{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T17:02:58Z","timestamp":1778778178162,"version":"3.51.4"},"reference-count":151,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2020,5,7]],"date-time":"2020-05-07T00:00:00Z","timestamp":1588809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The surface electromyography (sEMG) records the electrical activity of muscle fibers during contraction: one of its uses is to assess changes taking place within muscles in the course of a fatiguing contraction to provide insights into our understanding of muscle fatigue in training protocols and rehabilitation medicine. Until recently, these myoelectric manifestations of muscle fatigue (MMF) have been assessed essentially by linear sEMG analyses. However, sEMG shows a complex behavior, due to many concurrent factors. Therefore, in the last years, complexity-based methods have been tentatively applied to the sEMG signal to better individuate the MMF onset during sustained contractions. In this review, after describing concisely the traditional linear methods employed to assess MMF we present the complexity methods used for sEMG analysis based on an extensive literature search. We show that some of these indices, like those derived from recurrence plots, from entropy or fractal analysis, can detect MMF efficiently. However, we also show that more work remains to be done to compare the complexity indices in terms of reliability and sensibility; to optimize the choice of embedding dimension, time delay and threshold distance in reconstructing the phase space; and to elucidate the relationship between complexity estimators and the physiologic phenomena underlying the onset of MMF in exercising muscles.<\/jats:p>","DOI":"10.3390\/e22050529","type":"journal-article","created":{"date-parts":[[2020,5,8]],"date-time":"2020-05-08T03:45:20Z","timestamp":1588909520000},"page":"529","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":137,"title":["Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9510-1653","authenticated-orcid":false,"given":"Susanna","family":"Rampichini","sequence":"first","affiliation":[{"name":"Department of Biomedical Sciences for Health, Universit\u00e0 degli Studi di Milano, 20133 Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6239-7301","authenticated-orcid":false,"given":"Taian Martins","family":"Vieira","sequence":"additional","affiliation":[{"name":"Laboratorio di Ingegneria del Sistema Neuromuscolare (LISiN), Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, 10129 Turin, Italy"},{"name":"PoliToBIOMed Lab, Politecnico di Torino, 10129 Turin, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8775-2605","authenticated-orcid":false,"given":"Paolo","family":"Castiglioni","sequence":"additional","affiliation":[{"name":"IRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, Italy"}]},{"given":"Giampiero","family":"Merati","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences for Health, Universit\u00e0 degli Studi di Milano, 20133 Milan, Italy"},{"name":"IRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/s00421-019-04264-w","article-title":"Peripheral fatigue: New mechanistic insights from recent technologies","volume":"120","author":"Longo","year":"2020","journal-title":"Eur. J. Appl. Physiol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1007\/s00421-013-2790-9","article-title":"Effects of fatigue on the electromechanical delay components in gastrocnemius medialis muscle","volume":"114","author":"Rampichini","year":"2014","journal-title":"Eur. J. Appl. Physiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1007\/BF00421103","article-title":"EMG frequency spectrum, muscle structure, and fatigue during dynamic contractions in man","volume":"42","author":"Komi","year":"1979","journal-title":"Eur. J. Appl. Physiol. Occup. Physiol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1878","DOI":"10.1152\/jappl.1991.71.5.1878","article-title":"pH-induced effects on median frequency and conduction velocity of the myoelectric signal","volume":"71","author":"Brody","year":"1991","journal-title":"J. Appl. Physiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1007\/s00421-017-3558-4","article-title":"Electromechanical delays during a fatiguing exercise and recovery in patients with myotonic dystrophy type 1","volume":"117","author":"Esposito","year":"2017","journal-title":"Eur. J. Appl. Physiol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"389","DOI":"10.2165\/00007256-200939050-00005","article-title":"Exercise and fatigue","volume":"39","author":"Ament","year":"2009","journal-title":"Sport. Med."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1347","DOI":"10.1080\/02640410903165093","article-title":"Acute passive stretching in a previously fatigued muscle: Electrical and mechanical response during tetanic stimulation","volume":"27","author":"Esposito","year":"2009","journal-title":"J. Sports Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1007\/s00221-003-1678-z","article-title":"Properties of human motor units after prolonged activity at a constant firing rate","volume":"154","author":"Johnson","year":"2004","journal-title":"Exp. Brain Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1016\/j.jelekin.2012.02.019","article-title":"Electromyographic models to assess muscle fatigue","volume":"22","author":"Malanda","year":"2012","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1159\/000140989","article-title":"Morphologic studies of motor units in normal human muscles","volume":"23","author":"Feinstein","year":"1955","journal-title":"Acta Anat. (Basel)"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1016\/0013-4694(80)90292-8","article-title":"Force gradation and motor unit activity during voluntary movements in man","volume":"48","author":"Mariani","year":"1980","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1152\/japplphysiol.00162.2014","article-title":"The extraction of neural strategies from the surface EMG: An update","volume":"117","author":"Farina","year":"2014","journal-title":"J. Appl. Physiol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1016\/j.jelekin.2007.08.007","article-title":"Fatigue analysis of interference EMG signals obtained from biceps brachii during isometric voluntary contraction at various force levels","volume":"19","author":"Dimitrova","year":"2009","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.jelekin.2010.10.006","article-title":"Unraveling the neurophysiology of muscle fatigue","volume":"21","author":"Enoka","year":"2011","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/S1050-6411(02)00083-4","article-title":"V Interpretation of EMG changes with fatigue: Facts, pitfalls, and fallacies","volume":"13","author":"Dimitrova","year":"2003","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1109\/PROC.1977.10544","article-title":"Interpretation of myoelectric power spectra: A model and its applications","volume":"65","author":"Magnusson","year":"1977","journal-title":"Proc. IEEE"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1007\/BF02442444","article-title":"Influences of electrode geometry on bipolar recordings of the surface electromyogram","volume":"16","author":"Lynn","year":"1978","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_18","first-page":"573","article-title":"Myoelectric manifestations of localized fatigue in humans","volume":"29","year":"1984","journal-title":"Crit. Rev. Biomed. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1109\/TBME.1987.326035","article-title":"Spatial Filtering of Noninvasive Multielectrode EMG: Part II-Filter Performance in Theory and Modeling","volume":"BME-34","author":"Reucher","year":"1987","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1097\/00004691-199709000-00009","article-title":"Near- and far-fields: Source characteristics and the conducting medium in neurophysiology","volume":"14","author":"Stegeman","year":"1997","journal-title":"J. Clin. Neurophysiol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1615\/CritRevBiomedEng.v38.i4.10","article-title":"Advances in surface EMG: Recent progress in detection and processing techniques","volume":"38","author":"Merletti","year":"2010","journal-title":"Crit. Rev. Biomed. Eng."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/0021-9290(93)90086-T","article-title":"Evaluation Of Methods To Minimize Cross Talk In Surface Electromyography","volume":"26","author":"Koh","year":"1993","journal-title":"J. Biomech."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1963","DOI":"10.1109\/TBME.2006.881760","article-title":"Estimation of motor unit conduction velocity from surface EMG recordings by signal-based selection of the spatial filters","volume":"53","author":"Mesin","year":"2006","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.jelekin.2009.08.005","article-title":"Methodological aspects of SEMG recordings for force estimation - A tutorial and review","volume":"20","author":"Staudenmann","year":"2010","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_25","first-page":"63","article-title":"Effect of electrode shape on spectral features of surface detected motor unit action potentials","volume":"26","author":"Farina","year":"2001","journal-title":"Acta Physiol. Pharmacol. Bulg."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1109\/TBME.1985.325550","article-title":"A Note on the Noninvasive Estimation of Muscle Fiber Conduction Velocity","volume":"BME-32","author":"Broman","year":"1985","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1007\/BF02350984","article-title":"Methods for estimating muscle fibre conduction velocity from surface electromyographic signals","volume":"42","author":"Farina","year":"2004","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.bspc.2015.07.001","article-title":"Amplitude indicators and spatial aliasing in high density surface electromyography recordings","volume":"22","author":"Afsharipour","year":"2015","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1007\/BF00237855","article-title":"Fixed patterns of rapid postural responses among leg muscles during stance","volume":"30","author":"Nashner","year":"1977","journal-title":"Exp. Brain Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1113\/jphysiol.1955.sp005282","article-title":"A detailed study of the electric potentials recorded over some postural muscles while relaxed and standing","volume":"127","author":"Joseph","year":"1955","journal-title":"J. Physiol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1016\/j.jbiomech.2011.11.010","article-title":"Inter-electrode spacing of surface EMG sensors: Reduction of crosstalk contamination during voluntary contractions","volume":"45","author":"Kuznetsov","year":"2012","journal-title":"J. Biomech."