Nonparametric time series summary statistics for high-frequency accelerometry data from individuals with advanced dementia.

ABSTRACT: Accelerometry data has been widely used to measure activity and the circadian rhythm of individuals across the health sciences, in particular with people with advanced dementia. Modern accelerometers can record continuous observations on a single individual for several days at a sampling frequency of the order of one hertz. Such rich and lengthy data sets provide new opportunities for statistical insight, but also pose challenges in selecting from a wide range of possible summary statistics, and how the calculation of such statistics should be optimally tuned and implemented. In this paper, we build on existing approaches, as well as propose new summary statistics, and detail how these should be implemented with high frequency accelerometry data. We test and validate our methods on an obse

SUBMITTER: Suibkitwanchai K 

PROVIDER: S-EPMC7518630 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature