Amoud H, Snoussi H, Hewson D, Duchêne J (2008) Univariate and bivariate empirical mode decomposition for postural stability analysis. Eurasip J Adv Signal Process 2008:1–11
Arunganesh K, Sivakumaran N, Kumaravel S, Karthick P (2021) Analysis of EEG-EMG coherence in low frequency bands. Stud Health Technol Inf 281:520–521
Aydın S, Demirtaş S, Yetkin S (2018) Cortical correlations in wavelet domain for estimation of emotional dysfunctions. Neural Comput Appl 30:1085–1094
Budini F, Mcmanus LM, Berchicci M, Menotti F, Macaluso A, Russo FD, Lowery MM, Vito GD (2014) Alpha band cortico-muscular coherence occurs in healthy individuals during mechanically-induced tremor. PLoS ONE 9:1–15
Chen X, Xie P, Zhang Y, Chen Y, Yang F, Zhang L, Li X (2018) Multiscale information transfer in functional corticomuscular coupling estimation following stroke: a pilot study. Front Neurol 9:287–297
Article PubMed PubMed Central Google Scholar
Chen X, Zhang Y, Cheng S, Xie P (2019) Transfer spectral entropy and application to functional corticomuscular coupling. IEEE Trans Neural Syst Rehabil Eng 27:1092–1102
Chen X, Zhang Y, Yang Y, Li X, Xie P (2020) Beta-range corticomuscular coupling reflects asymmetries in hand movement. IEEE Trans Neural Syst Rehabil Eng 28:2575–2585
Choi W, Lee JW, Huh M-H, Kang S-H (2003) An algorithm for computing the exact distribution of the Kruskal–Wallis test. Commun Stat Simul Comput 32:1029–1040
Conway B, Halliday D, Farmer S, Shahani U, Maas P, Weir A, Rosenberg J (1995) Synchronization between motor cortex and spinal motoneuronal pool during the performance of a maintained motor task in man. J Physiol 489:917–924
Article PubMed PubMed Central CAS Google Scholar
Corder GW, Foreman DI (2009) Comparing more than two unrelated samples: the Kruskal–Wallis H-test. In: Nonparametric statistics for non-statisticians: a step-by-step approach, pp 99–121
Costa M, Goldberger AL, Peng C-K (2002) Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett 89:068102-068101–068102-068104
Dimigen O (2020) Optimizing the ICA-based removal of ocular EEG artifacts from free viewing experiments. Neuroimage 207:116117–116165
Dooley EE, Golaszewski NM, Bartholomew JB (2017) Estimating accuracy at exercise intensities: a comparative study of self-monitoring heart rate and physical activity wearable devices. JMIR Mhealth Uhealth 5:e7043
Faes L, Montalto A, Stramaglia S, Nollo G, Marinazzo D (2016) Multiscale analysis of information dynamics for linear multivariate processes. In: 2016 38th Annual international conference of the IEEE engineering in medicine and biology society (EMBC). IEEE, pp 5489–5492
Gao Y, Ren L, Zhou X, Zhang Q, Zhang Y (2018) Multichannel EEG-EMG coupling analysis using a variable scale symbolic transfer entropy approach. Chin J Biomed Eng 37:8–16
Gourévitch B, Bouquin-Jeannès RL, Faucon G (2006) Linear and nonlinear causality between signals: methods, examples and neurophysiological applications. Biol Cybern 95:349–369
Guo Z, McClelland VM, Simeone O, Mills KR, Cvetkovic Z (2021) Multiscale wavelet transfer entropy with application to corticomuscular coupling analysis. IEEE Trans Biomed Eng 69:771–782
Hadoush H, Alafeef M, Abdulhay E (2019) Brain complexity in children with mild and severe autism spectrum disorders: analysis of multiscale entropy in EEG. Brain Topogr 32:914–921
Halliday DM, Conway BA, Farmer SF, Rosenberg JR (1998) Using electroencephalography to study functional coupling between cortical activity and electromyograms during voluntary contractions in humans. Neurosci Lett 241:5–8
Article PubMed CAS Google Scholar
Hu M, Liang H (2017) Multiscale entropy: recent advances. In: Complexity and nonlinearity in cardiovascular signals, pp 115–138
Huang NE, Shen Z, Long SR, Wu MC, Shih HH, Zheng Q, Yen N-C, Tung CC, Liu HH (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc Roy Soc Lond Ser A Math Phys Eng Sci 454:903–995
Hussain L, Aziz W, Saeed S, Shah SA, Nadeem MSA, Awan IA, Abbas A, Majid A, Kazmi SZH (2017) Complexity analysis of EEG motor movement with eye open and close subjects using multiscale permutation entropy (MPE) technique. Biomed Res 28:7104–7111
Izvekov S, Voth GA (2005) A multiscale coarse-graining method for biomolecular systems. J Phys Chem B 109:2469–2473
Article PubMed CAS Google Scholar
Kandel E (1995) Essentials of neural science and behavior. Appleton Lange Norwalk CT 6:425–451
Kayama Y (1985) Ascending, descending and local control of neuronal activity in the rat lateral geniculate nucleus. Vis Res 25:339–347
Article PubMed CAS Google Scholar
Kılıç B, Aydın S (2022) Classification of contrasting discrete emotional states indicated by EEG based graph theoretical network measures. Neuroinformatics 1–15
Kumar JS, Bhuvaneswari P (2012) Analysis of electroencephalography (EEG) signals and its categorization—a study. Proc Eng 38:2525–2536
Li D, Li X, Liang Z, Voss LJ, Sleigh JW (2010) Multiscale permutation entropy analysis of EEG recordings during sevoflurane anesthesia. J Neural Eng 7:046010–046014
Li K, Hogrel J-Y, Duchêne J, Hewson DJ (2012) Analysis of fatigue and tremor during sustained maximal grip contractions using Hilbert–Huang transformation. Med Eng Phys 34:832–840
Liang Z, Cheng L, Shao S, Jin X, Yu T, Sleigh JW, Li X (2020) Information integration and mesoscopic cortical connectivity during propofol anesthesia. Anesthesiology 132:504–524
Liu J, Tan G, Sheng Y, Liu H (2020) Multiscale transfer spectral entropy for quantifying corticomuscular interaction. IEEE J Biomed Health Inform 25:2281–2292
Liu J, Wang J, Tan G, Sheng Y, Chang H, Xie Q, Liu H (2021) Correlation evaluation of functional corticomuscular coupling with abnormal muscle synergy after stroke. IEEE Trans Biomed Eng 68:3261–3272
Looney D, Park C, Kidmose P, Ungstrup M, Mandic D (2009) Measuring phase synchrony using complex extensions of EMD. In: 2009 IEEE/SP 15th workshop on statistical signal processing. IEEE, pp 49–52
Looney D, Mandic DP (2009) Multiscale image fusion using complex extensions of EMD. IEEE Trans Signal Process 57:1626–1630
Lungarella M, Pitti A, Kuniyoshi Y (2007) Information transfer at multiple scales. Phys Rev E 76:1–10
Mehrkanoon S, Breakspear M, Boonstra TW (2014) The reorganization of corticomuscular coherence during a transition between sensorimotor states. Neuroimage 100:692–702
Mima T, Hallett M (1999) Corticomuscular coherence: a review. J Clin Neurophysiol 16:501–511
Article PubMed CAS Google Scholar
Mima T, Steger J, Schulman AE, Gerloff C, Hallett M (2000) Electroencephalographic measurement of motor cortex control of muscle activity in humans. Clin Neurophysiol 111:326–337
Article PubMed CAS Google Scholar
Mima T, Matsuoka T, Hallett M (2001) Information flow from the sensorimotor cortex to muscle in humans. Clin Neurophysiol 112:122–126
Article PubMed CAS Google Scholar
Oldfield RC (1971) The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9:97–113
Article PubMed CAS Google Scholar
Pal S, Mitra M (2012) Empirical mode decomposition based ECG enhancement and QRS detection. Comput Biol Med 42:83–92
Park C, Looney D, Kidmose P, Ungstrup M, Mandic DP (2011) Time-frequency analysis of EEG asymmetry using bivariate empirical mode decomposition. IEEE Trans Neural Syst Rehabil Eng 19:366–373
Ping X, Yang F, Chen X, Du Y, Wu X (2015) Functional coupling analyses of electroencephalogram and electromyogram based on multiscale transfer entropy. Acta Physica Sinica 64:1–10
Ping X, Yang F, Chen X, Wu X (2017) EEG-EMG synchronization analysis based on gabor wavelet transform-granger causality. Chin J Biomed Eng 36:28–38
Pool E-M, Rehme AK, Fink GR, Eickhoff SB, Grefkes C (2013) Network dynamics engaged in the modulation of motor behavior in healthy subjects. Neuroimage 82:68–76
Raethjen J, Lindemann M, Dümpelmann M, Wenzelburger R, Stolze H, Pfister G, Elger CE, Timmer J, Deuschl G (2002) Corticomuscular coherence in the 6–15 Hz band: is the cortex involved in the generation of physiologic tremor? Exp Brain Res 142:32–40
Rilling G, Flandrin P, Gonçalves P, Lilly JM (2007) Bivariate empirical mode decomposition. IEEE Signal Process Lett 14:936–939
Salankar N, Mishra P, Garg L (2021) Emotion recognition from EEG signals using empirical mode decomposition and second-order difference plot. Biomed Signal Process Control 65:1–13
Schreiber T, Schmitz A (2000) Surrogate time series. Physica D 142:346–382
Surendran A, Jacob JE, Gopakumar K (2020) Analysis of EEG using variational mode decomposition method for diagnosis of epilepsy. In: AIP conference proceedings. AIP Publishing LLC, pp 1–6
Tavakoli Najafabadi M, Abootalebi V, Shayegh F (2016) A new hybrid method for EOG artifact rejection from EEG signal using CCA and RLS. Iran J Biomed Eng 10:1–10
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