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-017-13369-1","article-title":"Specificity of surface EMG recordings for gastrocnemius during upright standing","volume":"7","author":"Vieira","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1016\/j.clinbiomech.2009.01.010","article-title":"Surface EMG based muscle fatigue evaluation in biomechanics","volume":"24","author":"Cifrek","year":"2009","journal-title":"Clin. Biomech."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3937254","DOI":"10.1155\/2017\/3937254","article-title":"EMG Processing Based Measures of Fatigue Assessment during Manual Lifting","volume":"2017","author":"Shair","year":"2017","journal-title":"Biomed Res. Int."},{"key":"ref_35","first-page":"17","article-title":"Surface electromyography: Why, when and how to use it","volume":"4","author":"Vieira","year":"2011","journal-title":"Rev. Andal. Med. Deporte"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1109\/10.284927","article-title":"Single Site Electromyograph Amplitude Estimation","volume":"41","author":"Clancy","year":"1994","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2144","DOI":"10.1152\/jn.2001.86.5.2144","article-title":"Experimental simulation of cat electromyogram: Evidence for algebraic summation of motor-unit action-potential trains","volume":"86","author":"Day","year":"2001","journal-title":"J. Neurophysiol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1152\/japplphysiol.00894.2004","article-title":"Influence of amplitude cancellation on the simulated surface electromyogram","volume":"98","author":"Keenan","year":"2005","journal-title":"J. Appl. Physiol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"985","DOI":"10.3389\/fphys.2017.00985","article-title":"Interpreting signal amplitudes in surface electromyography studies in sport and rehabilitation sciences","volume":"8","author":"Vigotsky","year":"2018","journal-title":"Front. Physiol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1249\/00003677-200607000-00006","article-title":"Interpretation of the surface electromyogram in dynamic contractions","volume":"34","author":"Farina","year":"2006","journal-title":"Exerc. Sport Sci. Rev."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1109\/10.99071","article-title":"Errors in frequency parameters of EMG power spectra","volume":"38","author":"Hof","year":"1991","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1109\/10.930899","article-title":"Time frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions","volume":"48","author":"Bonato","year":"2001","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.1152\/jappl.1990.68.3.1177","article-title":"Electromyogram power spectra frequencies associated with motor unit recruitment strategies","volume":"68","author":"Solomonow","year":"1990","journal-title":"J. Appl. Physiol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1109\/TBME.1983.325057","article-title":"Motor Unit Firing Rate During Static Contraction Indicated by the Surface EMG Power Spectrum","volume":"BME-30","author":"Schomaker","year":"1983","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1007\/s00422-002-0309-2","article-title":"Influence of anatomical, physical, and detection-system parameters on surface EMG","volume":"86","author":"Farina","year":"2002","journal-title":"Biol. Cybern."},{"key":"ref_46","unstructured":"Merletti, R., Balestra, G., and Knaflitz, M. (1989, January 9\u201312). Effect of FFT based algorithms on estimation of myoelectric signal spectral parameters. Proceedings of the Images of the Twenty-First Century. Proceedings of the Annual International Engineering in Medicine and Biology Society, Seattle, WA, USA."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"(1990). Kirkendal Mechanisms of peripheral fatigue.pdf. Med. Sci. Sports Exerc., 22, 444\u2013449.","DOI":"10.1249\/00005768-199008000-00004"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1810","DOI":"10.1152\/jappl.1990.69.5.1810","article-title":"Myoelectric manifestations of fatigue in voluntary and electrically elicited contractions","volume":"69","author":"Merletti","year":"1990","journal-title":"J. Appl. Physiol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"342","DOI":"10.2519\/jospt.1996.24.6.342","article-title":"Myoelectric and mechanical manifestations of muscle fatigue in voluntary contractions","volume":"24","author":"Merletti","year":"1996","journal-title":"J. Orthop. Sports Phys. Ther."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1016\/j.jelekin.2011.08.006","article-title":"Are the myoelectric manifestations of fatigue distributed regionally in the human medial gastrocnemius muscle?","volume":"21","author":"Gallina","year":"2011","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1007\/s00421-003-0967-3","article-title":"Neuromuscular response to sustained low-level muscle activation: Within- and between-synergist substitution in the triceps surae muscles","volume":"91","author":"McLean","year":"2004","journal-title":"Eur. J. Appl. Physiol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1152\/jn.00837.2004","article-title":"Motor-unit activity differs with load type during a fatiguing contraction","volume":"93","author":"Mottram","year":"2005","journal-title":"J. Neurophysiol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1152\/jn.01063.2005","article-title":"Rotation of motoneurons during prolonged isometric contractions in humans","volume":"96","author":"Bawa","year":"2006","journal-title":"J. Neurophysiol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1007\/BF00357632","article-title":"Motor unit recruitment during