Analysis of entropies based on empirical mode decomposition in amnesic mild cognitive impairment of diabetes mellitus

Dong Cui; Jinhuan Wang; Zhijie Bian; Qiuli Li; Lei Wang; Xiaoli Li

doi:10.1142/s1793545815500108

[1] E. Ginter, V. Simko, "Type 2 diabetes mellitus, pandemic in 21st century," Adv. Exp. Med. Biol. 771, 42–50 (2012).

[2] J. A. Luchsinger, C. Reitz, B. Patel, M. X. Tang, J. J. Manly, R. Mayeux, "Relation of diabetes to mild cognitive impairment," Archiv. Neurol. 64(4), 570– 575 (2007).

[3] D. G. Bruce, W. A. Davis, G. P. Casey, S. E. Starkstein, R. M. Clarnette, O. P. Almeida, T. M. E. Davis, "Predictors of cognitive decline in older individuals with diabetes," Diabetes Care 31(11), 2103–2107 (2008).

[4] J. S. Saczynski, M. K. Jonsdottir, M. E. Garcia, P. V. Jonsson, R. Peila, G. Eiriksdottir, E. Olafsdottir, T. B. Harris, V. Gudnason, L. J. Launer, "Cognitive impairment: An increasingly important complication of type 2 diabetes," Am. J. Epidemiol. 168(10), 1132–1139 (2008).

[5] Y. W. Zhang, X. Zhang, J. Q. Zhang, C. Liu, Q. Y. Yuan, X. T. Yin, L. Q. Wei, J. G. Cui, R. Tao, P. Wei, J. Wang, "Gray matter volume abnormalities in type 2 diabetes mellitus with and without mild cognitive impairment," Neurosci. Lett. 562, 1–6 (2014).

[6] E. M. C. Schrijvers, J. C. M. Witteman, E. J. G. Sijbrands, A. Hofman, P. J. Koudstaal, M. M. B. Breteler, "Insulin metabolism and the risk of Alzheimer disease The Rotterdam study," Neurology 75(22) 1982–1987 (2010).

[7] R. O. Roberts, D. S. Knopman, Y. E. Geda, R. H. Cha, V. S. Pankratz, L. Baertlein, B. F. Boeve, E. G. Tangalos, R. J. Ivnik, M. M. Mielke, R. C. Petersen, "Association of diabetes with amnestic and nonamnestic mild cognitive impairment," Alzheimers Dement. 10(1), 18–26 (2014).

[8] T. Cukierman, H. C. Gerstein, J. D. Williamson, "Cognitive decline and dementia in diabetes-systematic overview of prospective observational studies," Diabetologia 48(12), 2460–2469 (2005).

[9] M. Elgendi, F. Vialatte, A. Cichocki, C. Latchoumane, J. Jeong, J. Dauwels, "Optimization of EEG frequency bands for improved diagnosis of Alzheimer disease," 2011 Annual Int. Conf. IEEE Engineering in Medicine and Biology Society, pp. 6087–6091 (2011).

[10] T. Gili, M. Cercignani, L. Serra, R. Perri, F. Giove, B. Maraviglia, C. Caltagirone, M. Bozzali, "Regional brain atrophy and functional disconnection across Alzheimer's disease evolution," J. Neurol. Neurosurg. Ps 82(1), 58–66 (2011).

[11] C. Babiloni, R. Ferri, G. Binetti, A. Cassarino, G. Dal Forno, M. Ercolani, F. Ferreri, G. B. Frisoni, B. Lanuzza, C. Miniussi, F. Nobili, G. Rodriguez, F. Rundo, C. J. Stam, T. Musha, F. Vecchio, P. M. Rossini, "Fronto-parietal coupling of brain rhythms in mild cognitive impairment: A multicentric EEG study," Brain Res. Bull. 69(1), 63–73 (2006).

[12] J. E. Skinner, D. N. Weiss, J. M. Anchin, Z. Turianikova, I. Tonhajzerova, J. Javorkova, K. Javorka, M. Baumert, M. Javorka, "Nonlinear PD2i heart rate complexity algorithm detects autonomic neuropathy in patients with type 1 diabetes mellitus," Clin. Neurophysiol. 122(7), 1457–1462 (2011).

[13] Y. Chen, T. D. Pham, "Sample entropy and regularity dimension in complexity analysis of cortical surface structure in early Alzheimer's disease and aging," J. Neurosci. Methods 215(2), 210–217 (2013).

[14] P. H. Tsai, C. Lin, J. Tsao, P. F. Lin, P. C. Wang, N. E. Huang, M. T. Lo, "Empirical mode decomposition based detrended sample entropy in electroencephalography for Alzheimer's disease," J. Neurosci. Methods 210(2), 230–237 (2012).

