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Introduction

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Multifractals and Chronic Diseases of the Central Nervous System

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Abstract

Disease of the central nervous system has been described in the literature as a group of neurological disorders for which the function of the brain or spinal cord is affected. This chapter outlines the general description of the diseases like epilepsy, Parkinson’s, Huntington’s, Alzheimer’s, and motor neuron diseases. Also a discussion on the diagnostic tools and the methodologies adapted is reviewed in detail.

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References

  • Abbound S, Berenfeld O, Sadeh D (1991) Simulation of high- resolution QRS complex using ventricular model with a fractal conduction system. Effects of ischemia on high-frequency QRS potentials. Circ Res 68:1751–1760

    Article  Google Scholar 

  • Acharya UR, Chua CK, Lim TC, Dorithy, Suri JS (2009) Automatic identification of epileptic EEG signals using nonlinear parameters. J Mech Med Biol 9:539–553

    Article  Google Scholar 

  • Acharya UR, Filippo Molinari S, Sree V, Chattopadhyay S, Ng KH et al (2012a) Automated diagnosis of epileptic EEG using entropies. Biomed Signal Process Control 7:401–408

    Article  Google Scholar 

  • Acharya UR, Sree SV, Alvin APC, Yanti R, Suri JS (2012b) Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals. Int J Neural Syst 22:1250002

    Article  PubMed  Google Scholar 

  • Addison PS (2002) The illustrated wavelet transform handbook. Institute of Physics Publishing, London

    Book  Google Scholar 

  • Afsar O, Tirnakli U, Kurths J (2016) Entropy-based complexity measures for gait data of patients with Parkinson’s disease. Chaos 26:023115

    Article  PubMed  Google Scholar 

  • Aike G, Huiming L (1994) Complexity of the brain and neural dynamics. Sci Technol Rev:4

    Google Scholar 

  • Alados CL, Huffman MA (2000) Fractal long-range correlations in behavioural sequences of wild chimpanzees: a non-invasive analytical tool for the evaluation of health. Ethnology 106:105–116

    Google Scholar 

  • Al-Angari HM, Sahakian AV (2007) Use of sample entropy approach to study heart rate variability in obstructive sleep apnea syndrome. IEEE Trans Biomed Eng 54:1900–1904

    Article  PubMed  Google Scholar 

  • Alessio E, Carbone A, Castelli G, Frappietro V (2002) Second-order moving average and scaling of stochastic time. Eur Phys J B 27:197–200

    CAS  Google Scholar 

  • Alotaiby TN, Abd El-Samie FE, Alshebeili SA, Aljibreen KH, Alkhanen E (2015) Seizure detection with common spatial pattern and support vector machines. In: 2015 International conference on Information and Communication Technology Research (ICTRC), pp 152–155

    Google Scholar 

  • Al-Qazzaz NK, Abdulazez IF, Ridha SA (2014a) Simulation recording of an ECG, PCG, and PPG for feature extractions. Al-Khwarizmi Eng J 10:81–91

    Google Scholar 

  • Al-Qazzaz N, Ali S, Ahmad S, Chellappan A, Islam K et al (2014b) Role of EEG as biomarker in the early detection and classification of dementia. Sci World J 2014:Article ID 906038

    Article  Google Scholar 

  • Amaral LAN, Ivanov PC, Aoyagi N, Hidaka I, Tomono S et al (2001) Behavioral-independent features of complex heartbeat dynamics. Phys Rev Lett 86:6026–6029

    Article  CAS  Google Scholar 

  • Anderson C, Stolz E, Shamsunder S (1998) Multivariate autoregressive models for classification of spontaneous electroencephalographic signals during mental tasks. IEEE Trans Biomed Eng 45:277–286

    Article  CAS  PubMed  Google Scholar 

  • Andrade OA, Nasuto S, Kyberd P, Sweeney-Reed CM, van Kanijn FR (2006) EMG signal filtering based on empirical mode decomposition. Biomed Signal Process Control 1:44–55

    Article  Google Scholar 

  • Andrzejak RG, Lehnertz K, Mormann F, Rieke C, David P et al (2001) Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state. Phys Rev E 64:061907

    Article  CAS  Google Scholar 

  • Anh V, Yu ZG, Wanliss JA (2007) Analysis of global geomagnetic variability. Nonlinear Process Geophys 14:701–708

    Article  Google Scholar 

  • Arjunan SP, Kumar DK (2007) Fractal theory based non-linear analysis of SEMG. In: 3rd International conference on Intelligent Sensors, Sensor Networks and Information, Melbourne, Australia, Dec. 3–6, pp 545–548

    Google Scholar 

  • Arjunan SP, Kumar DK (2010) Decoding subtle forearm flexions using fractal features of surface electromyogram from single and multiple sensors. J Neuroeng Rehabil 7:53

    Article  PubMed  PubMed Central  Google Scholar 

  • Arneodo A, Bacry E, Graves PV, Muzy JF (1995) Characterizing long-range correlations in DNA sequences from wavelet analysis. Phys Rev Lett 74:3293–3296

    Article  CAS  PubMed  Google Scholar 

  • Arneodo A, Decoster N, Roux SG (2000) A wavelet-based method for multifractal image analysis. I. Methodology and test applications on isotropic and anisotropic random rough surfaces. Eur Phys J B 15:567–600

    Article  CAS  Google Scholar 

  • Arneodo A, Audit B, Decoster N, Muzy JF, Vaillant C (2002) Wavelet based multifractal formalism: applications to DNA sequences, satellite images of the cloud structure, and stock market data. In: Bunde A, Kropp J, Schellnhuber H-J (eds) The science of disaster: climate disruptions, market crashes and heart attacks. Springer, Berlin, pp 27–102

    Google Scholar 

  • Artemiadis P, Kyriakopoulos K (2011) A switching regime model for the EMG-based control of a robot arm. IEEE Trans Syst Man Cybern B Cybern 41:53–63

    Article  PubMed  Google Scholar 

  • Aubert AE, Beckers F, Seps B (2002) Non-linear dynamics of heart rate variability in athletes: effect of training. Comput Cardiol 29:441–444

    Article  Google Scholar 

  • Augustine A, Prakash RD, Xavier R, Parassery MC (2016) Review of signal processing techniques for detection of power quality events. Am J Eng Appl Sci 9:364–370

    Article  Google Scholar 

  • Aung YM, Al-Jumaily A (2013) Estimation of upper limb joint angle using surface EMG signal. Int J Adv Robot Syst 10:369

    Article  Google Scholar 

  • Ayers S (1997) The application of chaos theory to psychology. Theory Psychol 7:373–398

    Article  Google Scholar 

  • Babloyantz A (1989) Estimation of correlation dimensions from single and multichannel recordings – a critical view. Brain Dyn 2:122–130

    Article  Google Scholar 

  • Babloyantz A, Salazar JM, Nicolis C (1985) Evidence of chaotic dynamics of brain activity during the sleep cycle. Phys Lett 111A:152–156

    Article  Google Scholar 

  • Bacry E, Delour J, Muzy JF (2001) Multifractal random walk. Phys Rev E 64:026103

    Article  CAS  Google Scholar 

  • Bahar S, Kantelhardt JW, Neiman A, Rego HHA, Russell DF et al (2001) Long-range temporal anticorrelations in paddlefish electroreceptors. Europhys Lett 56:454

    Article  CAS  Google Scholar 

  • Barabasi AL, Vicsek T (1991) Multifractality of self-affine fractals. Phys Rev A 44:2730

    Article  CAS  PubMed  Google Scholar 

  • Barsky RB, Miron JA (1989) The seasonal cycle and the business cycle. J Polit Econ 97(3):503–534

    Article  Google Scholar 

  • Bartsch R, Plotnik M, Kantelhardt JW, Havlin S, Giladi N, Hausdorff JM (2007) Fluctuation and synchronization of gait intervals and gait force profiles distinguish stages of Parkinson's disease. Physica A: Statistical Mechanics and its Applications 383(2):455–465

    Article  PubMed  Google Scholar 

  • Baspinar U, Varol HS, Senyurek VY (2013) Performance Comparison of Artificial Neural Network and Gaussian Mixture Model in Classifying Hand Motions by Using sEMG Signals. Biocybernetics and Biomedical Engineering 33(1):33–45

    Article  Google Scholar 

  • Bassingthwaighte J, Van Beek J, King R (1990) Fractal branchings: the basis of myocardial flow heterogeneities? Ann N Y Acad Sci 591:392–401

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bassingthwaighte JB, Liebovitch LS, West BJ (1994) Fractal physiology. Oxford University Press, New York, p 364

    Book  Google Scholar 

  • Baumert M, Czippelova B, Ganesan A, Schmidt M, Zaunseder S, Javorka M (2014) Entropy analysis of RR and QT interval variability during orthostatic and mental stress in healthy subjects. Entropy 16:6384–6393

    Article  Google Scholar 

  • Behbahani S, Jafarnia Dabanloo N, Motie Nasrabadi AA, Teixeira C, Dourado A (2013) Pre-ictal heart rate variability assessment of epileptic seizures by means of linear and non-linear analyses. Anatol J Cardiol 13:797–803

    Google Scholar 

  • Behnia M, Kelly J (1991) Role of electromyography in amyotrophic lateral sclerosis. Muscle Nerve 14:1236–1241

    Article  CAS  PubMed  Google Scholar 

  • Belbasis A, Fuss FK (2018) Muscle performance investigated with a novel smart compression garment based on pressure sensor force myography and its validation against EMG. Front Physiol 9:408

    Article  PubMed  PubMed Central  Google Scholar 

  • Bennasar M, Hicks Y, Clinch S, Jones P, Rosser A (2016) Huntington’s disease assessment using tri axis accelerometers. Comput Sci 96:1193–1201

