Details

Title

Critical Exponent Analysis Applied to Surface EMG Signals for Gesture Recognition

Journal title

Metrology and Measurement Systems

Yearbook

2011

Numer

No 4

Publication authors

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation

Date

2011

Identifier

ISSN 0860-8229

References

Koçer S. (2010), Classification of EMG signals using neuro-fuzzy system and diagnosis of neuromuscular diseases, Journal of Medical Systems, 34, 3, 321, doi.org/10.1007/s10916-008-9244-7 ; Oskoei M. (2007), Myoelectric control systems-A survey, Biomedical Signal Processing and Control, 2, 4, 275, doi.org/10.1016/j.bspc.2007.07.009 ; Boostani R. (2003), Evaluation of the forearm EMG signal features for the control of a prosthetic hand, Physiological Measurement, 24, 2, 309, doi.org/10.1088/0967-3334/24/2/307 ; Zecca M. (2002), Control of multifunctional prosthetic hands by processing the electromyographic signal, Critical Reviews in Biomedical Engineering, 30, 4-6, 459, doi.org/10.1615/CritRevBiomedEng.v30.i456.80 ; Oskoei M. (2008), Support vector machine-based classification scheme for myoelectric control applied to upper limb, IEEE Transactions on Biomedical Engineering, 55, 8, 1956, doi.org/10.1109/TBME.2008.919734 ; Lei M. (2001), Detecting nonlinearity of action surface EMG signal, Physics Letters A, 290, 5-6, 297, doi.org/10.1016/S0375-9601(01)00668-5 ; Meng Y. (2005), Test nonlinear determinacy of electromyogram, null, 4592. ; Padmanabhan P. (2004), Nonlinear analysis of EMG signals-A chaotic approach, null, 608. ; Chen W. (2007), Characterization of surface EMG signal based on fuzzy entropy, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 15, 2, 266, doi.org/10.1109/TNSRE.2007.897025 ; Hu X. (2005), Classification of surface EMG signal with fractal dimension, Journal of Zhejiang University - Science B, 6, 8, 844, doi.org/10.1631/jzus.2005.B0844 ; Gitter J. (1995), Fractal analysis of the electromyographic interference pattern, Journal of Neuroscience Methods, 58, 1-2, 103, doi.org/10.1016/0165-0270(94)00164-C ; Gupta V. (1997), Fractal analysis of surface EMG signals from the biceps, International Journal of Medical Informatics, 45, 3, 185, doi.org/10.1016/S1386-5056(97)00029-4 ; Arjunan S. (2010), Decoding subtle forearm flexions using fractal features of surface electromyogram from single and multiple sensors, Journal of NeuroEngineering and Rehabilitation, 7, 53. ; Naik G. (2011), Applications of ICA and fractal dimension in sEMG signal processing for subtle movement analysis: a review, Australasian Physical & Engineering Science in Medicine, 34, 2, 179, doi.org/10.1007/s13246-011-0066-4 ; Nakagawa M. (1993), A critical exponent method to evaluate fractal dimensions of self-affine data, Journal of the Physical Society of Japan, 62, 12, 4233, doi.org/10.1143/JPSJ.62.4233 ; Petry A. (2002), Speaker identification using nonlinear dynamical features, Chaos, Solitons & Fractals, 13, 2, 221, doi.org/10.1016/S0960-0779(00)00260-5 ; Sabanal S. (1996), The fractal properties of vocal sounds and their application in the speech recognition model, Chaos, Solitons & Fractals, 7, 11, 1825, doi.org/10.1016/S0960-0779(96)00043-4 ; L. De Oliveira (1999), Lung sound analysis with time-dependent fractal dimensions, Chaos, Solitons & Fractals, 10, 9, 1419. ; Nimkerdphol K. (2006), 3D locomotion and fractal analysis of Goldfish for acute toxicity bioassay, International Journal of Biological and Medical Sciences, 2, 3, 180. ; Nimkerdphol K. (2008), Effect of sodium hypochlorite on Zebrafish swimming behavior estimated by fractal dimension analysis, Journal of Bioscience and Bioengineering, 105, 5, 486, doi.org/10.1263/jbb.105.486 ; Phothisonothai M. (2005), EEG-based fractal analysis of different motor imagery tasks using critical exponent method, International Journal of Biological and Life Sciences, 1, 3, 175. ; Phothisonothai M. (2007), Fractal-based EEG data analysis of body parts movement imagery tasks, Journal of Physiological Sciences, 57, 4, 217, doi.org/10.2170/physiolsci.RP006307 ; Phinyomark A. (2011), Fractal Analysis of Surface Electromyography (EMG) Signal for Identify Hand Movements Using Critical Exponent Analysis, null, 703. ; Goge A. (2004), Investigating classification parameters for continuous myoelectrically controlled prostheses, null, 141. ; Esteller R. (2001), A comparison of waveform fractal dimension algorithms, IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 48, 2, 177, doi.org/10.1109/81.904882 ; Phinyomark A. (2010), Evaluation of EMG feature extraction for hand movement recognition based on Euclidean distance and standard deviation, null, 856. ; Phinyomark A. (2011), Evaluation of EMG feature extraction for movement control of upper limb prostheses based on class separation index, null, 750.

DOI

10.2478/v10178-011-0061-9

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