[15] T. Mizuno, T. Takahashi, R. Y. Cho, M. Kikuchi, T. Murata, K. Takahashi, Y. Wada, "Assessment of EEG dynamical complexity in Alzheimer's disease using multiscale entropy," Clin. Neurophysiol. 121(9), 1438–1446 (2010).

[16] D. Abasolo, J. Escudero, R. Hornero, C. Gomez, P. Espino, "Approximate entropy and auto mutual information analysis of the electroencephalogram in Alzheimer's disease patients," Med. Biol. Eng. Comput. 46(10), 1019–1028 (2008).

[17] D. Abasolo, R. Hornero, P. Espino, D. Alvarez, J. Poza, "Entropy analysis of the EEG background activity in Alzheimer's disease patients," Physiol. Meas. 27(3), 241–253 (2006).

[18] F. J. Hsiao, W. T. Chen, Y. J. Wang, S. H. Yan, Y. Y. Lin, "Altered source-based EEG coherence of resting-state sensorimotor network in early-stage Alzheimer's disease compared to mild cognitive impairment," Neurosci. Lett. 558, 47–52 (2014).

[19] D. Abasolo, R. Hornero, P. Espino, D. Alvarez, J. Poza, "Multiway array decomposition analysis of EEGs in Alzheimer's disease," J. Neurosci. Methods 207(1), 41–50 (2012).

[20] P. Ghorbanian, D. M. Devilbiss, A. J. Simon, A. Bernstein, T. Hess, H. Ashrafiuon, Discrete wavelet transform EEG features of Alzheimer's disease in activated states, 2012 Annual Int. Conf. IEEE Engineering in Medicine and Biology Society, pp. 2937–2940 (2012).

[21] F. J. Fraga, T. H. Falk, L. R. Trambaiolli, E. F. Oliveira, W. H. L. Pinaya, P. A. M. Kanda, R. Anghinah, "Towards an EEG-based biomarker for Alzheimer's disease: Improving amplitude modulation analysis features," Int. Conf. Acoust. Speech, pp. 1207–1211 (2013).

[22] J. Escudero, D. Abasolo, R. Hornero, P. Espino, M. Lopez, "Analysis of electroencephalograms in Alzheimer's disease patients with multiscale entropy," Physiol. Meas. 27(11), 1091–1106 (2006).

[23] G. Emmanuelle, H. H. Anne, M. Guillaume, C. Mathieu, L. Georges, "Complexity quantification of signals from the heart, the macrocirculation and the microcirculation through a multiscale entropy analysis," Biomed. Signal Process. 8(4), 341–345 (2013).

[24] D. Abasolo, R. Hornero, P. Espino, J. Poza, C. I. Sanchez, R. de la Rosa, "Analysis of regularity in the EEG background activity of Alzheimer's disease patients with approximate entropy," Clin. Neurophysiol. 116(8), 1826–1834 (2005).

[25] M. P. Tarvainen, D. J. Cornforth, P. Kuoppa, J. A. Lipponen, H. F. Jelinek, Complexity of heart rate variability in type 2 diabetes — effect of hyperglycemia, 2013 Annual Int. Conf. IEEE Engineering in Medicine and Biology Society, pp. 5558–5561 (2013).

[26] H. T. Wu, P. C. Hsu, C. F. Lin, H. J. Wang, C. K. Sun, A. B. Liu, M. T. Lo, C. J. Tang, "Multiscale entropy analysis of pulse wave velocity for assessing atherosclerosis in the aged and diabetic," IEEE Trans. Biomed. Eng. 58(10), 2978–2981 (2011).

[27] F. Molinari, U. R. Acharya, R. J. Martis, R. De Luca, G. Petraroli, W. Liboni, "Entropy analysis of muscular near-infrared spectroscopy (NIRS) signals during exercise programme of type 2 diabetic patients: Quantitative assessment of muscle metabolic pattern," Comput. Methods Prog. Biol. 112(3), 518–528 (2013).

[28] M. A. H. Hazari, B. Ram Reddy, N. Uzma, B. S. Kumar, "Cognitive impairment in type 2 diabetes mellitus," Int. J. Diabetes Mellitus 01, 1–6 (2011).

[29] T. Brismar, "The human EEG-physiological and clinical studies," Physiol. Behav. 92(1–2), 141–147 (2007).

[30] G. K. Cooray, L. Maurex, T. Brismar, "Cognitive impairment correlates to low auditory event-related potential amplitudes in type 1 diabetes," Psychoneuroendocrinology 33(7), 942–950 (2008).

