中文

Journal of Applied Sciences >

2014 , Vol. 32 >Issue 6: 631 - 638

DOI: https://doi.org/10.3969/j.issn.0255-8297.2014.06.013

Signal and Information Processing

Entropy Analysis of EEG for Elderly Patients with Mild Cognitive Impairment

Expand
  • 1. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
    2. Xuanwu Hospital, Capital Medical University, Beijing 100053, China
    3. Beijing Key Laboratory of Neuromodulation, Beijing 100053, China

Received date: 2013-07-20

  Revised date: 2014-04-04

  Online published: 2014-04-04

Fold

Abstract

 In this study, eight elderly patients with mild cognitive impairment (MCI) and 17 normal controls
participated in a cognition task. The subjects were asked to judge whether the color of two graphics is matched
or not, and their scalp electroencephalographs (EEG) were recorded. We calculated the relative power, sample
entropy (SEn) and cumulative residual entropy (CREn) of the event-related EEG signals to explore differences
between the MCI patients and normal controls. The following results were obtained. 1) There was no
difference in alpha relative power, while the MCI patients had higher complexity at medial-frontal and medialposterior
regions than the normal controls. 2) The frontal region showed significantly higher complexity than
other regions and the center hemisphere had lower complexity than left and right hemisphere in both groups
throughout the task. 3) Complexity in anterior brain in match task was higher than that in mismatch task
in both groups. Normal controls had more complex EEG activity during the match task in the right-center
region. 4) Relative to SEn, the analysis of CREn found more specific nonlinear characteristic in the EEG of
MCI patients. All these results show the MCI patients have abnormal EEG activity in brain, and CREn is
more suitable for describing the nonlinear characteristic of EEG than SEn.

Key words： cognitive impairment (MCI); electroencephalographs (EEG); relative power; sample entropy; cumulative residual entropy

Cite this article

WEI Ling1, ZHAO Jian-qiang1, SHI Jun1, XUE Qing2,3, WANG Yu-ping2,3, LI Ying-jie1 . Entropy Analysis of EEG for Elderly Patients with Mild Cognitive Impairment[J]. Journal of Applied Sciences, 2014 , 32(6) : 631 -638 . DOI: 10.3969/j.issn.0255-8297.2014.06.013

References

[1] LEVEY A, LAH J, GOLDSTEIN F, STEENLAND K, BLIWISE D. Mild cognitive impairment: an opportunity to identify patients at high risk for progression to Alzheimer's disease[J]. Clinical Therapeutics, 2006, 28(7): 991-1001.

 [2] MORETTI D V, MINIUSSI C, FRISONI G B, GEROLDI C, ZANETTI O, BINETTI G, ROSSINI P M. Hippocampal atrophy and EEG markers in subjects with mild cognitive impairment[J]. Clinical Neurophysiology, 2007, 118(12): 2716-2729.

 [3] BABILONI C, FRISONI G B, PIEVANI M, VECCHIO F, LIZIO R, BUTTIGLIONE M, GEROLDI C, FRACASSI C, EUSEBI F, FERRI R, ROSSINI P M. Hippocampal volume and cortical sources of EEG alpha rhythms in mild cognitive impairment and Alzheimer disease[J]. Neuroimage, 2009, 44(1): 123-135.

 [4] STAM C J. Nonlinear dynamical analysis of EEG and MEG: review of an emerging field[J]. Clinical Neurophysiology, 2005, 116(10): 2266-2301.

 [5] HOGAN M J, KILMARTIN L, KEANE M, COLLINS P, STAFF R T, KAISER J, LAI R, UPTON N. Electrophysiological entropy in younger adults, older controls and older cognitively declined adults[J]. Brain Research, 2012, 1445: 1-10.

 [6] WANG F, VEMURI B C. Non-Rigid Multi-Modal Image Registration Using Cross-Cumulative Residual Entropy[J].International Journal of Computer Vision, 2007, 74(2): 201-215.

