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Computational and Mathematical Methods in Medicine
Volume 2015 (2015), Article ID 953868, 8 pages
Research Article

A Novel Application of Multiscale Entropy in Electroencephalography to Predict the Efficacy of Acetylcholinesterase Inhibitor in Alzheimer’s Disease

1Neurology Department, National Yang-Ming University Hospital, Yi-Lan, Taiwan
2Neurology Department, National Yang-Ming University School of Medicine, Taipei, Taiwan
3Division of Pulmonology, Department of Internal Medicine, National Yang-Ming University Hospital, Yi-Lan, Taiwan
4Department of Internal Medicine, College of Medicine, National Yang-Ming University School of Medicine, Taipei, Taiwan
5Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
6Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chungli, Taiwan
7Research Center for Adaptive Data Analysis, National Central University, No. 300, Jhongda Road, Taoyuan 32001, Taiwan

Received 1 December 2014; Accepted 2 January 2015

Academic Editor: Kazeem O. Okosun

Copyright © 2015 Ping-Huang Tsai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Alzheimer’s disease (AD) is the most common form of dementia. According to one hypothesis, AD is caused by the reduced synthesis of the neurotransmitter acetylcholine. Therefore, acetylcholinesterase (AChE) inhibitors are considered to be an effective therapy. For clinicians, however, AChE inhibitors are not a predictable treatment for individual patients. We aimed to disclose the difference by biosignal processing. In this study, we used multiscale entropy (MSE) analysis, which can disclose the embedded information in different time scales, in electroencephalography (EEG), in an attempt to predict the efficacy of AChE inhibitors. Seventeen newly diagnosed AD patients were enrolled, with an initial minimental state examination (MMSE) score of . After 12 months of AChE inhibitor therapy, 7 patients were responsive and 10 patients were nonresponsive. The major difference between these two groups is Slope 2 (MSE6 to 20). The area below the receiver operating characteristic (ROC) curve of Slope 2 is 0.871 (95% CI = 0.69–1). The sensitivity is 85.7% and the specificity is 60%, whereas the cut-off value of Slope 2 is −0.024. Therefore, MSE analysis of EEG signals, especially Slope 2, provides a potential tool for predicting the efficacy of AChE inhibitors prior to therapy.