[31] G. K. Cooray, L. Hyllienmark, T. Brismar, "Decreased cortical connectivity and information flowin type 1 diabetes," Clin. Neurophysiol. 122(10), 1943–1950 (2011).

[32] N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N. C. Yen, C. C. Tung, H. Liu, "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis," Phys. Eng. Sci. 454(1971), 903–995 (1998).

[33] G. Puavilai, S. Chanprasertyotin, A. Sriphrapradaeng, "Diagnostic criteria for diabetes mellitus and other categories of glucose intolerance: 1997 criteria by the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus (ADA), 1998 WHO consultation criteria, and 1985 WHO criteria. World Health Organization," Diabetes Res. Clin. Pract. 44(1), 21–26 (1999).

[34] F. Portet, P. J. Ousset, P. J. Visser, G. B. Frisoni, F. Nobili, P. Scheltens, B. Vellas, J. Touchon. "Mild cognitive impairment (MCI) in medical practice: A critical review of the concept and new diagnostic procedure. Report of the MCI Working Group of the European Consortium on Alzheimer's Disease," J. Neurol. Neurosurg. Psychiatry 77(6), 714–718 (2006).

[35] G. A. Carlesimo, C. Caltagirone, G. Gainotti, "The mental deterioration battery: Normative data, diagnostic reliability and qualitative analyses of cognitive impairment. The Group for the Standardization of the Mental Deterioration Battery," Eur. Neurol. 36(6), 378–384 (1996).

[36] G. Novelli, Three clinical tests for the assessment of lexical retrieval and production. Norms from 320 normal subjects, Archivio di psicologia, Neurologia E Psichiatria 47, 477–506 (1986).

[37] A. Orsini, D. Grossi, E. Capitani, M. Laiacona, C. Papagno, G. Vallar, "Verbal and spatial immediate memory span: Normative data from 1355 adults and 1112 children," Ital. J. Neurol. Sci. 8(6) 539–548 (1987).

[38] Reitan, "Validity of the trail making test as an indication of organic brain damage," Percept. Mot. Skills 958, 271–276 (1958).

[39] M. P. Lawton, E. M. Brody, "Assessment of older people: Self-maintaining and instrumental activities of daily living," Gerontologist 9(3), 179–186 (1969).

[40] S. M. Pincus, "Approximate entropy as a measure of system complexity," Proc. Natl. Acad. Sci. USA 88, 2297–2301 (1991).

[41] L. Guo, D. Rivero, A. Pazos, "Epileptic seizure detection using multiwavelet transform based approximate entropy and artificial neural networks," J. Neurosci. Methods 193(1), 156–163 (2010).

[42] M. G. Signorini, G. Magenes, S. Cerutti, D. Arduini, "Linear and nonlinear parameters for the analysis of fetal heart rate signal from cardiotocographic recordings," IEEE Trans. Biomed. Eng. 50(3), 365– 374 (2003).

[43] S. M. Pincus, "Assessing serial irregularity and its implications for health," Popul. Health Aging 954, 245–267 (2001).

[44] J. Bruhn, H. Ropcke, A. Hoeft, "Approximate entropy as an electroencephalographic measure of anesthetic drug effect during desflurane anesthesia," Anesthesiology 92(3), 715–726 (2000).

[45] C. E. Elger, G. Widman, R. Andrzejak, M. Dumpelmann, J. Arnhold, P. Grassberger, K. Lehnertz, "Value of nonlinear time series analysis of the EEG in neocortical epilepsies," Adv. Neurol. 84, 317–330 (2000).

[46] L. Zadeh, Fuzzy sets, Inform. Control 8(3), 338–353 (1965).

[47] C. Bandt, B. Pompe, "Permutation entropy: A natural complexity measure for time series," Phys. Rev. Lett. 88(17), 174102 (2002).

[48] X. Li, G. Ouyang, D. A. Richards, "Predictability analysis of absence seizures with permutation entropy," Epilepsy Res. 77(1), 70–74 (2007).

[49] E. Olofsen, J. W. Sleigh, A. Dahan, "Permutation entropy of the electroencephalogram: A measure of anaesthetic drug effect," Br. J. Anaesthesiol 101(6), 810–821 (2008).

[50] J. W. Sleigh, D. A. Steyn-Ross, M. L. Steyn-Ross, C. Grant, G. Ludbrook, "Cortical entropy changes with general anaesthesia: Theory and experiment," Physiol. Meas. 25(4), 921–934 (2004).

[51] W. T. Chen, J. Zhuang, W. X. Yu, Z. Z. Wang, "Measuring complexity using FuzzyEn, ApEn, and SampEn," Med. Eng. Phys. 31(1), 61–68 (2009).

