Abstract

AbstractBackgroundDementia with Lewy bodies (DLB) and Alzheimer’s disease (AD) are challenging to differentiate. Mobile health devices that measure motor and sleep domains between clinic visits may improve differential diagnosis.MethodParticipants with probable AD and probable DLB wore ActiGraph triaxial wGT3X‐BT actigraphy devices on their nondominant wrists for 2 weeks and multichannel Sleep ProfilerX8TM EEG devices on their foreheads for 2 consecutive nights.3 Actigraphy data were processed and scored using GGIR and activity counts in R. The Sleep Profiler characterizes abnormal slow‐wave sleep and non‐REM hypertonia (NRH).ResultAt baseline, participants with DLB (n = 9) had higher UPDRS scores and a higher likelihood of psychosis than participants with AD (n = 8; see Table 1). Using univariate Wilcoxon Rank‐Sum tests, we found that at baseline participants with DLB had lower daily activity counts, higher % time in NRH, and lower % time in REM sleep than participants with AD (unadjusted p‐values < 0.05; See Figure 1). In a recent 6‐month followup, activity levels were lower on average than baseline activity levels for both DLB (n = 5) and AD (n = 5). at 6‐months, the differences in % sleep in NRH increased between DLB participants (n = 5) and AD participants (n = 3) as average % NRH increase 6% in DLB and decreased 1% in AD (see Table 2). These 6‐month differences are not statistically significant, but data collection are ongoing. An exploration of methods for processing and scoring actigraphy data revealed that processing can result in wide range of findings. As a result, we have focused on actigraphy outcomes which are more suitable to older participants with dementia.ConclusionParticipants with DLB demonstrated lower baseline physical activity and higher rates of baseline sleep disturbances than participants with AD; sleep differences between DLB and AD appeared to increase over 6 months. Actigraphy and sleep‐monitoring devices are well tolerated in participants with dementia and they can reliably collect valid, useful activity and sleep data in between clinic visits.

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