    Google Scholar 

  • Benson CC, Partha S, Lajish VL, Kumar R (2017) Fractal analysis of MRI data for the improved characterization of brain tumors. Adv Comput Sci Technol 10:1305–1315

    Google Scholar 

  • Berger H (1929) Über das Elektrenkephalogramm des Menschen (On the EEG in humans). Archiv fur Psychiatrie Nervenkrankheiten 87:527–570

    Article  Google Scholar 

  • Berntson GG, Bigger JT Jr, Eckberg DL, Grossman P, Kaufmann PG et al (1997) Heart rate variability: origins, methods, and interpretive caveats. Psychophysiology 34:623–648

    Article  CAS  PubMed  Google Scholar 

  • Bhaduri A, Ghosh D (2016) Quantitative assessment of heart rate dynamics during meditation: an ECG based study with multi Fractality and visibility graph. Front Physiol 7:44

    Article  PubMed  PubMed Central  Google Scholar 

  • Bhavaraju NC, Frei MG, Osorio I (2006) Analog seizure detection and performance evaluation. IEEE Trans Biomed Eng 53:238–245

    Article  PubMed  Google Scholar 

  • Bianchetti A, Trabucch M (2001) Clinical aspects of Alzheimer’s disease. Aging Clin Exp Res 13:221–130

    Article  CAS  Google Scholar 

  • Bilodeau M, Cincera M, Arsenault AB, Gravel D (1997) Normality and stationarity of EMG signals of elbow flexor muscles during ramp and step isometric contractions. J Electromyogr Kinesiol 7:87–96

    Article  CAS  PubMed  Google Scholar 

  • Bishop SM, Yarham SI, Navapurkar VU, Menon DK, Ercole A (2012) Multifractal analysis of hemodynamic behavior intraoperative instability and its pharmacological manipulation. Anesthesiology 117:810–821

    Article  PubMed  Google Scholar 

  • Blesic S, Milosevic S, Stratimirovic D, Ljubisavljevic M (1999) Detrended fluctuation analysis of time series of a firing fusimotor neuron. Physica A 268:275–282

    Article  Google Scholar 

  • Block A, Von Bloh W, Schellnhuber HJ (1990) Efficient box-counting determination of generalized fractal dimensions. Phys Rev A 42:1869–1874

    Article  CAS  PubMed  Google Scholar 

  • Bogunovic N, Jovic A (2010) Processing and Analysis of biomedical nonlinear signals by data mining methods. In: IWSSIP 2010–17th international conference on Systems, Signals and Image Processing, pp 276–279

    Google Scholar 

  • Bronzino JD (2000) The biomedical engineering handbook. A CRC handbook published in Cooperation with IEEE Press, pp 184–185

    Google Scholar 

  • Brown CT, Witschey WRT (2003) The fractal geometry of ancient Maya settlement. J Archaeol Sci 30:1619–1632

    Article  Google Scholar 

  • Bu N, Okamoto M, Tsuji T (2009) A hybrid motion classification approach for EMG-based human-robot interfaces using Bayesian and neural networks. IEEE Trans Robot 25:502–511

    Article  Google Scholar 

  • Buczkowski S, Hildgen P, Cartilier L (1998) Measurements of fractal dimension by box-counting: a critical analysis of data scatter. Physica A 252:23–34

    Article  Google Scholar 

  • Buldyrev SV, Goldberger AL, Havlin S, Mantegna RN, Matsa ME et al (1995) Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis. Phys Rev E 51:5084

    Article  CAS  Google Scholar 

  • Bunde A, Havlin S, Kantelhardt JW, Penzel T, Peter JH et al (2000) Correlated and uncorrelated regions in heart-rate fluctuations during sleep. Phys Rev Lett 85:3736–3739

    Article  CAS  PubMed  Google Scholar 

  • Bylsma FW, Peyser CE, Folstein SE, Folstein MF, Ross C et al (1994) EEG power spectra in Huntington’s disease: clinical and neuropsychological correlates. Neuropsychologia 32:137–150

    Article  CAS  PubMed  Google Scholar 

  • Cashaback JG, Cluff T, Potvin JR (2013) Muscle fatigue and contraction intensity modulates the complexity of surface electromyography. J Electromyogr Kinesiol 23:78–83

    Article  PubMed  Google Scholar 

  • Castiglioni P, Lazzeroni D, Brambilla V, Coruzzi P, Faini A (2017) Multifractal multiscale dfa of cardiovascular time series: differences in complex dynamics of systolic blood pressure, diastolic blood pressure and heart rate. in Proceedings of the 2017 39th Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 3477–3480, Jeju Island, South Korea, July 2017

    Google Scholar 

  • Chen X, Liu A, Peng H, Ward RK (2014) A preliminary study of muscular artifact cancellation in single-channel EEG. Sensors 14:18370–18389

    Article  PubMed  PubMed Central  Google Scholar 

  • Chorage SS, Sonone AB (2017) DWT based identification of amyotrophic lateral sclerosis using surface EMG signal. Int J Res Eng Appl Manag 3:31–35

    Google Scholar 

  • Chowdhury RH, Reaz MBI, Ali MABM, Bakar AAA, Chellappan K et al (2013) Surface electromyography signal processing and classification techniques. Sensors 13:12431–12466

    Article  PubMed  PubMed Central  Google Scholar 

  • Clancy EA, Liu L, Pu L, Moyer DVZ (2012) Identification of constant-posture EMG-torque relationship about the elbow using nonlinear dynamic models. IEEE Trans Biomed Eng 59:205–212

    Article  PubMed  Google Scholar 

  • Claus JJ, Ongerboer deVisser BW, Walstra JM, Hijdra A, Verbeeten B Jr, van Gool WA (1998) Quantitative spectral electroencephalography in predicting survival in patients with early Alzheimer disease. Arch Neurol 55:1105–1111

    Article  CAS  PubMed  Google Scholar 

  • Claus JJ, Ongerboer de Visser BW, Bour LJ et al (2000) Determinants of quantitative spectral electroencephalography in early Alzheimer’s disease: cognitive function, regional cerebral bloodflow, and computed tomography. Dement Geriatr Cogn Disord 11:81–89

    Article  CAS  PubMed  Google Scholar 

  • Colliot O, Chételat G, Chupin M, Desgranges B, Magnin B et al (2008) Discrimination between Alzheimer disease, mild cognitive impairment, and normal aging by using automated segmentation of the hippocampus. Radiology 248:194–201

    Article  PubMed  Google Scholar 

  • Conte E, Ware K, Marvulli R, Ianieri G, Megna M et al (2015) Chaos, fractal and recurrence quantification analysis of surface electromyography in muscular dystrophy. World J Neurosci 5:205–257

    Article  Google Scholar 

  • Costa M, Goldberger AL, Peng CK (2002) Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett 89:068102

    Article  PubMed  CAS  Google Scholar 

  • D’Addio G, Romano M, Maresca L, Bifulco P, Giallauria F, et al (2014) Fractal behavior of heart rate variability during ECG stress test in cardiac patients. In: 8th Conference of the European Study Group on Cardiovascular Oscillations, ESGCO 2014, pp 155–156

    Google Scholar 

  • Danoudis M, Iansek R (2014) Gait in Huntington’s disease and the stride length-cadence relationship. BMC Neurol 14:161

    Article  PubMed  PubMed Central  Google Scholar 

  • Darbin O, Adams E, Martino A, Naritoku L, Dees D et al (2013) Non-linear dynamics in parkinsonism. Front Neurol 4:211

    Article  PubMed  PubMed Central  Google Scholar 

  • DeKosky ST, Marek K (2003) Looking backward to move forward: early detection of neurodegenerative disorders. Science 302(5646):830–834

    Article  CAS  PubMed  Google Scholar 

  • Devous MD Sr (2002) Functional brain imaging in the dementias: role in early detection, differential diagnosis, and longitudinal studies. Eur J Nucl Med Mol Imaging 29:1685–1696

    Article  PubMed  Google Scholar 

  • Dick OE, Nozdrachev AD (2015) Nonlinear dynamics of involuntary shaking of the human hand under motor dysfunction. Hum Physiol 41:156

    Article  Google Scholar 

  • Dick OE, Nozdrachev AD (2016) Features of parkinsonian and essential tremor of the human Hand1. Hum Physiol 42:271–278

    Article  Google Scholar 

  • Du G, Ning X (2008) Multifractal properties of Chinese stock market in Shanghai. Physica A 387:261–269

    Article  Google Scholar 

  • Dutta S, Ghosh D, Samanta S (2016) Non linear approach to study the dynamics of neurodegenerative diseases by multifractal Detrended cross-correlation analysis—a quantitative assessment on gait disease. Physica A 448:181–195

    Article  Google Scholar 

  • Eggleston KS, Olin BD, Fisher RS (2014) Ictal tachycardia: the head-heart connection. Seizure 23:496–505

    Article  PubMed  Google Scholar 

  • Eke A, Herman P, Kocsis L, Kozak LR (2002) Fractal characterization of complexity in temporal physiological signals. Physiol Meas 23:R1–R38

    Article  CAS  PubMed  Google Scholar 

  • Elgandelwar SM, Bairagi VK (2016) Analysis of EEG signals for diagnosis of Alzheimer disease. Int J Sci Eng Res 7:529–532

    Google Scholar 

  • Enescu B, Ito K, Struzik ZR (2004) Wavelet-based multifractal analysis of real and stimulated time series of earthquakes. Annuals of Disaster Prevention Research Institute, Kyoto University, No. 47B