prolonged isometric contractions","volume":"67","author":"Fallentin","year":"1993","journal-title":"Eur. J. Appl. Physiol. Occup. Physiol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.jelekin.2004.08.007","article-title":"Comparison of Fourier and wavelet transform procedures for examining the mechanomyographic and electromyographic frequency domain responses during fatiguing isokinetic muscle actions of the biceps brachii","volume":"15","author":"Beck","year":"2005","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1109\/10.821766","article-title":"Time-frequency analysis of myoelectric signals during dynamic contractions: A comparative study","volume":"47","author":"Karlsson","year":"2000","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.jelekin.2007.01.006","article-title":"Correlations between short-time Fourier- and continuous wavelet transforms in the analysis of localized back and hip muscle fatigue during isometric contractions.pdf","volume":"18","author":"Coorevits","year":"2008","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1109\/86.867887","article-title":"Wavelet and short-time fourier transform analysis of electromyography for detection of back muscle fatigue","volume":"8","author":"Sparto","year":"2000","journal-title":"IEEE Trans. Rehabil. Eng."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1007\/s00421-012-2499-1","article-title":"Changes in surface EMG assessed by discrete wavelet transform during maximal isometric voluntary contractions following supramaximal cycling","volume":"113","author":"Silvestre","year":"2013","journal-title":"Eur. J. Appl. Physiol."},{"key":"ref_60","first-page":"313","article-title":"Physiology and Mathematics of Myoelectric Signals","volume":"26","year":"1979","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"953","DOI":"10.1002\/mus.880170819","article-title":"Fractal dimension of electromyographic signals recorded with surface electrodes during isometric contractions is linearly correlated with muscle activation","volume":"17","author":"Anmuth","year":"1994","journal-title":"Muscle Nerve"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"910","DOI":"10.1631\/jzus.2007.A0910","article-title":"Multifractal analysis of surface EMG signals for assessing muscle fatigue during static contractions","volume":"8","author":"Wang","year":"2007","journal-title":"J. Zhejiang Univ. Sci. A"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Merletti, R., and Parker, P.J. (2004). Electromyography: Physiology, Engineering, and Noninvasive Applications, Wiley-IEEE Press.","DOI":"10.1002\/0471678384"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Deligni\u00e8res, D., and Marmelat, V. (2013). Theoretical and methodological issues in serial correlation analysis. Advances in Experimental Medicine and Biology, Springer.","DOI":"10.1007\/978-1-4614-5465-6_7"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"R1","DOI":"10.1088\/0967-3334\/23\/1\/201","article-title":"Fractal characterization of complexity in temporal physiological signals","volume":"23","author":"Eke","year":"2002","journal-title":"Physiol. Meas."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1080\/00222890009601366","article-title":"Variability and noise in continuous force production","volume":"32","author":"Slifkin","year":"2000","journal-title":"J. Mot. Behav."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"2297","DOI":"10.1073\/pnas.88.6.2297","article-title":"Approximate entropy as a measure of system complexity","volume":"88","author":"Pincus","year":"1991","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_68","first-page":"421","article-title":"Fractals in physiology and medicine","volume":"60","author":"Goldberger","year":"1987","journal-title":"Yale J. Biol. Med."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"244103","DOI":"10.1103\/PhysRevLett.93.244103","article-title":"Long chaotic transients in complex networks","volume":"93","author":"Zumdieck","year":"2004","journal-title":"Phys. Rev. Lett."},{"key":"ref_70","unstructured":"Mandelbrot, B. (1977). Fractals: Form, Chance and Dimension, W.H.Freeman. [1st ed.]."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1016\/0165-0270(94)00164-C","article-title":"Fractal analysis of the electromyographic interference pattern","volume":"58","author":"Gitter","year":"1995","journal-title":"J. Neurosci. Methods"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Chakraborty, M., and Parbat, D. (2017, January 7\u20139). Fractals, chaos and entropy analysis to obtain parametric features of surface electromyography signals during dynamic contraction of biceps muscles under varying load. Proceedings of the 2017 2nd International Conference for Convergence in Technology (I2CT), Mumbai, India.","DOI":"10.1109\/I2CT.2017.8226125"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0010-4825(88)90041-8","article-title":"Fractals and the analysis of waveforms","volume":"18","author":"Katz","year":"1988","journal-title":"Comput. Biol. Med."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1016\/j.compbiomed.2010.10.001","article-title":"What is wrong in Katz\u2019s method? Comments on: \u201cA note on fractal dimensions of biomedical waveforms\u201d","volume":"40","author":"Castiglioni","year":"2010","journal-title":"Comput. Biol. Med."