[52] X. L. Li, S. Y. Cui, L. J. Voss, "Using permutation entropy to measure the electroencephalographic effects of sevoflurane," Anesthesiology 109(3), 448– 456 (2008).

[53] H. Vierti€o-Oja, V. Maja, M. S rkel , P. Talja, N. Tenkanen, H. Tolvanen-Laakso, M. Paloheimo, A. Vakkuri, A. Yli-Hankala, P. Meril inen, "Description of the EntropyTM algorithm as applied in the Datex-Ohmeda S/5TM entropy module," Acta Anaesthesiol. Scand. 48(2), 154–161 (2004).

[54] Z. K. Peng, P. W. Tse, F. L. Chu, "A comparison study of improved Hilbert–Huang transform and wavelet transform: Application to fault diagnosis for rolling bearing," Mech. Syst. Signal Process. 19(5), 974–988 (2005).

[55] X. Y. Zhang, J. Z. Zhou, "Multi-fault diagnosis for rolling element bearings based on ensemble empirical mode decomposition and optimized support vector machines," Mech. Syst. Signal Process. 41(1– 2), 127–140 (2013).

[56] J. R. Huang, S. Z. Fan, M. F. Abbod, K. K. Jen, J. F. Wu, J. S. Shieh, "Application of multivariate empirical mode decomposition and sample entropy in EEG signals via artificial neural networks for interpreting depth of anesthesia," Entropy 15(9), 3325–3339 (2013).

[57] X. Li, D. Li, Z. Liang, L. J. Voss, J. W. Sleigh, "Analysis of depth of anesthesia with Hilbert– Huang spectral entropy," Clin. Neurophysiol. 119 (11), 2465–2475 (2008).

[58] A. Gallix, J. M. Gorriz, J. Ramirez, I. A. Illan, E. W. Lang, "On the empirical mode decomposition applied to the analysis of brain SPECT images," Expert Syst. Appl. 39(18), 13451–13461 (2012).

[59] C. Zadikoff, S. H. Fox, D. F. Tang-Wai, T. Thomsen, R. M. A. de Bie, P. Wadia, J. Miyasaki, S. Duff- Canning, A. E. Lang, C. Marras, "A comparison of the mini mental state exam to the Montreal cognitive assessment in identifying cognitive deficits in Parkinson's disease," Mov. Disord. 23(2), 297–299 (2008).

[60] D. R. Roalf, P. J. Moberg, S. X. Xie, D. A. Wolk, S. T. Moelter, S. E. Arnold, "Comparative accuracies of two common screening instruments for classi fication of Alzheimer's disease, mild cognitive impairment, and healthy aging," Alzheimers Dement. 9(5), 529–537 (2013).

[61] P. Athilingam, K. B. King, S. W. Burgin, M. Ackerman, L. A. Cushman, L. Chen, "Montreal cognitive assessment and mini-mental status examination compared as cognitive screening tools in heart failure," Heart Lung 40(6), 521–529 (2011).

[62] S. Nazem, A. D. Siderowf, J. E. Duda, T. T. Have, A. Colcher, S. S. Horn, P. J. Moberg, J. R. Wilkinson, H. I. Hurtig, M. B. Stern, D. Weintraub, "Montreal cognitive assessment performance in patients with Parkinson's disease with `normal' global cognition according to mini-mental state examination score," J. Am. Geriatr. Soc. 57(2), 304– 308 (2009).

[63] K. Alagiakrishnan, N. Zhao, L. Mereu, P. Senior, A. Senthilselvan, Montreal cognitive assessment is superior to standardized mini-mental status exam in detecting mild cognitive impairment in the middleaged and elderly patients with type 2 diabetes mellitus, Biomed. Res. Int. 5 (2013), doi: 10.1155/2013/ 186106.

[64] S. M. Manschot, A. M. A. Brands, J. van der Grond, R. P. C. Kessels, A. Algra, L. J. Kappelle, G. J. Biessels, U. D. E. St, "Brain magnetic resonance imaging correlates of impaired cognition in patients with type 2 diabetes," Diabetes 55(4), 1106–1113 (2006).

[65] A. C. Yang, S. J. Wang, K. L. Lai, C. F. Tsai, C. H. Yang, J. P. Hwang, M. T. Lo, N. E. Huang, C. K. Peng, J. L. Fuh, "Cognitive and neuropsychiatric correlates of EEG dynamic complexity in patients with Alzheimer's disease," Prog. Neuropsychopharmacol Biol Psychiatry 47, 52–61 (2013).

[66] J. H. Park, S. Kim, C. H. Kim, A. Cichocki, K. Kim, "Multiscale entropy analysis of EEG from patients under different pathological conditions," Fractals 15(4), 399–404 (2007).