    Google Scholar 

  • Farina D, Negro F (2012) Accessing the neural drive to muscle and translation to neurorehabilitation technologies. IEEE Rev Biomed Eng 5:3–14

    Article  PubMed  Google Scholar 

  • Farina D, Merletti R, Enoka RM (2004) The extraction of neural strategies from the surface EMG. J Appl Physiol 96:1486–1495

    Article  PubMed  Google Scholar 

  • Fattah SA, Iqbal MA, Jumana MA, Sayeed Ud Doulah ABM (2012) Identifying the motor neuron disease in EMG signal using time and frequency domain features with comparison. Signal Image Process Int J 3:99–113

    Article  Google Scholar 

  • Fattah SA, Sayeed Ud Doulah ABM, Iqbal MA, Shahnaz C, Zhu W-P, et al (2013) Identification of motor neuron disease using wavelet domain features extracted from EMG signal. In: IEEE international symposium on circuits and systems (ISCAS 2013), 19–23 May 2013. Beijing, China

    Google Scholar 

  • Faure P, Korn H (2001) Is there chaos in the brain? I. Concepts of nonlinear dynamics and methods of investigation. Comptes Rendus de l’Académie des Sciences III 324:773–793

    CAS  Google Scholar 

  • Faust O, Acharya UR, Min L, Sputh B (2010) Automatic identification of epileptic and background EEG signals using frequency domain parameters. Int J Neural Syst 20:159–176

    Article  PubMed  Google Scholar 

  • Faust O, Acharya UR, Adeli H, Adeli A (2015) Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis. Seizure 26:56–64

    Article  PubMed  Google Scholar 

  • Feder J (1988) Fractals. Plenum Press, New York

    Book  Google Scholar 

  • Fergus P, Hussain A, David Hignett D, Al-Jumeily KA-A, Hamdan H (2016) A machine learning system for automated whole-brain seizure detection. Appl Comput Inform 12:70–89

    Article  Google Scholar 

  • Fisher R, van Emde Boas W, Blume W, Elger C, Genton P et al (2005) Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE). Epilepsia 46:470–472

    Article  PubMed  Google Scholar 

  • Flynn AC, Jelinek HF, Smith MC (2005) Heart rate variability analysis: a useful assessment tool for diabetes associated cardiac dysfunction in rural and remote areas. Aust J Rural Health 13:77–82

    Article  PubMed  Google Scholar 

  • Forsgren L, Almay BGL, Holmgren G, Wall S (1983) Epidemiology of motor neuron disease in Northern Sweden. Acta Neurol Scand 68:20–29

    Article  CAS  PubMed  Google Scholar 

  • Fu K, Qu JF, Chai Y, Zou T (2015) Hilbert marginal spectrum analysis for automatic seizure detection in EEG signals. Biomed Signal Process Control 18:179–185

    Article  Google Scholar 

  • Fujiwara K, Miyajima M, Yamakawa T, Abe E, Suzuki Y et al (2016) Epileptic seizure prediction based on multivariate statistical process control of heart rate variability features. IEEE Trans Biomed Eng 63:1321–1332

    Article  PubMed  Google Scholar 

  • Fukuda O, Kim J, Nakai I, Ichikawa Y (2011) EMG control of a pneumatic 5-fingered hand using a Petri net. Artificial Life and Robotics 16(1):90–93

    Article  Google Scholar 

  • Gabor AJ, Leach RR, Dowla FU (1996) Automated seizure detection using a self-organizing neural network. Electroencephalogr Clin Neurophysiol 99:257–266

    Article  CAS  PubMed  Google Scholar 

  • Gao J, Sultan H, Hu J, Tung WW (2010) Denoising nonlinear time series by adaptive filtering and wavelet shrinkage: a comparison. IEEE Signal Process Lett 17:237–240

    Article  Google Scholar 

  • Garrett D, Peterson D, Anderson C, Thaut M (2003) Comparison of linear, nonlinear, and feature selection methods for EEG signal classification. IEEE Trans Neural Syst Rehabil Eng 11:141–144

    Article  PubMed  Google Scholar 

  • Gato S, Jayasuriya N, Roberts P (2007) Temperature and rainfall thresholds for base use urban water demand modelling. J Hydrol 337(3–4):364–376

    Article  Google Scholar 

  • Ge E, Leung Y (2013) Detection of crossover time scales in multifractal detrended fluctuation analysis. J Geogr Syst 15:115–147

    Article  Google Scholar 

  • Ghosh D, Deb A, Dutta K, Sarkar R, Dutta I et al (2004) Multifractality and multifractal specific heat in fragmentation process in 24Mg-AgBr interaction at 4.5 A GeV. Indian J Phys 78:359–362

    Google Scholar 

  • Ghosh DC, Chakraborty M, Das T (2013) Fractal approach to identify quantitatively Intracardiac atrial fibrillation from ECG signals. Int J Eng Res Appl 3:129–134

    Google Scholar 

  • Ghosh D, Dutta S, Chakraborty S, Samanta S (2017) Chaos based quantitative electro-diagnostic marker for diagnosis of myopathy, neuropathy and motor neuron disease. J Neurol Neurosci 8(S4):226

    Google Scholar 

  • Gierałtowski J, Żebrowski JJ, Baranowski R (2012) Multiscale multifractal analysis of heart rate variability recordings with a large number of occurrences of arrhythmia. Phys Rev E 85(2)

    Google Scholar 

  • Gigola S, Ortiz F, D’Attellis CE, Silva W, Kochen S (2004) Prediction of epileptic seizures using accumulated energy in a multiresolution framework. J Neurosci Methods 138:107–111

    Article  CAS  PubMed  Google Scholar 

  • Goldberger AL (1996) Non-linear dynamics for clinicians: chaos theory, fractals, and complexity at the bedside. Lancet 11:1312–1314

    Article  Google Scholar 

  • Goldberger AL, Rigney DR, West BJ (1990) Chaos and fractals in human physiology. Sci Am 262:42–49

    Article  CAS  PubMed  Google Scholar 

  • Goldberger AL, Amaral LAN, Hausdorff JM, Ivanov PC, Peng CK et al (2002) Fractal dynamics in physiology: alterations with disease and aging. Proc Natl Acad Sci U S A 99:2466–2472

    Article  PubMed  PubMed Central  Google Scholar 

  • Golińska AK (2012) Detrended fluctuation analysis (DFA) in biomedical signal processing: selected examples. Stud Logic Grammar Rhetor 29(42):107–115

    Google Scholar 

  • Gospodinova E (2014) Graphical methods for nonlinear analysis of ECG signals. Int J Adv Res Comput Sci Softw Eng 4:40–44

    Google Scholar 

  • Gotman J (1982) Automatic recognition of epileptic seizures in the EEG. Electroencephalogr Clin Neurophoysiol 54:530–540

    Article  CAS  Google Scholar 

  • Grassberger P, Procaccia I (1983) Characterization of strange attractors. Phys Rev Lett 50:346–349

    Article  Google Scholar 

  • Gu G-F, Zhou W-X (2010) Detrending moving average algorithm for multifractals. Phys Rev E 82:11136

    Article  CAS  Google Scholar 

  • Gupta V, Suryanarayanan S, Reddy NP (1997) Fractal analysis of surface EMG signals from the biceps. Int J Med Inform 45:185–192

    Article  CAS  PubMed  Google Scholar 

  • Gutiérrez Gutiérrez G, López CB, Navacerrada F, Martínez AM (2012) Use of electromyography in the diagnosis of inflammatory myopathies. ReumatologÃa ClÃnica (English Edition) 8(4):195–200

    Article  Google Scholar 

  • Halsey TC, Jensen MH, Kadanoff LP, Procaccia I, Shraiman BI (1986) Fractal measures and their singularities: the characterization of strange sets. Phys Rev A 33:1141–1151

    Article  CAS  Google Scholar 

  • Hamou A, Simmons A, Bauer M, Lewden B, Wahlund LO et al (2011) Cluster analysis of MR imaging in Alzheimer‘s disease using decision tree refinement. Int J Artif Intell 6:90–99

    Google Scholar 

  • Han C-X, Wang J, Yi G-S, Che Y-Q (2013) Investigation of EEG abnormalities in the early stage of Parkinson’s disease. Cogn Neurodyn 7:351–359

    Article  PubMed  PubMed Central  Google Scholar 

  • Hassan AR, Siuly S, Zhang Y (2016) Epileptic seizure detection in EEG signals using tunable-q factor wavelet transform and bootstrap aggregating. Comput Methods Prog Biomed 137:247–259

    Article  Google Scholar 

  • Hata M, Kazui H, Tanaka T, Ishii R, Canuet L et al (2015) Functional connectivity assessed by resting state EEG correlates with cognitive decline of Alzheimer’s disease – an eLORETA study. Clin Neurophysiol 127:1269–1278

    Article  PubMed  Google Scholar 

  • Hausdorf F (1919) Dimension und ausseres Mass. Math Ann 79:157–179

    Article  Google Scholar 

  • Hausdorff JM (2005) Gait variability: methods, modeling and meaning. J Neuroeng Rehabil 2:19–27

    Article  PubMed  PubMed Central  Google Scholar 

  • Hausdorff JM (2007) Gait dynamics, fractals and falls: finding meaning in the stride-to-stride fluctuations of human walking. Hum Mov Sci 26:555–589

    Article  PubMed  PubMed Central  Google Scholar 

  • Hausdorff JM (2009) Gait dynamics in parkinson’s disease: common and distinct behavior among stride length, gait variability, and fractal-like scaling. Chaos 19:026113

    Article  PubMed  PubMed Central  Google Scholar 

  • Hausdorff JM, Lertratanakul A, Cudkowicz ME, Peterson AL, Kaliton D et al (1985) Dynamic markers of altered gait rhythm in amyotrophic lateral sclerosis. J Appl Physiol 88:2045–2053

    Article  Google Scholar 

  • Hausdorff JM, Mitchell SL, Firtion R, Peng CK, Cudkowicz ME et al (1997) Altered fractal dynamics of gait: reduced stride-interval correlations with aging and Huntington’s disease. J Appl Physiol 82:262–269

    Article  CAS  PubMed  Google Scholar 

  • He LY, Chen SP (2011a) Nonlinear bivariate dependency between price and volume relationships in agricultural commodity futures markets: a perspective from multifractal detrended cross-correlation analysis. Physica A 390:297–308

    Article  Google Scholar 

  • He LY, Chen SP (2011b) Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets. Chaos Solitons Fractals 44:355–361

    Article  Google Scholar 

  • Helkala E, Laulumaa V, Soikkeli R, Partanen J, Soininen H et al (1991) Slow-wave activity in the spectral analysis of the electroencephalogram is associated with cortical dysfunctions in patients with Alzheimer’s disease. Behav Neurosci 105:409–415

    Article  CAS  PubMed  Google Scholar 

  • Henderson G, Ifeachor E, Hudson N, Goh C, Outram N et al (2006) Development and assessment of methods for detecting dementia using the human electroencephalogram. IEEE Trans Biomed Eng 53:1557–1568

    Article  PubMed  Google Scholar 

  • Higuchi T (1988) Approach to an irregular time series on the basis of the fractal theory. Physica D 31:277–283

    Article  Google Scholar 

  • Hirata Y, Matsuda H, Nemoto K (2005) Voxel-based morphometry to discriminate early Alzheimer’s disease from controls. Neurosci Lett 382:269–274

    Article  CAS  PubMed  Google Scholar 

  • Holschneider M (1995) Wavelets : an analysis tool. Clarendon Press/Oxford University Press, Oxford/New York

    Google Scholar 

  • Hoon MJLD, Van der Hagen THJJ, Schoonewelle H, van Dam H (1996) Why Yule-Walker should not be used for autoregressive modeling. Ann Nucl Energy 23:1219–1228

    Article  Google Scholar 

  • Horvatic D, Stanley HE, Podobnik B (2011) Detrended cross-correlation analysis for non-stationary time series with periodic trends. Europhys Lett 94:18007

    Article  CAS  Google Scholar 

  • Hove MJ, Suzuki K, Uchitomi H, Orimo S, Miyake Y (2012) Interactive rhythmic auditory stimulation reinstates natural 1/f timing in gait of parkinson’s patients. PLoS One 7:e32600

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hu X, Wang Z-z, Ren X-m (2005) Classification of surface EMG signal with fractal dimension. J Zhejiang Univ Sci 6B(8):844–848

    Article  Google Scholar 

  • Hug F (2011) Can muscle coordination be precisely studied by surface electromyography. J Electromyogr Kinesiol 21:1–12

    Article  PubMed  Google Scholar 

  • Huh K-H, Baik J-S, Yi W-J, Heo M-S, Lee S-S et al (2011) Fractal analysis of mandibular trabecular bone: optimal tile sizes for the tile counting method. Imaging Sci Dent 41:71–78

    Article  PubMed  PubMed Central  Google Scholar 

  • Humeau A, Chapeau–Blondeau F, Rousseau D, Rousseau P, Trzepizur W et al (2008) Multifractality, sample entropy, and wavelet analyses for age-related changes in the peripheral cardiovascular system: preliminary results. Med Phys 35:717–723

    Article  PubMed  Google Scholar 

  • Hurst H (1951) Long term storage capacity of reservoirs. Trans Am Soc Civil Eng 116:770–799

    Google Scholar 

  • Hyman S, Chisholm D, Kessler R, Patel V, Whiteford HA (2006) Mental disorders in disease control priorities in developing countries. In: Jamison DT, Breman JG, Measham AR, Alleyne G, Claeson M, Evans DB (eds), Disease control priorities in developing countries, pp 605–625

    Google Scholar 

  • Iasemidis LD, Shiau DS, Chaovalitwongse W, Sackellares JC, Pardolas PM et al (2003) Adaptive epileptic seizure prediction system. IEEE Trans Biomed Eng 50:616–627

    Article  PubMed  Google Scholar 

  • Ihlen EAF (2012) Introduction to multifractal detrended fluctuation analysis in Matlab. Front Physiol 3:Article141

    Article  Google Scholar 

  • Inbar GF, Paiss O, Allin J, Kranz H (1986) Monitoring surface EMG spectral changes by the zero crossing rate. Med Biol Eng Comput 24:10–18

    Article  CAS  PubMed  Google Scholar 

  • Ivanov PC, Amaral LA, Goldberger AL, Halvin S, Rosenblum MG et al (1999) Multifractality in human heartbeat dynamics. Nature 399:461–465

    Article  CAS  PubMed  Google Scholar 

  • Ivanov P, Amaral LA, Goldberger S, Halvin M, Rosenblum H et al (2001) From 1/f noise to multifractal cascades in heartbeat dynamics. Chaos 11:641–652

    Article  PubMed  Google Scholar 

  • Ivanov P, Chen Z, Hu K, Stanley HE (2004) Multiscale aspects of cardiac control. Physica A 344:685–704

    Article  Google Scholar 

  • Ivanova K, Ausloos M, Clothiaux EE, Ackerman TP (2000) Break-up of stratus cloud structure predicted from non-Brownian motion liquid water and brightness temperature fluctuations. Europhys Lett 52:40

    Article  CAS  Google Scholar 

  • Izhikevich EM (2007) Dynamical systems in neuroscience. The geometry of excitability and bursting. The MIT Press, Cambridge, MA, p 441

    Book  Google Scholar 

  • Jankovic J (2008) Parkinson’s disease: clinical features and diagnosis. J Neurol Neurosurg Psychiatry 79:368–376

    Article  CAS  PubMed  Google Scholar 

  • Jankovic J, Kapadia AS (2001) Functional decline in parkinson disease. Arch Neurol 58:1611–1615

    Article  CAS  PubMed  Google Scholar 

  • Joseph P, Acharya UR, Poo CK, Chee J, Min LC et al (2004) Effect of reflexological stimulation on heart rate variability. ITBM-RBM 25:40–45

    Article  Google Scholar 

  • Joshi S, Shenoy PD, Vibhudendra Simha GG, Venugopal KR, Patnaik LM (2010) Classification of neuro degenerative disorders based on major risk factors employing machine learning techniques. IACSIT Int J Eng Technol 2:350–355

    Article  Google Scholar 

  • Jovic A, Bogunovic N (2010) Classification of biological signals based on nonlinear features. In: Melecon 2010–2010 15th IEEE Mediterranean Electrotechnical conference, pp 1340–1345

    Google Scholar 

  • Jun WC, Oh G, Kim S (2006) Understanding volatility correlation behavior with a magnitude cross-correlation function. Phys Rev E 73:066128

    Article  CAS  Google Scholar 

  • Kahn Y, Gotman J (2003) Wavelet based automatic seizure detection in intracerebral electroencephalogram. Clin Neurophysiol 114:898–908

    Article  Google Scholar 

  • Kamath C (2012) Entropy-based algorithm to detect life threatening cardiac arrhythmias using raw electrocardiogram signals. Middle East J Sci Res 12:1403–1412

    Google Scholar 

  • Kandel ER, Squire LR (2000) Neuroscience: breaking down scientific barriers to the study of brain and mind. Science 290:1113–1120

    Article  CAS  PubMed  Google Scholar 

  • Kantelhardt JW, Berkovits R, Havlin S, Bunde A (1999) Are the phases in the Anderson model long-range correlated? Physica A 266:461–464

    Article  Google Scholar 

  • Kantelhardt JW, Zschiegner SA, Koscielny-Bunde E, Bunde A, Havlin S et al (2002) Multifractal detrended fluctuation analysis of nonstationary time series. Physica A 316:87–114

    Article  Google Scholar 

  • Kantelhardt JW, Rybski D, Zschiegner SA, Braun P, Koscielny-Bunde E et al (2003) Multifractality of river runoff and precipitation: comparison of fluctuation analysis and wavelet methods. Physica A 330:240–245

    Article  Google Scholar 

  • Kasi PK (2009) Characterization of motor unit discharge rate in patients with Amytrophic Lateral Sclerosis (ALS). Worcester Polytechnic Institute, May 2009

    Google Scholar 

  • Kartz M (1988) Fractals and the analysis of waveforms. Comput Biol Med 18:145–156

    Article  Google Scholar 

  • Kehri V, Ingle R, Awale R, Oimbe S (2017) Techniques of EMG signal analysis and classification of neuromuscular diseases. In: Iyer B, Nalbalwar S, Pawade R (eds) ICCASP/ICMMD-2016. Advances in intelligent systems research. vol 137, pp 485–491. © 2017- The authors. Published by Atlantis Press

    Google Scholar 

  • Kim HS, Eykholt R, Salas JD (1999) Nonlinear dynamics, delay times and embedding windows. Physica D 127:48–60

    Article  Google Scholar 

  • Kim SH, Faloutos C, Yang HJ (2013) Coercively adjusted auto regression model for forecasting in epilepsy EEG. Hindawi Publishing Corporation, Computational and mathematical methods in medicine, 2013, Article ID 545613

    Google Scholar 

  • Kiran PU, Abhiram N, Taran S, Bajaj V (2018) TQWT based features for classification of ALS and healthy EMG signals. Am J Comput Sci Inf Technol 6:19

