0948 An Iterated Function System Implemented on a Python Application as a Tool to Detect Dementia and Mild Cognitive Impairment During Rapid Eye Movement Sleep and Rest

Introduction In time series, brown noise by means of the Detrended Fluctuation Analysis in Mild Cognitive Impaired (MCI) subjects during the NREM to REM sleep transition has been reported, so an application that may show different colors of noise of MCI, demented or normal Older Adults (OAs) was tested during REM sleep and wakefulness. To achieve this purpose, a Python application with an Iterated Function System (IFS) approach was created as it is known that an IFS emphasizes the fractal behavior of the series. The IFS is a generalization of the Chaos Game and the shape resulting from the set of points can have fractal characteristics. Methods 18 OAs (66 ± 6; 11 ± 4 years of education) were registered during the whole night and/or rest conditions. A Mexican test to measure cognitive performance (Neuropsi, 98.1 ± 20) and the Mini-Mental State Examination (MMSE, 27 ± 4) were used to detect dementia, MCI, or normal cognitive functions (CTRLs). An IFS was built by selecting vertices from a circle (an n-gon with a large enough n) based on the values of the time series. Results During REM sleep and rest conditions, brown noise was present in OAs with dementia or MCI; pink noise was shown in CTRLs; whereas EMG signals followed white noise. The figures in the circles were drawn related to the color of noise: the fan-shaped circle was related to white noise, pink noise was sickle-shaped whereas brown noise followed the perimeter of the circle. Conclusion The IFS method was useful to distinguish dementia and MCI from normality. Support (If Any) GV-T (CONACyT, 416939); the Cátedras-CONACyT Program supported CIM-A and AR-L.