Potential dementia biomarkers based on the time-varying microstructure of sleep EEG spindles.
The time-varying microstructure of sleep EEG spindles may have clinical significance in dementia studies. In this work, the sleep spindle is modeled as an AM-FM signal and parameterized in terms of six parameters, three quantifying the instantaneous envelope (IE) and three quantifying the instantaneous frequency (IF) of the spindle model. The IE and IF waveforms of sleep spindles from patients with dementia and normal controls were estimated using the time-frequency technique of Complex Demodulation (CD). Sinusoidal curve-fitting using a matching pursuit (MP) approach was applied to the IE and IF waveforms for the estimation of the six model parameters. Specific differences were found in sleep spindle instantaneous frequency dynamics between spindles from dementia subjects and spindles from controls.
Ktonas
P Y
PY
Sleep Research Unit, Department of Psychiatry, National Kapodistrian University of Athens, Greece.
Golemati
S
S
Xanthopoulos
P
P
Sakkalis
V
V
Ortigueira
M D
MD
Tsekou
H
H
Zervakis
M
M
Paparrigopoulos
T
T
Soldatos
C R
CR
D000465:Algorithms; D015415:Biomarkers / Q000737:chemistry*; D001931:Brain Mapping; D003704:Dementia / Q000175:diagnosis* / Q000628:therapy*; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods; D004867:Equipment Design; D006801:Humans; D015233:Models, Statistical; D008962:Models, Theoretical; D017286:Polysomnography / Q000295:instrumentation* / Q000379:methods; D012815:Signal Processing, Computer-Assisted; D012890:Sleep; D012894:Sleep Stages; D013997:Time Factors
D015415:Biomarkers