Expert and crowd-sourced validation of an individualized sleep spindle detection method employing complex demodulation and individualized normalization.

ABSTRACT: A spindle detection method was developed that: (1) extracts the signal of interest (i.e., spindle-related phasic changes in sigma) relative to ongoing "background" sigma activity using complex demodulation, (2) accounts for variations of spindle characteristics across the night, scalp derivations and between individuals, and (3) employs a minimum number of sometimes arbitrary, user-defined parameters. Complex demodulation was used to extract instantaneous power in the spindle band. To account for intra- and inter-individual differences, the signal was z-score transformed using a 60 s sliding window, per channel, over the course of the recording. Spindle events were detected with a z-score threshold corresponding to a low probability (e.g., 99th percentile). Spindle characteristics, such as

SUBMITTER: Ray LB 

PROVIDER: S-EPMC4585171 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature