The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Entropy analysis of the EEG background activity in Alzheimer's disease patients
Open accessAbstract
Alzheimer's disease (AD) is the most common neurodegenerative disorder. Although a definite diagnosis is only possible by necropsy, a differential diagnosis with other types of dementia and with major depression should be attempted. The aim of this study was to analyse the electroencephalogram (EEG) background activity of AD patients to test the hypothesis that the regularity of the AD patients' EEG is higher than that of age-matched controls. We recorded the EEG from 19 scalp electrodes in 11 AD patients and 11 age-matched controls. Two different methods were used to estimate the regularity of the EEG background activity: spectral entropy (SpecEn) and sample entropy (SampEn). We did not find significant differences between AD patients and control subjects' EEGs with SpecEn. On the other hand, AD patients had significantly lower SampEn values than control subjects (p < 0.01) at electrodes P3, P4, O1 and O2. Our results show an increase of EEG regularity in AD patients. These findings suggest that nonlinear analysis of the EEG with SampEn could yield essential information and may contribute to increasing the insight into brain dysfunction in AD in ways which are not possible with more classical and conventional statistical methods.
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Cites
Approximate entropy as a measure of system complexity.
Pincus, S. M. (1991) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.88.6.2297 · Cited by 5,811
Mutual information analysis of the EEG in patients with Alzheimer's disease
Jeong, J., Gore, J. C., & Peterson, B. S. (2001) · Clinical Neurophysiology · doi:10.1016/s1388-2457(01)00513-2 · Cited by 397 · cited 1×
“Keywords: Alzheimer’s disease, electroencephalogram, sample entropy, spectral entropy”
Cited by
Differential entropy feature for EEG-based vigilance estimation
Shi, L.-C., Jiao, Y.-Y., & Lu, B.-L. (2013) · 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2013.6611075 · Cited by 396
Refined Composite Multiscale Dispersion Entropy and its Application to Biomedical Signals
(2017) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2017.2679136 · Cited by 319
An ensemble system for automatic sleep stage classification using single channel EEG signal
Koley, B., & Dey, D. (2012) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2012.09.012 · Cited by 291
Analysis of electroencephalograms in Alzheimer's disease patients with multiscale entropy
Escudero, J., Abásolo, D., Hornero, R., Espino, P., & López, M. (2006) · Physiological Measurement · doi:10.1088/0967-3334/27/11/004 · Cited by 264
Self-citationSong, Y., & Liò, P. (2010) · Journal of Biomedical Science and Engineering · doi:10.4236/jbise.2010.36078 · Cited by 191
Metadata
- Authors
- Abásolo, D., Hornero, R., Espino, P., Álvarez, D., & Poza, J.
- Venue
- Physiological Measurement
- Publisher
- IOP Publishing
- Published
- 2006-01-13
- Volume
- 27
- Issue
- 3
- Pages
- 241-253
- ISSN
- 0967-3334 (ISSN-L)
- 1361-6579
- OpenAlex
- W2065919594
- Cited by
- 347
- References
- 2
- FWCI
- 6.30
- Type
- journal article
- Language
- en
- Open access
- bronze
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