    Google Scholar 

  • Kirchner M, Schubert P, Liebherr M, Haas CT (2014) Detrended fluctuation analysis and adaptive fractal analysis of stride time data in Parkinson’s disease: stitching together short gait trials. PLoS One 9:e85787

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Klöppel S, Stonnington CM, Chu C, Draganski B, Scahill RI et al (2008) Automatic classification of MR scans in Alzheimer’s disease. Brain 131:681–689

    Article  PubMed  Google Scholar 

  • Korn H, Faure P (2003) Is there chaos in the brain? II. Experimental evidence and related models. C R Biol 326:787–840

    Article  PubMed  Google Scholar 

  • Koscielny-Bunde E, Bunde A, Havlin S, Roman HE, Goldreich Y et al (1998) Indication of a universal persistence law governing atmospheric variability. Phys Rev Lett 81:729

    Article  CAS  Google Scholar 

  • Krenz G, Linehan J, Dawson C (1992) A fractal continuum model of the pulmonary arterial tree. J Appl Physiol 72:2225–2237

    Article  CAS  PubMed  Google Scholar 

  • Krishna PM, Gadre VM, Desai UB (2003) Multifractals: from modeling to control of broadband network traffic. In: Rangarajan G, Ding M (eds) Processes with long-range correlations, Lecture notes in physics, vol 621. Springer, Berlin/Heidelberg, pp 373–392

    Chapter  Google Scholar 

  • Kumar SP, Sriraam N, Benakop PG, Jinaga BC (2010) Entropies based detection of epileptic seizures with artificial neural network classifiers. Expert Syst Appl 37:3284–3291

    Article  Google Scholar 

  • Lake DE, Richman JS, Griffin MP, Moorman JR (2002) Sample entropy analysis of neonatal heart rate variability. Am J Physiol Regul Integr Comp Physiol 283:R789–R797

    Article  CAS  PubMed  Google Scholar 

  • Lambert EH (1969) Electromyography in amyotrophic lateral sclerosis. In: Norris FH, Kurland LT (eds) Motor neuron diseases: research in amyotrophic lateral sclerosis and related disorders. Grune and Stratton, New York, pp 135–153

    Google Scholar 

  • Lambert EH, Mulder DW (1957) Electromyographic studies in amyotrophic lateral sclerosis. Mayo Clin Proc 32:441–446

    CAS  Google Scholar 

  • Lamberts RJ, Thijs RD, Laffan A, Langan Y, Sander JW (2012) Sudden unexpected death in epilepsy: people with nocturnal seizures may be at highest risk. Epilepsia 53:253–257

    Article  PubMed  Google Scholar 

  • Lehnertz K (2008) Epilepsy and nonlinear dynamics. J Biol Phys 34:253–266

    Article  PubMed  PubMed Central  Google Scholar 

  • Leigh PN, Al-Chalabi A (2000) Recent advances in amyotrophic lateral sclerosis. Curr Opin Neurol 13:397–405

    Article  PubMed  Google Scholar 

  • Li X (2002) EEG analysis with epileptic seizures using wavelet transform. Department of Automation and Computer-Aided Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, 28 Nov 2002

    Google Scholar 

  • Li X, Ouyang G (2006) Nonlinear similarity analysis for epileptic seizures prediction. Nonlinear Anal Theory Methods Appl 64:1666–1678

    Article  Google Scholar 

  • Li X, Yao X (2005) Application of fuzzy similarity to prediction of epileptic seizures using EEG signals. In: Proceedings of the 2nd international conference on Fuzzy Systems and Knowledge Discovery (FSKD ’05), 3613, pp 645–652

    Chapter  Google Scholar 

  • Li S, Shi F, Pu F, Li X, Jiang T et al (2007) Hippocampal shape analysis of Alzheimer disease based on machine learning methods. Am J Neuroradiol 28:1339–1345

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li S, Liu G, Lin Z (2009) Comparisons of wavelet packet, lifting wavelet and stationary wavelet transform for denoising ECG. In: 2nd IEEE international conference on Computer Science and Information Technology, ICCSIT, pp 491–494

    Google Scholar 

  • Li Y, Wei HL, Billings SA (2011) Identification of time-varying systems using multi-wavelet basis functions. IEEE Trans Control Syst Technol 19:656–663

    Article  CAS  Google Scholar 

  • Li Y, Luo ML, Li K (2016) A multi-wavelet-based time-varying model identification approach for time-frequency analysis of EEG signals. Neurocomputing 193:106–114

    Article  Google Scholar 

  • Libenson M (2009) Practical Approach to Electroencephalography. Saunders

    Google Scholar 

  • Lim J, Sanghera MK, Darbin O, Stewart RM, Jankovic J et al (2010) Nonlinear temporal organization of neuronal discharge in the basal ganglia of Parkinson’s disease patients. Exp Neurol 224:542–544

    Article  PubMed  Google Scholar 

  • Liu Y, Gopikrishnan P, Cizeau P, Meyer M, Peng CK et al (1999) Statistical properties of the volatility of price fluctuations. Phys Rev E 60:1390

    Article  CAS  Google Scholar 

  • Liu D, Pang Z, Wang Z (2009) Epileptic seizure prediction by a system of particle filter associated with a neural network. EURASIP J Adv Signal Process 2009:638534

    Article  Google Scholar 

  • Lopes R, Betrouni N (2009) Fractal and multifractal analysis: a review. Med Image Anal 13:634–649

    Article  CAS  PubMed  Google Scholar 

  • Malamud BD, Turcotte DL (1999) Self-affine time series: measures of weak and strong persistence. J Statist Plann Inference 80:173–196

    Article  Google Scholar 

  • Malarvili M, Mesbah M (2009) Newborn seizure detection based on heart rate variability. IEEE Trans Biomed Eng 56:2594–2603

    Article  CAS  PubMed  Google Scholar 

  • Mallat S (2002) A wavelet tour of signal processing, 3rd edn. Amsterdam, Elsevier

    Google Scholar 

  • Mandelbrot B (1967) Hong long is the coast of Britain? Statistical self-similarity and fractional dimension. Science 156(3775):636–638

    Article  CAS  PubMed  Google Scholar 

  • Mandelbrot B (1977) Fractals: form, chance, and dimension. W. H. Freeman and Company, San Francisco, p 365

    Google Scholar 

  • Mandelbrot B (1985) Self-affine fractals and the fractal dimension. Phys Scr 32:257–260

    Article  Google Scholar 

  • Mandelbrot BB (1995) Negative dimensions and Holders, multifractals and their Holder spectra, and the role of lateral preasymptotics in science. J Fourier Anal Appl Kahane special issue 409–432

    Google Scholar 

  • Mantegna RN, Stanley HE (2000) An introduction to econophysics. Cambridge University Press, Cambridge

    Google Scholar 

  • Marri K, Swaminathan R (2015) Identification of onset of fatigue in biceps Brachii muscles using surface EMG and multifractal DMA Algorithm. Biomed Sci Instrum 51:107–114

    PubMed  Google Scholar 

  • Marri K, Swaminathan R (2016) Analysis of biceps Brachii muscles in dynamic contraction using sEMG signals and multifractal DMA algorithm. Int J Signal Process Syst 4:79–85

    Google Scholar 

  • Marri K, Jose J, Karthick PA, Ramakrishnan S (2014) Analysis of fatigue conditions in triceps brachii muscle using sEMG signals and spectral correlation density function. In: International conference on Informatics, Electronics and Vision (ICIEV), Dhaka, May 23–24, pp 1–4

    Google Scholar 

  • Marsden CD (1982) The mysterious motor function of the basal ganglia: the Robert Wartenberg lecture. Neurology 32:514–539

    Article  CAS  PubMed  Google Scholar 

  • Meier R, Dittrich H, Schulze-Bonhage A, Aertsen A (2008) Detecting epileptic seizures in long-term human EEG: a new approach to automatic online and real-time detection and classification of polymorphic seizure patterns. J Clin Neurophysiol 25:119–131

    Article  PubMed  Google Scholar 

  • Meigal AY, Rissanen SM, Tarvainen MP, Georgiadis SD, Karjalainen PA, Airaksinen O, Kankaanpää M (2012) Linear and nonlinear tremor acceleration characteristics in patients with Parkinson's disease. Physiol Meas 33(3):395–412

    Article  PubMed  Google Scholar 

  • Meigal AY, Rissanen SM, Tarvainen MP, Airaksinen O, Kankaanpaa M et al (2013) Non-linear EMG parameters for differential and early diagnostics of Parkinson’s disease. Front Neurol 4:135

    Article  PubMed  PubMed Central  Google Scholar 

  • Merletti R, Farina D (2008) Surface EMG processing: introduction to the special issue. Biomed Signal Process Control 3:115–117

    Article  Google Scholar 

  • Merrikh-Bayat F (2011) Time series analysis of parkinson’s disease, huntington’s disease and amyotrophic lateral sclerosis. Procedia Comput Sci 3:210–215

    Article  Google Scholar 

  • Mesin L, Cescon C, Gazzoni M, Merletti R, Rainoldi A (2009) A bidimensional index for the selective assessment of myoelectric manifestations of peripheral and central muscle fatigue. J Electromyogr Kinesiol 19:851–863

    Article  PubMed  Google Scholar 

  • Millan H, Kalauzi A, Cukic M, Biondi R (2010) Nonlinear dynamics of meteorological variables: Multifractality and chaotic invariants in daily records from Pastaza, Ecuador. Theor Appl Climatol 102:75–85

    Article  Google Scholar 

  • Minasyan GR, Chatten JB, Chatten MJ, Harner RN (2010) Patient-specific early seizure detection from scalp EEG. J Clin Neurophysiol 27:163–178