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Beretta-Piccoli, M., D\u2019Antona, G., Barbero, M., Fisher, B., Dieli-Conwright, C.M., Clijsen, R., and Cescon, C. (2015). Evaluation of central and peripheral fatigue in the quadriceps using fractal dimension and conduction velocity in young females. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0123921"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1016\/j.jelekin.2012.06.005","article-title":"Sample entropy analysis of surface EMG for improved muscle activity onset detection against spurious background spikes","volume":"22","author":"Zhang","year":"2012","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1088\/0967-3334\/37\/1\/162","article-title":"Muscle fiber conduction velocity and fractal dimension of EMG during fatiguing contraction of young and elderly active men","volume":"37","author":"Boccia","year":"2016","journal-title":"Physiol. Meas."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1016\/j.jelekin.2008.08.003","article-title":"A bi-dimensional index for the selective assessment of myoelectric manifestations of peripheral and central muscle fatigue","volume":"19","author":"Mesin","year":"2009","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_79","unstructured":"Xu, Z., and Xiao, S. (November, January 30). Fractal dimension of surface EMG and its determinants. Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. \u2018Magnificent Milestones and Emerging Opportunities in Medical Engineering\u2019 (Cat. No.97CH36136), Chicago, IL, USA."},{"key":"ref_80","first-page":"5373846","article-title":"Relationship between Isometric Muscle Force and Fractal Dimension of Surface Electromyogram","volume":"2018","author":"Boccia","year":"2018","journal-title":"Biomed Res. Int."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.gaitpost.2008.04.002","article-title":"Assessment of force and fatigue in isometric contractions of the upper trapezius muscle by surface EMG signal and perceived exertion scale","volume":"28","author":"Troiano","year":"2008","journal-title":"Gait Posture"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1080\/10255842.2012.675055","article-title":"Computation of fractal features based on the fractal analysis of surface Electromyogram to estimate force of contraction of different muscles","volume":"17","author":"Kumar","year":"2014","journal-title":"Comput. Methods Biomech. Biomed. Eng."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"616","DOI":"10.1088\/1361-6579\/aa614c","article-title":"Test-retest reliability of muscle fiber conduction velocity and fractal dimension of surface EMG during isometric contractions","volume":"38","author":"Zampella","year":"2017","journal-title":"Physiol. Meas."},{"key":"ref_84","unstructured":"Lin, S.Y., Hung, C.I., Wang, H.I., Wu, Y.T., and Wang, P.S. (2015, January 15\u201317). Extraction of physically fatigue feature in exercise using electromyography, electroencephalography and electrocardiography. Proceedings of the 2015 11th International Conference on Natural Computation (ICNC), Zhangjiajie, China."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Meduri, F., Beretta-Piccoli, M., Calanni, L., Segreto, V., Giovanetti, G., Barbero, M., Cescon, C., and D\u2019Antona, G. (2016). Inter-Gender sEMG evaluation of central and peripheral fatigue in biceps brachii of young healthy subjects. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0168443"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1530","DOI":"10.1016\/j.medengphy.2016.09.022","article-title":"Motor unit firing rates and synchronisation affect the fractal dimension of simulated surface electromyogram during isometric\/isotonic contraction of vastus lateralis muscle","volume":"38","author":"Mesin","year":"2016","journal-title":"Med. Eng. Phys."},{"key":"ref_87","first-page":"1685","article-title":"Mosaic Organization of DNA nucleotides","volume":"49","author":"Peng","year":"2014","journal-title":"Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Top."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"115","DOI":"10.3389\/fphys.2019.00115","article-title":"A fast DFA algorithm for multifractal multiscale analysis of physiological time series","volume":"10","author":"Castiglioni","year":"2019","journal-title":"Front. Physiol."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/S0378-4371(01)00144-3","article-title":"Detecting long-range correlations with detrended fluctuation analysis","volume":"295","author":"Kantelhardt","year":"2001","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"533","DOI":"10.3389\/fphys.2017.00533","article-title":"Decomposing multifractal crossovers","volume":"8","author":"Nagy","year":"2017","journal-title":"Front. Physiol."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"2085","DOI":"10.1113\/jphysiol.2015.284380","article-title":"Fatigue reduces the complexity of knee extensor torque fluctuations during maximal and submaximal intermittent isometric contractions in man","volume":"593","author":"Pethick","year":"2015","journal-title":"J. Physiol."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"1349","DOI":"10.1080\/17461391.2019.1599450","article-title":"Fatigue reduces the complexity of knee extensor torque during fatiguing sustained isometric contractions","volume":"19","author":"Pethick","year":"2019","journal-title":"Eur. J. Sport Sci."