1. Characteristic time scales of electroencephalograms of narcoleptic patients and healthy controls
- Author
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Do-Un Jeong, Byunghun Choi, Eui-Joong Kim, Hong-Beom Shin, Young-Jin Koo, Jong Won Kim, and Kwang Suk Park
- Subjects
Adult ,Male ,medicine.medical_specialty ,Adolescent ,business.industry ,Models, Neurological ,Healthy subjects ,Electroencephalography ,Signal Processing, Computer-Assisted ,Health Informatics ,Audiology ,medicine.disease ,Statistics, Nonparametric ,Computer Science Applications ,Case-Control Studies ,Statistics ,medicine ,Detrended fluctuation analysis ,Humans ,Female ,business ,Algorithms ,Narcolepsy ,Slow-wave sleep - Abstract
Sleep electroencephalograms (EEGs) typically showed correlated fluctuations that became random-like oscillations beyond a characteristic time scale. To investigate this behavior quantitatively, the detrended fluctuation analysis (DFA) was applied to EEGs of 10 narcoleptic patients (22.0 ± 4.0 yrs; 6 males) and 8 healthy controls (24.0 ± 2.0 yrs; 5 males). The characteristic time scales of the narcoleptics and controls were estimated as 1.8 ± 0.7 and 4.4 ± 1.2s, respectively (significance level, p0.01). We further performed DFA of the EEGs segmented into 30s epochs and found that the DFA scaling exponents increased in deep sleep stages. These results were verified with power spectrum and auto-correlation analysis, and reproduced by a mathematical model. We thus concluded that characteristics of EEGs of narcoleptic patients could be differentiated from those of healthy subjects, suggesting a potential application of DFA in diagnosing narcolepsy.
- Published
- 2010
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