    Article  PubMed  PubMed Central  Google Scholar 

  • Minguez C, Winblad B (2010) Biomarkers for Alzheimer’s disease and other forms of dementia: clinical needs, limitations and future aspects. Exp Gerontol 45:5–14

    Article  CAS  Google Scholar 

  • Mobasser F, Eklund JM, Hashtrudi-Zaad K (2007) Estimation of elbow-induced wrist force with EMG signals using fast orthogonal search. IEEE Trans Biomed Eng 54:683–693

    Article  PubMed  Google Scholar 

  • Molina-Picó A, Cuesta-Frau D, Aboy M, Crespo C, Miró-Martínez P et al (2011) Comparative study of approximate entropy and sample entropy robustness to spikes. Artif Intell Med 53:97–106

    Article  PubMed  Google Scholar 

  • Monsifrot J, Carpentier EL, Aoustin Y (2004) Sequential decoding of intramuscular EMG signals via estimation of a Markov model. IEEE Trans Neural Syst Rehabil Eng 22:1030–1038

    Article  Google Scholar 

  • Morales CJ, Kolaczyk ED (2002) Wavelet-based multifractal analysis of human balance. Ann Biomed Eng 30:588–597

    Article  PubMed  Google Scholar 

  • Mormann F, Kreuz T, Andrzejak RG, Peter D, Lehnertz K et al (2003) Epileptic seizures are preceded by a decrease in synchronization. Epilepsy Res 53:173–185

    Article  PubMed  Google Scholar 

  • Mormann F, Thomas K, Christoph R, Andrzejak RG, Kraskov A et al (2005) On the predictability of epileptic seizures. Clin Neurophysiol 116:569–587

    Article  PubMed  Google Scholar 

  • Movahed MS, Jafari GR, Ghasemi F, Rahvar S, Tabar MRR (2006) Multifractal detrended fluctuation analysis of sunspot time series. J Stat Mech Theory Exp 2006(2):1–17

    Article  Google Scholar 

  • Muzy JF, Bacry E, Arneodo A (1991) Wavelets and multifractal formalism for singular signals: application to turbulence data. Phys Rev Lett 67:3515–3518

    Article  CAS  PubMed  Google Scholar 

  • Muzy JF, Bacry E, Arneodo A (1994) The multifractal formalism revisited with wavelets. Int J Bifurcation Chaos 4:245–302

    Article  Google Scholar 

  • Namazi H, Kulish VV (2015) Fractional diffusion based modelling and prediction of human brain response to external stimuli. Comput Math Methods Med 2015:148534

    PubMed  PubMed Central  Google Scholar 

  • Namazi H, Kulish VV (2016) Fractal based analysis of the influence of odorants on heart activity. Sci Rep 6:38555

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Namazi H, Kulish VV, Wong A (2015) Mathematical modelling and prediction of the effect of chemotherapy on cancer cells. Sci Rep 5:13583

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Namazi H, Kulish VV, Akrami A (2016a) The analysis of the influence of fractal structure of stimuli on fractal dynamics in fixational eye movements and EEG signal. Sci Rep 6:26639

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Namazi H, Kulish VV, Hussaini J, Delaviz A, Delaviz F et al (2016b) A signal processing based analysis and prediction of seizure onset in patients with epilepsy. Oncotarget 7:342–350

    PubMed  Google Scholar 

  • Nasehi S, Pourghassem H (2013) Patient-specific epileptic seizure onset detection algorithm based on spectral features and IPSONN classifier. In: International conference on Communication Systems and Network Technologies, pp 186–190, 2013

    Google Scholar 

  • Nathan DG, Fontanarosa PB, Wilson JD (2001) Opportunities for medical research in the 21st century. JAMA 285:533–534

    Article  CAS  PubMed  Google Scholar 

  • Ocak H (2009) Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy. Expert Syst Appl 36:2027–2036

    Article  Google Scholar 

  • Ossadnik SM, Buldyrev SV, Goldberger AL, Havlin S, Mantegna RN et al (1994) Correlation approach to identify coding regions in DNA sequences. Biophys J 67:64–70

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Oswiecimka P, Kwapien J, Drozdz S, Rak R (2005) Investigating multifractality of stock market fluctuations using wavelet and detrending fluctuation methods. Acta Phys Pol B 36:2447–2457

    CAS  Google Scholar 

  • Parker TS, Chua LO (1989) Practical numerical algorithms for chaotic systems. Springer, New York, pp 193–194

    Book  Google Scholar 

  • Parkinson I, Fazzalari N (1994) Cancellous bone structure analysis using image analysis. Australas Phys Eng Sci Med 17:64–70

    CAS  PubMed  Google Scholar 

  • Patrzalek E (2006) Fractals: Useful Beauty General Introduction to Fractal Geometry. In: General Introduction to Fractal Geometry, pp 1–7, Stan Ackermans Institute, IPO Centre for User- System Interaction, Eindhoven University of Technology

    Google Scholar 

  • Pavei J, Walz R, Marques JLB (2014) Study of biomarkers for prediction of epileptic seizures using ECG. In: Proceedings CBEB 2014 XXIV Brazilian conference on Biomedical Engineering—CBEB 2014 (Uberlândia), pp 1677–1680

    Google Scholar 

  • Pavei J, Heinzen RG, Novakova B, Walz R, Serra AJ et al (2017) Early seizure detection based on cardiac autonomic regulation dynamics. Front Physiol 8:765

    Article  PubMed  PubMed Central  Google Scholar 

  • Peitgen HO, Jurgens H, Saupe D (1992) Chaos and Fractals, Springer, New York (Appendix B)

    Book  Google Scholar 

  • Peng C-K, Buldyrev SV, Havlin S, Simons M, Stanley HE et al (1994) Mosaic organization of DNA nucleotides. Phys Rev E 49:1685–1689

    Article  CAS  Google Scholar 

  • Peng C-K, Havlin S, Stanley HE, Goldberger AL (1995) Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos 5:82–87

    Article  CAS  PubMed  Google Scholar 

  • Peng CK, Mietus JE, Liu Y, Lee C, Hausdorff JM et al (2002) Quantifying fractal dynamics of human respiration: age and gender effects. Ann Biomed Eng 30:683–692

    Article  CAS  PubMed  Google Scholar 

  • Penney JB, Young AB (1993) Huntington’s disease. In: Jankovic J, Tolosa E (eds) Parkinson’s disease and movement disorders. Williams & Wilkins, Baltimore, pp 205–216

    Google Scholar 

  • Petersen RC, Roberts RO, Knopman DS, Boeve BF, Geda YE et al (2009) Mild cognitive impairment: ten years later. Arch Neurol 66:1447

    Article  PubMed  PubMed Central  Google Scholar 

  • Petrosian A, Prokhorov DV, Lajara-Nanson W, Schiffer RB (2001) Recurrent neural network-based approach for early recognition of Alzheimer’s disease in EEG. Clin Neurophysiol 112:1378–1387

    Article  CAS  PubMed  Google Scholar 

  • Pezard L, Jech R, Ruzicka E (2001) Investigation of non-linear properties of multi- channel EEG in the early stages of Parkinson’s disease. Clin Neurophysiol 112:38–45

    Article  CAS  PubMed  Google Scholar 

  • Phinyomark A, Limsakul C, Phukpattaranont P (2009) A comparative study of wavelet denoising for multifunction myoelectric control. In: International conference on Computer and Automation Engineering, ICCAE, pp 21–25

    Google Scholar 

  • Pikkujamsa SM, Makikallio TM, Sourannder LB, Raiha IJ, Puukka P et al (1999) Cardiac interbeat interval dynamics from childhood to senescence. Comparison of conventional and new measures based on fractals and chaos theory. Circulation 100:393–399

    Article  CAS  PubMed  Google Scholar 

  • Pikkujamsa SM, Makikallio TH, Airaksinen KEJ, Huikuri HV (2001) Determinants and interindividual variation of R-R interval dynamics in healthy middle aged subjects. Am J Phys Heart Circ Phys 280:H1400–H1406

    CAS  Google Scholar 

  • Pincus SM (1991) Approximate entropy as a measure of system complexity. In: Proc Natl Acad Sci USA, vol 88, pp 2297–2301

    Google Scholar 

  • Pincus SM (1995) Approximate entropy ApEn as a complexity measure. Chaos 5:110–117

    Article  PubMed  Google Scholar 

  • Podobnik B, Stanley HE (2008) Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series. Phys Rev Lett 100:084102

    Article  CAS  PubMed  Google Scholar 

  • Podobnik B, Grosse I, Horvati D, Ilic S, Ivanov PC et al (2009a) Quantifying cross-correlations using local and global detrending approaches. Eur Phys J B 71:243–250

    Article  CAS  Google Scholar 

  • Podobnik B, Horvatic D, Petersen AM, Stanley HE (2009b) Cross-correlations between volume change and price change. Proc Natl Acad Sci USA 106:22079–22084

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Podobnik B, Jiang Z-Q, Zhou W-X, Stanley HE (2011) Statistical tests for power-law cross-correlated processes. Phys Rev E 84:066118

    Article  CAS  Google Scholar 

  • Polat K, Güne S (2007) Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform. Appl Math Comput 187:1017–1026

    Google Scholar 

  • Ponnusamy A, Marques JL, Reuber M (2011) Heart rate variability measures as biomarkers in patients with psychogenic nonepileptic seizures: potential and limitations. Epilepsy Behav 22:685–691

    Article  PubMed  Google Scholar 

  • Ponnusamy A, Marques JL, Reuber M (2012) Comparison of heart rate variability parameters during complex partial seizures and psychogenic nonepileptic seizures. Epilepsia 53:1314–1321

