fft.harmonic

<p>the trelliscope data frame containing two variables: subject ID and activity</p>

<p>Take FFT input and reorganize it showing top significant frequencies.</p>

internal

Penalized Multi-Band Learning algorithm can be effectively implemented for circadian rhythm analysis and daily activity pattern characterization using actigraphy (continuously measured objective physical activity data). Functions for interactive visualization of actigraph data are also included. Method reference: Li, X., Kane, M., Zhang, Y., Sun, W., Song, Y., Dong, S., Lin, Q., Zhu, Q., Jiang, F., Zhao, H. (2019) A Novel Penalized Multi-band Learning Approach Characterizes the Consolidation of Sleep-Wake Circadian Rhythms During Early Childhood Development.

Xinyue Li

fft.harmonic: FFT auxillary function

Description

Usage

Arguments

Value