},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Hernandez, L., and Camic, C. (2019). Fatigue-Mediated Loss of Complexity is Contraction-Type Dependent in Vastus Lateralis Electromyographic Signals. Sports, 7.","DOI":"10.3390\/sports7040078"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1016\/j.jelekin.2014.08.006","article-title":"The neural control of coactivation during fatiguing contractions revisited","volume":"24","author":"Duchateau","year":"2014","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"2628","DOI":"10.1152\/jappl.2001.91.6.2628","article-title":"Activation of human quadriceps femoris during isometric, concentric, and eccentric contractions","volume":"91","author":"Babault","year":"2001","journal-title":"J. Appl. Physiol."},{"key":"ref_96","first-page":"412","article-title":"Mechanomyographic and electromyographic responses of the vastus medialis muscle during isometric and concentric muscle actions","volume":"19","author":"Coburn","year":"2005","journal-title":"J. Strength Cond. Res."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1016\/S1050-6411(00)00031-6","article-title":"Different neuromuscular recruitment patterns during eccentric, concentric and isometric contractions","volume":"10","author":"Kay","year":"2000","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/S0378-4371(02)01383-3","article-title":"Multifractal detrended fluctuation analysis of nonstationary time series","volume":"316","author":"Kantelhardt","year":"2002","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_99","first-page":"S1157","article-title":"The detection of long-range correlations of operation force and sEMG with multifractal detrended fluctuation analysis","volume":"26","author":"Li","year":"2015","journal-title":"Biomed. Mater. Eng."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/j.jelekin.2009.06.002","article-title":"Fatigue estimation using a novel multi-fractal detrended fluctuation analysis-based approach","volume":"20","author":"Talebinejad","year":"2010","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_101","first-page":"49","article-title":"Evidence of deterministic chaos in the myoelectric signal","volume":"36","author":"Nieminen","year":"1996","journal-title":"Electromyogr. Clin. Neurophysiol."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1142\/S0218127491000403","article-title":"Nonlinear Time Sequence Analysis","volume":"3","author":"Grassberger","year":"1991","journal-title":"Int. J. Bifurc. Chaos"},{"key":"ref_103","unstructured":"Bodruzzaman, M., Devgan, S., and Kari, S. (1992, January 12\u201315). Chaotic classification of electromyographic (EMG) signals via correlation dimension measurement. Proceedings of the IEEE Southeastcon\u201992, Birmingham, AL, USA."},{"key":"ref_104","unstructured":"Padmanabhan, P., and Puthusserypady, S. (2004, January 1\u20135). Nonlinear analysis of EMG signals-A chaotic approach. Proceedings of the 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Francisco, CA, USA."},{"key":"ref_105","unstructured":"Yanli, M., Yuping, L., and Bingzheng, L. (2006, January 17\u201318). Test nonlinear determinacy of electromyogram. Proceedings of the 27th Annual Conference on IEEE Engineering in Medicine and Biology, Shanghai, China."},{"key":"ref_106","first-page":"329","article-title":"Chaotic analysis of electromyography signal at low back and lower limb muscles during forward bending posture","volume":"45","author":"Swie","year":"2005","journal-title":"Electromyogr. Clin. Neurophysiol."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"e206","DOI":"10.1016\/j.jelekin.2008.02.008","article-title":"Novel parameters of surface EMG in patients with Parkinson\u2019s disease and healthy young and old controls","volume":"19","author":"Meigal","year":"2009","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"284308","DOI":"10.1155\/2014\/284308","article-title":"The analysis of surface EMG signals with the wavelet-based correlation dimension method","volume":"2014","author":"Wang","year":"2014","journal-title":"Comput. Math. Methods Med."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"596","DOI":"10.1063\/1.1488255","article-title":"Recurrence plots and unstable periodic orbits","volume":"12","author":"Bradley","year":"2002","journal-title":"Chaos"},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1209\/0295-5075\/4\/9\/004","article-title":"Recurrence plots of dynamical systems","volume":"4","author":"Eckmann","year":"1987","journal-title":"Epl"},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1152\/jappl.1994.76.2.965","article-title":"Dynamical assessment of physiological systems and states using recurrence plot strategies","volume":"76","author":"Webber","year":"1994","journal-title":"J. Appl. Physiol."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"3467","DOI":"10.1142\/S0218127407019226","article-title":"Recurrence quantifications: Feature extractions from recurrence plots","volume":"17","author":"Webber","year":"2007","journal-title":"Int. J. Bifurc. Chaos"},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1016\/S1350-4533(99)00073-9","article-title":"Detection of hidden rhythms in surface EMG signals with a non-linear time-series tool","volume":"21","author":"Filligoi","year":"1999","journal-title":"Med. Eng. Phys."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1152\/jappl.1995.78.3.814","article-title":"Influence of isometric loading on biceps EMG dynamics as assessed by linear and nonlinear tools","volume":"78","author":"Webber","year":"1995","journal-title":"J. Appl. Physiol."