    Article  PubMed  Google Scholar 

  • Poornachandra S (2008) Wavelet-based denoising using subband dependent threshold for ECG signals. Digital Signal Process 18:49–55

    Article  Google Scholar 

  • Prince M, Bryce R, Albanese E, Wimo A, Ribeiro W et al (2013) The global prevalence of dementia: a systematic review and meta analysis. Alzheimers Dement 9:63–75

    Article  PubMed  Google Scholar 

  • Quintero-Rincon A, Pereyra M, Giano CD, Batatia H, Risk M (2016) A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals. J Phys Conf Ser 705:012032

    Article  Google Scholar 

  • Quiroga RQ, Garcia H (2003) Single-trial event-related potentials with wavelet denoising. Clin Neurophysiol 114:376–390

    Article  Google Scholar 

  • Rabbi AF, Aarabi A, Fazel-Rezai R (2010) Fuzzy rule-based seizure prediction based on correlation dimension changes in intracranial EEG. In: Proceedings of the IEEE Engineering in Medicine and Biology Society conference, pp 3301–3304

    Google Scholar 

  • Reaz MBI, Hussain MS, Mohd-Yasin F (2006) Techniques of EMG signal analysis: detection, processing, classification and applications. Biological Procedures Online 8:11–35

    Article  Google Scholar 

  • Rhaman M, Karim AHM, Hasan M, Sultana J (2013) Successive RR interval analysis of PVC with sinus rhythm using fractal dimension, Poincare plot and sample entropy method. Int J Image Graphics Signal Process 2:17–24

    Article  Google Scholar 

  • Richman JS, Moorman JR (2000) Physiological time-series analysis using approximate entropy and sample entropy. Am J Phys Heart Circ Phys 278:H2039–H2049

    CAS  Google Scholar 

  • Rodrıguez-Bermudez G, Garcıa-Laencina PJ (2015) Analysis of EEG signals using nonlinear dynamics and chaos: a review. Appl Math Inf Sci 9:2309–2321

    Google Scholar 

  • Rogowski Z, Gath I, Bental E (1981) On the prediction of epileptic seizures. Biol Cybern 42:9–15

    Article  CAS  PubMed  Google Scholar 

  • Ronghua T, Chizhong H, Siyu F, Suming Z, Jinxiang W et al (2001) Correlation analysis of the cognitive function and changes of BEAM and CT scan in patients with Alzheimer’s disease. J Neurol Disord Stroke 8:266–269

    Google Scholar 

  • Ruonala V, Meigal A, Rissanen SM, Airaksinen O, Kankaanpää M et al (2014) EMG signal morphology and kinematic parameters in essential tremor and Parkinson’s disease patients. J Electromyogr Kinesiol 24:300–306

    Article  CAS  PubMed  Google Scholar 

  • Saab ME, Gotman J (2005) A system to detect the onset of epileptic seizures in scalp EEG. Clin Neurophysiol 116:427–442

    Article  CAS  PubMed  Google Scholar 

  • Salant Y, Gath I, Henriksen O (1998) Prediction of epileptic seizures from two-channel EEG. Med Biol Eng Comput 36:549–556

    Article  CAS  PubMed  Google Scholar 

  • Samiee K, Kiranyaz S, Gabbouj M, Saramäki T (2015) Long-term epileptic EEG classification via 2D mapping and textural features. Expert Syst Appl 42:7175–7185

    Article  Google Scholar 

  • Sanei S, Chambers JA (2007) EEG signal processing. Wiley, New York

    Book  Google Scholar 

  • Sarkar M, Leong TY (2003) Characterization of medical time series using fuzzy similarity-based fractal dimensions. Artif Intell Med 27:201–222

    Article  PubMed  Google Scholar 

  • Schaafsma JD, Giladi N, Balash Y, Bartels AL, Gurevich T et al (2003) Gait dynamics in parkinson’s disease: relationship to parkinsonian features, falls and response to levodopa. J Neurol Sci 212:47–53

    Article  PubMed  Google Scholar 

  • Schellenberg R, Schwarz A (1993) EEG- and EP-mapping--possible indicators for disturbed information processing in schizophrenia? Prog Neuro-Psychopharmacol Biol Psychiatry 17:595–607

    Article  CAS  Google Scholar 

  • Schiff SJ, Jerger K, Duong DH, Chang T, Spano ML, Ditto WL (1994) Controlling chaos in the brain. Nature 370(6491):615–620

    Article  CAS  PubMed  Google Scholar 

  • Sezgin N (2012) Analysis of EMG signals in aggressive and normal activities by using higher-order spectra. Sci World J 2012:478952

    Article  Google Scholar 

  • Shen CP, Chen CC, Hsieh SL, Chen WH, Chen JM et al (2013) High-performance seizure detection system using a wavelet-approximate entropy-fSVM cascade with clinical validation. Clin EEG Neurosci 44:247–256

    Article  PubMed  Google Scholar 

  • Shen D, Cul L, Cul B, Fang J, Li D et al (2015) A systematic review and meta-analysis of the functional MRI investigation of motor neuron disease. Front Neurol 6:246

    Article  PubMed  PubMed Central  Google Scholar 

  • Sheng H, Chen YQ (2011) Multifractional property analysis of human sleep EEG signals. In: Proceedings of the ASME 2011 International Design Engineering Technical Conferences & Computers and Information in Engineering conference, August 28–31, 2011, Washington, DC, USA

    Google Scholar 

  • Shoeb A, Guttag J (2010) Application of machine learning to epileptic seizure detection. In: Proceedings of the 27th international conference on Machine Learning, Haifa, Israel, 2010

    Google Scholar 

  • Sian J, Gerlach M, Youdim MBH, Riederer P (1999) Parkinson’s disease: a major hypokinetic basal ganglia disorder. J Neural Transm 106:443–476

    Article  CAS  PubMed  Google Scholar 

  • Silchenko A, Hu CK (2001) Multifractal characterization of stochastic resonance. Phys Rev E 63:041105

    Article  CAS  Google Scholar 

  • Simjanoska M, Gjoreski M, Bogdanova A, Koteska B, Gams M, et al (2018) ECG-derived blood pressure classification using complexity analysis-based machine learning. In: Proceedings of the 11th international joint conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) – 5, HEALTHINF, pp 282–292

    Google Scholar 

  • Singh M, Singh M, Paramjeet (2013) Neuro-degenerative disease diagnosis using human gait: a review. IJITKMI 7:16–20

    Google Scholar 

  • Siuly S, Li Y (2014) A novel statistical framework for multiclass EEG signal classification. Eng Appl Artif Intell 34:154–167

    Article  Google Scholar 

  • Siuly S, Zhang Y (2016) Medical big data: neurological diseases diagnosis through medical data analysis. Data Sci Eng 1:54–64

    Article  Google Scholar 

  • Siuly S, Li Y, Wen P (2011) EEG signal classification based on simple random sampling technique with least square support vector machines. Int J Biomed Eng Technol 7:390–409

    Article  Google Scholar 

  • Solinski M, Gierałtowski J, Zebrowski J (2016) Modeling heart rate variability including the effect of sleep stages. Chaos 26:023101

    Article  PubMed  Google Scholar 

  • Song Y (2011) A review of developments of EEG-based automatic medical support systems for epilepsy diagnosis and seizure detection. J Biomed Sci Eng 4:788–796

    Article  Google Scholar 

  • Soo Y, Sugi M, Nishino M, Yokoi H, Arai T, et al (2009) Quantitative estimation of muscle fatigue using surface electromyography during static muscle contraction. In: 31st IEEE Engineering in Medicine and Biology Society conference, Minneapolis, MN, Sept 3–6, 1, 2975–2978

    Google Scholar 

  • Stam CJ (2005) Nonlinear dynamical analysis of EEG and MEG: review of an emerging field. Clin Neurophysiol 116:2266–2301

    Article  CAS  PubMed  Google Scholar 

  • Stam CJ, Jelles B, Achtereekte HA, Rombouts SA, Slaets JP et al (1995) Investigation of EEG non-linearity in dementia and Parkinson’s disease. Electroencephalogr Clin Neurophysiol 95:309–317

    Article  CAS  PubMed  Google Scholar 

  • Stanley HE, Meakin P (1988) Multifractal phenomena in physics and chemistry. Nature 335:405–409

    Article  CAS  Google Scholar 

  • Stanley HE, Amaral LAN, Goldberger AL, Havlin S, Ivanov PC et al (1999) Statistical physics and physiology: Monofractal and multifractal approaches. Physica A 270:309–324

    Article  CAS  PubMed  Google Scholar 

  • Stollberger C, Finsterer J, Lutz W, Stoberl C, Kroiss A et al (2000) Multivariate analysis based prediction rule for pulmonary embolism. Thromb Res 97:267–273

    Article  CAS  PubMed  Google Scholar 

  • Sugavaneswaran L, Umapathy K, Krishnan S (2012) Ambiguity domain-based identification of altered gait pattern in ALS disorder. J Neural Eng 9(4):046004

    Article  CAS  PubMed  Google Scholar 

  • Suryanarayanan S, Reddy NP, Gupta V (1995) Artificial neural networks for estimation of joint angle from EMG signals. In: Proceedings of 17th international conference of the engineering in Medicine and Biology Society, 1

    Google Scholar 

  • Tafhim M, Kshirsagar P (2014) A Review on EMG Signal Classification for neurological disorder using neural network. In: International conference on Advances in Engineering & Technology – 2014 (ICAET-2014), pp 21–23

    Google Scholar 

  • Talebinejad M, Chan ADC, Miri A, Dansereau RM (2009) Fractal analysis of surface electromyography signals: a novel power spectrum- based method. J Electromyogr Kinesiol 19:840–850

