Between-day reliability of daily activity fluctuations in young adults at baseline and 6-months follow-up Connor Wicks, Nicholas Reynolds and Vivien Marmelat University of Nebraska at Omaha, Omaha, NE 68182 INTRODUCTION RESULTS The Cronbach alpha value from the ICC comparison between days during phase 1 was aICC = 0.7006 and aICC = 0.82 for phase 2. Human Daily Motor Activity (DMA) is characterized by complex temporal fluctuations presenting scale invariance1,2. DMA is estimated from a time series composed of consecutive bouts of activity recorded per-epoch from an activity monitor. Scale invariance in DMA could be used as a marker of neurological disease.3 However, it is critical to assess if the measure is consistent between consecutive days. METHODS Healthy young adults wore an activity monitor (Figure 1) on their non-dominant wrist for seven consecutive days at baseline (N=24) and after 6-months (N=19) Accelerometer data was sampled at 100 Hz and Vector Magnitude (VM) was extracted at epochs of 15 seconds. 𝑉𝑀= 𝐴𝑥𝑖𝑠 1 2+ 𝐴𝑥𝑖𝑠 2 2+ 𝐴𝑥𝑖𝑠 3 2 Figure 3: Representative data for 7 healthy young subjects of between-day reliability of DMA variability in phase one (upper) and phase 2 (lower), which takes place six months after. Each dot represents the DFA of DMA for one subject on one day. Each color represents a different subject. Figure 1: Actigraph GT9X Detrended Fluctuation Analysis4 (DFA) was used to estimate scale invariance of the ‘active’ periods (9am to 9pm) of VM series (Figure 2). DFA computes the average size of fluctuations F for every window of size n between 10 and N/4, where N is the length of the DMA time series. Any ‘zero’ number reflecting ‘non-active’ periods were removed before the application of the DFA. DISCUSSION The Cronbach alpha value above 0.7 suggests a good reliability of the DFA measures of DMA, i.e. subjects with high a-DFA on one day are likely to present high a-DFA on other days as well. Healthy elderly and PD subjects will be recruited to participate in this study, to determine the relationship between DMA variability and PD severity. The slope of F(n) as a function of n in log-log coordinates corresponds to the scaling exponent a. We calculated a from individual daily VM. Intra-class correlations (ICC) were run to test the reliability of the scaling exponent a: Between consecutive days at baseline Between consecutive days after 6-months Between the average of both 7-days periods  CONCLUSIONS The Cronbach alpha value suggest a good level of reliability in the DFA-alpha values estimated from the DMA from the Actigraph activity monitor. This validation was necessary to ensure that we could use DMA variability as a potential bio-marker of the progression of PD. REFERENCES 1. Hu K, et al. Physica A 337, 307-18, 2004. 2. Hu K, et al. Proc Natl Acad Sci 106, 2490-2494, 2009. 3. Hu K, et al. Sci Rep 6, 27742, 2016. 4. Peng CK, et al. Phys Rev E 49, 1685-1689, 1993. Figure 2: Representative example of the ‘active’ period of a VM time series (left) and corresponding DFA plot (right), for epoch lengths of 15 sec. This work was supported by the Center for Research in Human Movement Variability of University of Nebraska at Omaha, NIH (P20GM109090).