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.jneumeth.2004.09.018","article-title":"Influence of high motor unit synchronization levels on non-linear and spectral variables of the surface EMG","volume":"143","author":"Fattorini","year":"2005","journal-title":"J. Neurosci. Methods"},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"1753","DOI":"10.1152\/japplphysiol.00314.2002","article-title":"Nonlinear surface EMG analysis to detect changes of motor unit conduction velocity and synchronization","volume":"93","author":"Farina","year":"2002","journal-title":"J. Appl. Physiol."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.bspc.2007.10.003","article-title":"Moving approximate entropy applied to surface electromyographic signals","volume":"3","author":"Ahmad","year":"2008","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1007\/s00221-006-0734-x","article-title":"Recurrence quantification analysis of surface EMG detects changes in motor unit synchronization induced by recurrent inhibition","volume":"178","author":"Gelli","year":"2007","journal-title":"Exp. Brain Res."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.jneumeth.2011.01.005","article-title":"Reliability of EMG determinism to detect changes in motor unit synchrony and coherence during submaximal contraction","volume":"196","author":"Schmied","year":"2011","journal-title":"J. Neurosci. Methods"},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.jneumeth.2008.09.023","article-title":"Recurrence quantification analysis of surface electromyographic signal: Sensitivity to potentiation and neuromuscular fatigue","volume":"177","author":"Morana","year":"2009","journal-title":"J. Neurosci. Methods"},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"1260","DOI":"10.1016\/j.medengphy.2016.09.009","article-title":"Comparison of algorithms to quantify muscle fatigue in upper limb muscles based on sEMG signals","volume":"38","author":"Kahl","year":"2016","journal-title":"Med. Eng. Phys."},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1007\/s004210100488","article-title":"Effect of human exposure to altitude on muscle endurance during isometric contractions","volume":"85","author":"Felici","year":"2001","journal-title":"Eur. J. Appl. Physiol."},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1007\/s004220050591","article-title":"Nonlinear time-course of lumbar muscle fatigue using recurrence quantifications","volume":"82","author":"Ikegawa","year":"2000","journal-title":"Biol. Cybern."},{"key":"ref_124","unstructured":"Yang, H.C., Wang, D.M., and Wang, J. (2006, January 17\u201318). Linear and non-linear features of surface EMG during fatigue and recovery period. Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, China."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"3847","DOI":"10.1007\/s00421-012-2358-0","article-title":"Evaluation of muscle fatigue of wheelchair basketball players with spinal cord injury using recurrence quantification analysis of surface EMG","volume":"112","author":"Uzun","year":"2012","journal-title":"Eur. J. Appl. Physiol."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1007\/s004210000364","article-title":"Linear and non-linear analysis of surface electromyograms in weightlifters","volume":"84","author":"Felici","year":"2001","journal-title":"Eur. J. Appl. Physiol."},{"key":"ref_127","doi-asserted-by":"crossref","unstructured":"Ito, K., and Hotta, Y. (September, January 28). EMG-based detection of muscle fatigue during low-level isometric contraction by recurrence quantification analysis and monopolar configuration. Proceedings of the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, CA, USA.","DOI":"10.1109\/EMBC.2012.6346902"},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"H2039","DOI":"10.1152\/ajpheart.2000.278.6.H2039","article-title":"Physiological time-series analysis using approximate entropy and sample entropy maturity in premature infants Physiological time-series analysis using approximate entropy and sample entropy","volume":"278","author":"Richman","year":"2000","journal-title":"Am. J. Physiol. Heart Circ. Physiol."},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"1483","DOI":"10.1007\/s10439-010-9933-5","article-title":"Fuzzy approximate entropy analysis of chaotic and natural complex systems: Detecting muscle fatigue using electromyography signals","volume":"38","author":"Xie","year":"2010","journal-title":"Ann. Biomed. Eng."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/TBME.2005.859786","article-title":"Assessment of the autonomic control of heart rate variability in healthy and spinal-cord injured subjects: Contribution of different complexity-based estimators","volume":"53","author":"Merati","year":"2006","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.medengphy.2008.04.005","article-title":"Measuring complexity using FuzzyEn, ApEn, and SampEn","volume":"31","author":"Chen","year":"2009","journal-title":"Med. Eng. Phys."},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"2871","DOI":"10.1016\/j.asoc.2010.11.020","article-title":"Complexity analysis of the biomedical signal using fuzzy entropy measurement","volume":"11","author":"Xie","year":"2011","journal-title":"Appl. Soft Comput. J."},{"key":"ref_133","doi-asserted-by":"crossref","unstructured":"Navaneethakrishna, M., and Ramakrishnan, S. (2014, January 26\u201330). Multiscale feature based analysis of surface EMG signals under fatigue and non-fatigue conditions. Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, IL, USA.","DOI":"10.1109\/EMBC.2014.6944655"},{"key":"ref_134","doi-asserted-by":"crossref","unstructured":"Zhu, X., Zhang, X., Tang, X., Gao, X., and Chen, X. (2017). Re-evaluating electromyogram-force relation in healthy biceps brachii muscles using complexity measures. Entropy, 19.","DOI":"10.3390\/e19110624"},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"068102","DOI":"10.1103\/PhysRevLett.89.068102","article-title":"Multiscale Entropy Analysis of Complex Physiologic Time Series","volume":"89","author":"Costa","year":"2002","journal-title":"Phys. Rev. Lett."},{"key":"ref_136","doi-asserted-by":"crossref","unstructured":"Castiglioni, P., Coruzzi, P., Bini, M., Parati, G., and Faini, A. (2017). Multiscale Sample Entropy of cardiovascular signals: Does the choice between fixed- or varying-tolerance among scales influence its evaluation and interpretation?. Entropy, 19.","DOI":"10.3390\/e19110590"},{"key":"ref_137","doi-asserted-by":"crossref","unstructured":"Castiglioni, P., Parati, G., and Faini, A. (2019). Information-domain analysis of cardiovascular complexity: Night and day modulations of entropy and the effects of hypertension. Entropy, 21.","DOI":"10.3390\/e21060550"},{"key":"ref_138","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.jelekin.2012.08.004","article-title":"Muscle fatigue and contraction intensity modulates the complexity of surface electromyography","volume":"23","author":"Cashaback","year":"2013","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"066010","DOI":"10.1088\/1741-2560\/8\/6\/066010","article-title":"Characterizing the complexity of spontaneous motor unit patterns of amyotrophic lateral sclerosis using approximate entropy","volume":"8","author":"Zhou","year":"2011","journal-title":"J. Neural Eng."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"2785","DOI":"10.1142\/S0218127400001870","article-title":"Testing For Nonlinearity Of The Contraction Segments In Uterine Electromyography","volume":"10","author":"Radhakrishnan","year":"2000","journal-title":"Int. J. Bifurc. Chaos Appl. Sci."},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"2466","DOI":"10.1073\/pnas.012579499","article-title":"Fractal dynamics in physiology: Alterations with disease and aging","volume":"99","author":"Goldberger","year":"2002","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_142","doi-asserted-by":"crossref","unstructured":"Navaneethakrishna, M., Karthick, P.A., and Ramakrishnan, S. (2015, January 25\u201329). Analysis of biceps brachii sEMG signal using Multiscale Fuzzy Approximate Entropy. Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, Italy.","DOI":"10.1109\/EMBC.2015.7320219"},{"key":"ref_143","doi-asserted-by":"crossref","unstructured":"Tong, H., Zhang, X., Ma, H., Chen, Y., and Chen, X. (2016). Fatiguing effects on the multi-scale entropy of surface electromyography in children with cerebral palsy. Entropy, 18.","DOI":"10.3390\/e18050177"},{"key":"ref_144","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/0167-2789(85)90011-9","article-title":"Determining Lyapunov exponents from a time series","volume":"16","author":"Wolf","year":"1985","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/0167-2789(93)90009-P","article-title":"A practical method for calculating largest Lyapunov exponents from small data sets","volume":"65","author":"Rosenstein","year":"1993","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/S0167-2789(97)00118-8","article-title":"Practical method for determining the minimum embedding dimension of a scalar time series","volume":"110","author":"Cao","year":"1997","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_147","first-page":"066138","article-title":"Estimating mutual information","volume":"68","author":"Kraskov","year":"2004","journal-title":"Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Top."},{"key":"ref_148","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1016\/j.jbiomech.2014.01.033","article-title":"Comparing the local dynamic stability of trunk movements between varsity athletes with and without non-specific low back pain","volume":"47","author":"Graham","year":"2014","journal-title":"J. Biomech."},{"key":"ref_149","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/S1050-6411(00)00042-0","article-title":"Exercise induced muscle damage and recovery assessed by means of linear and non-linear sEMG analysis and ultrasonography","volume":"11","author":"Sbriccoli","year":"2001","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_150","first-page":"1369","article-title":"Analysis of complex time series using refined composite multiscale entropy","volume":"378","author":"Wu","year":"2014","journal-title":"Phys. Lett. Sect. A Gen. At. Solid State Phys."},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"1768264","DOI":"10.1155\/2017\/1768264","article-title":"Efficient computation of multiscale entropy over short biomedical time series based on linear state-space models","volume":"2017","author":"Faes","year":"2017","journal-title":"Complexity"}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/22\/5\/529\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:26:26Z","timestamp":1760174786000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/22\/5\/529"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,7]]},"references-count":151,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["e22050529"],"URL":"https:\/\/doi.org\/10.3390\/e22050529","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,7]]}}}