    Article  PubMed  Google Scholar 

  • Talkner P, Weber RO (2000) Power spectrum and detrended fluctuation analysis: application to daily temperatures. Phys Rev E 62:150

    Article  CAS  Google Scholar 

  • Telesca L, Lapenna V (2006) Measuring multifractality in seismic sequences. Tectonophysics 423:115–123

    Article  Google Scholar 

  • Telesca L, Lapenna V, Macchiato M (2005) Multifractal fluctuations in earthquake-related geoelectrical signals. New J Phys 7:214

    Article  Google Scholar 

  • Thankor NV, Tong S (2009) Quantitative EEG analysis methods and clinical applications (Artech House, 2009)

    Google Scholar 

  • Thongpanja S, Phinyomark A, Quaine F, Laurillau Y, Wongkittisuksa B, et al (2013) Effects of window size and contraction types on the stationarity of biceps brachii muscle EMG signals. In: IEEE 7th International Convention on Rehabilitation Engineering and Assistive Technology, 2013, 44:1–44:4

    Google Scholar 

  • Tzallas AT, Tsipouras MG, Fotiadis DI (2009) Epileptic seizure detection in EEGs using time-frequency analysis. IEEE Trans Inf Technol Biomed 13:703–710

    Article  PubMed  Google Scholar 

  • Ullah K, Jung-Hoon K (2009) A mathematical model for mapping EMG signal to joint torque for the human elbow joint using nonlinear regression. In: 4th International Conference on Autonomous Robots and Agents, ICARA 2009

    Google Scholar 

  • Vaillancourt DE, Newell KM (2000) The dynamics of resting and postural tremor in Parkinson's disease. Clin Neurophysiol 111(11):2046–2056

    Article  CAS  PubMed  Google Scholar 

  • Vanage AM, Khade RH, Shinde DB (2012) Classifying five different arrhythmias by analyzing the ECG signals. IJCEM Int J Comput Eng Manag 15:75–80

    Google Scholar 

  • Vandewalle N, Ausloos M (1998) Crossing of two mobile averages: a method for measuring the roughness exponent. Phys Rev E 58:6832–6834

    Article  CAS  Google Scholar 

  • Vandewalle N, Ausloos M, Boveroux P (1999a) The moving averages demystified. Physica A 269:170–176

    Article  Google Scholar 

  • Vandewalle N, Ausloos M, Houssa M, Mertens PW, Heyns MM (1999b) Non-Gaussian behavior and anticorrelations in ultrathin gate oxides after soft breakdown. Appl Phys Lett 74:1579–1581

    Article  CAS  Google Scholar 

  • Varon C, Caicedo A, Jansen K, Lagae L, Huffel SV (2014) Detection of epileptic seizures from single lead ECG by means of phase rectified signal averaging. In: 36th Annual international conference of the IEEE Engineering in Medicine and Biology Society, Chicago, pp 3789–3790

    Google Scholar 

  • Vaseghi VS (1996) Advanced Signal Processing and Digital Noise Reduction. John Wiley, New York

    Book  Google Scholar 

  • Vassoler RT, Zebende GF (2012) DCCA cross-correlation coefficient apply in time series of air temperature and air relative humidity. Physica A 391:2438–2443

    Article  Google Scholar 

  • Venugopal G, Ramakrishnan S (2014) Analysis of progressive changes associated with muscle fatigue in dynamic contraction of biceps brachii muscle using surface EMG signals and bispectrum features. Biomed Eng Lett 4:269–276

    Article  Google Scholar 

  • Venugopal G, Navaneethakrishna M, Ramakrishnan S (2014) Extraction and analysis of multiple time window features associated with muscle fatigue conditions using SEMG signals. Expert Syst Appl 41:2652–2659

    Article  Google Scholar 

  • Vinik AI, Erbas T, Casellini CM (2013) Diabetic cardiac autonomic neuropathy, inflammation and cardiovascular disease. J Diab Invest 4:4–18

    Article  CAS  Google Scholar 

  • Vogel J, Castellini C, van der Smagt PP (2011) EMG-based teleoperation and manipulation with the DLR LWR-III. In: Proceedings IEEE/RSJ international conference on Intelligent Robots and Systems, 2011, pp 672–678

    Google Scholar 

  • von Campenhausen S, Bornschein B, Wick R, Botzel K, Sampaio C et al (2005) Prevalence and incidence of Parkinson’s disease in Europe. Eur Neuropsychopharmacol 15:473–490

    Article  CAS  Google Scholar 

  • Wang G, Huang H, Xie H, Wang Z, Hu X (2007) Multifractal analysis of ventricular fibrillation and ventricular tachycardia. Med Eng Phys 29:375–379

    Article  PubMed  Google Scholar 

  • Wang Y, Wei Y, Wu C (2010) Cross-correlations between Chinese A-share and B-share markets. Physica A 389:5468–5478

    Article  Google Scholar 

  • Warner JH, Sampalo C (2016) Modeling variability in the progression of Huntington’s disease a novel modeling approach applied to structural imaging markers from TRACK-HD. CPT Pharmacometrics Syst Pharmacol 5:437–445

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Webber CL Jr, Zbilut JP (1984) Dynamical assessment of physiological systems and states using recurrence plot strategies. J Appl Physiol 76:965–973

    Article  Google Scholar 

  • Weibel ER (1991) Fractal geometry: a design principle for living organisms. Am J Physiol 261:361–369

    Google Scholar 

  • Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ et al (2012) The Alzheimer’s disease neuroimaging initiative: a review of papers published since its inception. Alzheimers Dement 8:S1–S68

    Article  PubMed  Google Scholar 

  • Wessel N, Ziehmann C, Kurths J, Meyerfeldt U, Schirdewan A et al (2000) Short-term forecasting of life-threatening cardiac arrhythmias based on symbolic dynamics and finite- time growth rules. Phys Rev E 61:733–739

    Article  CAS  Google Scholar 

  • Wink AM, Bullmore E, Barnes A, Bernard F, Suckling J (2008) Monofractal and multifractal dynamics of low frequency endogenous brain oscillations in functional MRI. Hum Brain Mapp 29:791–801

    Article  PubMed  PubMed Central  Google Scholar 

  • Wittchen HU, Jacobi F, Rehm J, Gustavsson A, Svensson M et al (2011) The size and burden of mental disorders and other disorders of the brain in Europe 2010. Eur Neuropsychopharmacol 21:655–679

    Article  CAS  PubMed  Google Scholar 

  • Yuan Q, Zhou W, Li S, Cai D (2011) Epileptic EEG classification based on extreme learning machine and nonlinear features. Epilepsy Res 96:29–38

    Article  PubMed  Google Scholar 

  • Yuan Y, Zhuang X, Liu Z (2012) Price-volume multifractal analysis and its application in Chinese stock markets. Physica A 391:3484–3495

    Article  Google Scholar 

  • Yunfeng Wu, Sin CN (2010) A PDF-based classification of gait cadence patterns in patients with amyotrophic lateral sclerosis. In: Annual international conference of the IEEE EMBS Buenos Aires, Argentina, pp 1304–1307, 2010

    Google Scholar 

  • Zandi SA, Dumont GA, Javidan M, Tafreshi R (2009) An entropy-based approach to predict seizures in temporal lobe epilepsy using scalp EEG. Conf Proc IEEE Eng Med Biol Soc 2009:2228–2231

    Google Scholar 

  • Zebende GF (2011) DCCA cross-correlation coefficient: quantifying level of cross-correlation. Physica A 390:614–618

    Article  Google Scholar 

  • Zhang ZG, Liu HT, Chan SC, Luk KDK, Hu Y (2010) Time- dependent power spectral density estimation of surface electromyography during isometric muscle contraction: methods and comparisons. J Electromyogr Kinesiol 20:89–101

    Article  PubMed  Google Scholar 

  • Zheng Y, Gao JB, Sanchez JC, Principe JC, Okun MS (2005) Multiplicative multifractal modeling and discrimination of human neuronal activity. Phys Lett A 344:253–264

    Article  CAS  Google Scholar 

  • Zhou WX (2008) Multifractal detrended cross-correlation analysis for two nonstationary time series. Phys Rev E 77:066211

    Article  CAS  Google Scholar 

  • Zhou P, Li X, Nezhad FJ, Rymer WZ, Barkhaus PE (2012) Duration of observation required in detecting fasciculation potentials in amyotrophic lateral sclerosis using high-density surface EMG. J Neuroeng Rehabil 9:78

    Article  PubMed  PubMed Central  Google Scholar 

  • Zhuo SM, Gan JQ, Sepulveda F (2008) Classifying mental tasks based on features of higher-order statistics from EEG signals in brain–computer interface. Inf Sci 178:1629–1640

    Article  Google Scholar 

  • Zueva MV (2015) Fractality of sensations and the brain health: the theory linking neurodegenerative disorder with distortion of spatial and temporal scale-invariance and fractal complexity of the visible world. Front Aging Neurosci 7:135

    Article  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. Department of Physics, Sir C V Raman Centre for Physics and Music, Jadavpur University, Kolkata, West Bengal, India

    Dipak Ghosh

  2. Department for Physics, Seacom Engineering College, Howrah, West Bengal, India

    Shukla Samanta

  3. Electrical and Electronics Engineering, ICFAI University, Agartala, Tripura, India

    Sayantan Chakraborty

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  1. Dipak Ghosh
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  2. Shukla Samanta
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  3. Sayantan Chakraborty
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Ghosh, D., Samanta, S., Chakraborty, S. (2019). Introduction. In: Multifractals and Chronic Diseases of the Central Nervous System. Springer, Singapore. https://doi.org/10.1007/978-981-13-3552-5_1

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