Assessment of Fractal Characteristics of Locomotor Activity of Geriatric In-Patients With Alzheimer’s Dementia

There has been considerable interest in quantifying the complexity of physiologic time series, such as heart rate. However, traditional algorithms indicate higher complexity for certain pathologic processes associated with random outputs than for healthy dynamics exhibiting long-range correlations. This paradox may be due to the fact that conventional algorithms fail to account for the multiple time scales inherent in healthy physiologic dynamics. We introduce a method to calculate multiscale entropy (MSE) for complex time series. We find that MSE robustly separates healthy and pathologic groups and consistently yields higher values for simulated long-range correlated noise compared to uncorrelated noise.

Sleep-wake rhythm disturbances in patients with Alzheimer's disease (AD) make a strong demand on caregivers and are among the most important reasons for institutionalization. Several previous studies reported that the disturbances improve with increased environmental light, which, through the retinohypothalamic tract, activates the suprachiasmatic nucleus (SCN), the biological clock of the brain. The data of recently published positive and negative reports on the effect of bright light on actigraphically assessed rest-activity rhythms in demented elderly were reanalyzed using several statistical procedures. It was demonstrated that the light-induced improvement in coupling of the rest-activity rhythm to the environmental zeitgeber of bright light is better detected using nonparametric procedures. Cosinor, complex demodulation, and Lomb-Scargle periodogram-derived variables are much less sensitive to this effect because of the highly nonsinusoidal waveform of the rest-activity rhythm. Guidelines for analyses of actigraphic data are given to improve the sensitivity to treatment effects in future studies.