The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Analysis of EEG background activity in Alzheimer's disease patients with Lempel–Ziv complexity and central tendency measure
Abstract
In this study we have investigated the electroencephalogram (EEG) background activity in patients with Alzheimer's disease (AD) using non-linear analysis methods. We calculated the Lempel-Ziv (LZ) complexity - applying two different sequence conversion methods - and the central tendency measure (CTM) of the EEG in 11 AD patients and 11 age-matched control subjects. CTM quantifies the degree of variability, while LZ complexity reflects the arising rate of new patterns along with the EEG time series. We did not find significant differences between AD patients and control subjects' EEGs with CTM. On the other hand, AD patients had significantly lower LZ complexity values (p<0.01) at electrodes P3 and O1 with a two-symbol sequence conversion, and P3, P4, O1 and T5 using three symbols. Our results show a decreased complexity of EEG patterns in AD patients. In addition, we obtained 90.9% sensitivity and 72.7% specificity at O1, and 72.7% sensitivity and 90.9% specificity at P3 and P4. These findings suggest that LZ complexity may contribute to increase the insight into brain dysfunction in AD in ways which are not possible with more classical and conventional statistical methods.
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Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
Harrison's Principles of Internal Medicine.
(1988) · Annals of Internal Medicine · doi:10.7326/0003-4819-108-3-499_2 · Cited by 12,514
Determining Lyapunov exponents from a time series
Wolf, A., Swift, J. B., Swinney, H. L., & Vastano, J. A. (1985) · Physica D: Nonlinear Phenomena · doi:10.1016/0167-2789(85)90011-9 · Cited by 9,499
Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine
Zweig, M. H., & Campbell, G. (1993) · Clinical Chemistry · doi:10.1093/clinchem/39.4.561 · Cited by 6,569
Measuring the strangeness of strange attractors
Grassberger, P., & Procaccia, I. (1983) · Physica D: Nonlinear Phenomena · doi:10.1016/0167-2789(83)90298-1 · Cited by 5,650
On the Complexity of Finite Sequences
Lempel, A., & Ziv, J. (1976) · IEEE Transactions on Information Theory · doi:10.1109/tit.1976.1055501 · Cited by 2,717
Nonlinear Time Series Analysis
(2012) · SpringerReference · doi:10.1007/springerreference_205493 · Cited by 1,983
Harrison's Principles of Internal Medicine
Freeman, D. L. (2001) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.286.8.971-a · Cited by 1,624
EEG dynamics in patients with Alzheimer's disease
Jeong, J. (2004) · Clinical Neurophysiology · doi:10.1016/j.clinph.2004.01.001 · Cited by 1,337
Low-dimensional chaos in an instance of epilepsy.
Babloyantz, A., & Destexhe, A. (1986) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.83.10.3513 · Cited by 763
Cited by
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-citationTzimourta, K. D., Christou, V., Tzallas, A. T., Giannakeas, N., Astrakas, L. G., Angelidis, P., Tsalikakis, D., & Tsipouras, M. G. (2021) · International Journal of Neural Systems · doi:10.1142/s0129065721300023 · Cited by 78
Metadata
- Authors
- Abásolo, D., Hornero, R., Gómez, C., García, M., & López, M.
- Venue
- Medical Engineering & Physics
- Publisher
- IOP Publishing
- Published
- 2005-08-24
- Volume
- 28
- Issue
- 4
- Pages
- 315-322
- ISSN
- 1350-4533 (ISSN-L)
- 1873-4030
- OpenAlex
- W2129613547
- Cited by
- 313
- References
- 39
- FWCI
- 4.82
- Type
- journal article
- Language
- en
- Open access
- closed
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- Abásolo, D., Hornero, R., Gómez, C., García, M., & López, M. (2006). Analysis of EEG background activity in Alzheimer's disease patients with Lempel–Ziv complexity and central tendency measure. Medical Engineering & Physics. https://doi.org/10.1016/j.medengphy.2005.07.004
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