56th open Seminar in Acoustics 2009; 141-46.
Codello I, Kuniszyk-Jóźkowiak W, Smołka E, Suszyński W. Speaker Recognition Using Continuous Wavelet Transform with Bark Scales. Polish Journal of Environmental Studies 2009; 18 (3B): 78-82.
Coorevits P, Danneels L, Cambier D, Ramon H, Druyts H, Karlsson J S, De Moor G, Vanderstraeten G. Correlations between short-time Fourier and continuous wavelet transforms in the analysis of localized back and hip muscle fatigue during isometric contractions. Journal of Electromyography and Kinesiology 2008; 18: 637-44.
Fele-Žorž G, Kavšek G, Novak-Antolič Ž, Jager F. A comparison of various linear and non-linear processing techniques to separate EMG records of term and pre-term delivery groups. Med. Biol. Eng. Comp. 2008; 46: 911-22.
Flanders M. Choosing a wavelet for single-trial EMG. Journal of Neuroscience Methods 2002; 116: 165-177.
Manal K, Buchanan T S. A one-parameter neural activation to muscle activation model: estimating isometric joint moments from electromyograms. Journal of Biomechanics
; 36: 1197-1203.
Moshou D, Hostens I, Papaioannou, Ramon H. Dynamic muscle fatigue detection using self-organizing maps. Applied Soft Computing 2005; 5: 391-398.
Olmo G, Laterza F, Lo Presti L, Matched wavelet approach in stretching analysis of electrically evoked surface EMG signal. Signal Processing 2000; 80: 671-684.
Farina D, Falla D, Estimation of muscle conduction velocity from two-dimensional surface EMG recordings in dynamic tasks. Biomechanical Signal Processing and Control 2008; 3: 138-144.
Piotrkiewicz M, Hausmanowa-Petrusewicz I, Mierzejewska J. Are motoneurons involved in muscular dystrophy? Clinical Neurophysiology 1999; 110: 1111-22.
Piotrkiewicz M, Filipiuk M, Hausmanowa-Petrusewicz I. MU firing characteristics in human dystrophic muscle. Acta neurobiologiae experimentalis. 1993; 53(1): 313-18.
Piotrkiewicz M, Kudina l, Chen JJJ, Zalewska E, Hausmanowa-Petrusewicz I. Assessment of Human Motoneuron Afterhyperpolarization Duration in Health and Disease. Biocybernetics and Biomedical Engineering 2012; 32 (3): 43-61.
Rabiner LR, Schafer, Digital Processing of Speech Signals. New Jersey; Prentice-Hall, Inc. ; 1978.
von Tscharner V, Goephert B, Nigg BM. Changes in EMG signals for muscle tibialis anterior while running barefoot or with shoes resolved by non-lenarly scaled wavelets. Journal of Biomechanics 2003; 36: 1169-76.
Zalewska E, Hausmanowa-Petrusewicz I. Approximation of motor unit structure from the analysis of motor unit potential. Clinical Neurophysiology 2008; 119: 2501-06.
Zalewska E, Hausmanowa-Petrusewicz I. Effectiveness of motor unit potentials classification using various parameters and indexes. Clinical Neurophysiology 2000; 111: 1380-1387.
Zalewska E, Rowinska-Marcinska K, Gawel M, Hausmanowa-Petrusewicz I. Simulation studies on the motor unit potentials with satellite components in amyotrophic lateral sclerosis and spinal muscle atrophy, Muscle & Nerve 2012; 45 (4): 514-521.
Zieliński T P. Digital Signal Processing. Warszawa; Publisher Transport and Communications; 2005 (in Polish).
DOI: http://dx.doi.org/10.17951/ai.2016.16.1.62
Date of publication: 2016-10-04 00:00:00
Date of submission: 2016-05-17 10:55:24
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Copyright (c) 2016 Waldemar Suszyński, Wiesława Kuniszyk-Jóźkowiak, Ireneusz Codello, Rafał Stęgierski, Karol Kuczyński, Janusz Jaszczuk
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