 [7] WANG Y, TANG X, KONG J, ZHUANG D, LI S. Different systems in human brain are involved in presemantic discrimination of pictures as revealed by event-related potentials[J]. Neuroscience Letters, 1998, 257(3): 143-146.

 [8] WANG Y, CUI L, WANG H, TIAN S, ZHANG X. The sequential processing of visual feature conjunction mismatches in the human brain [J]. Psychophysiology, 2004, 41(1): 21-29.

 [9] AKIN M. Comparison of wavelet transform and FFT methods in the analysis of EEG signals [J]. Journal of Medical Systems, 2002, 26(3): 241-247.

[10] RICHMAN J S, MOORMAN J R. Physiological time-series analysis using approximate entropy and sample entropy [J]. American Journal of Physiology- Heart and Circulatory Physiology, 2000, 278(6): 2039-2049.

[11] ZHONG J, SHI J, CAI Y, ZHANG Q. Recognition of hand motions via surface EMG signal with rough entropy[C]//IEEE International Conference on Engineering in Medicine and Biology Society.Boston, America,2011: 4100-4103.

[12] VANDER HIELE K, VEIN A A, REIJNTJES R H, WESTENDORP R G, BOLLEN E L, VAN BUCHEM M A, VAN DIJK J G, MIDDELKOOP H A. EEG correlates in the spectrum of cognitive decline[J]. Clinical Neurophysiology, 2007, 118(9): 1931-1939.

[13] BABILONI C, BINETTI G, CASSETTA E, Dal FORNOG, DEL P C, FERRERI F, FERRI R, FRISONI G, HIRATA K, LANUZZA B, MINIUSSI C, MORETTI D V, NOBILI F, RODRIGUEZ G, ROMANI G L, SALINARI S, ROSSINI P M. Sources of cortical rhythms change as a function of cognitive impairment in pathological aging: a multicenter study[J]. Clinical Neurophysiology, 2006, 117(2): 252-268.

[14] BABILONI C, LIZIO R, VECCHIO F, FRISONI G B, PIEVANI M, GEROLDI C, CLAUDIA F, FERRI R, LANUZZA B, ROSSINI P M. Reactivity of cortical alpha rhythms to eye opening in mild cognitive impairment  and Alzheimer's disease: an EEG study[J].Journal of Alzheimer'sDisease,2010, 22(4): 1047-1064.

[15] VANDER HIELE K, VEIN A A, VANDER WELLE A, VANDER GROND J, WESTENDORP R G, BOLLEN E L, VAN BUCHEM M A, VAN DIJK J G, MIDDELKOOP H A. EEG and MRI correlates of mild cognitive impairment and Alzheimer's disease[J]. Neurobiology of Aging, 2007, 28(9): 1322-1329.

[16] CABEZA R. Hemispheric asymmetry reduction in older adults: the HAROLD model [J]. Psychology and Aging, 2002, 17(1): 85-100.

[17]GUTCHESS A H, IEUJI Y, FEDERMEIER K D. Event-related potentials reveal age differences in the encoding and recognition of scenes [J]. Journal of Cognitive Neuroscience, 2007, 19(7): 1089-1103.

[18] TRZEPACZ P T, YU P, BHAMIDIPATI P K, WILLIS B, FORRESTER T, TABAS L, SCHWARZ A J, SAYKIN A J. Frontolimbic atrophy is associated with agitation and aggression in mild cognitive impairment and Alzheimer's disease[J]. Alzheimers Dement, 2012.

[19] TAKAHASHI T, CHO R Y, MURATA T, MIZUNO T, KIKUCHI M, MIZUKAMI K, KOSAKA H, TAKAHASHI K, WADA Y. Age-related variation in EEG complexity to photic stimulation: a multiscale entropy analysis[J]. Clinical Neurophysiology, 2009, 120(3): 476-483.
 
Options
Outlines

/

〈 〉