g.applymetrics: Extract metrics from acceleration signals

View source: R/g.applymetrics.R

g.applymetricsR Documentation

Extract metrics from acceleration signals

Description

Function to extract metrics from acceleration signal. Not intended for direct use by user

Usage

  g.applymetrics(data, sf, ws3, metrics2do,
                          n = 4, lb = 0.2, hb = 15,
                          zc.lb = 0.25, zc.hb = 3, 
                          zc.sb = 0.01, zc.order = 2,
                          actilife_LFE = FALSE)

Arguments

data

Three column matrix with x, y, and z acceleration data

n

filter order, see GGIR for details

sf

sample frequency

ws3

Epoch size in seconds

metrics2do

Dataframe with Boolean indicator for all metrics whether they should be extracted or not. For instance, metrics2do$do.bfen = TRUE, indicates that the bfen metric should be extracted

lb

Lower boundery of cut-off frequencies, see GGIR.

hb

Higher boundery of cut-off frequencies, see GGIR.

zc.lb

See GGIR

zc.hb

See GGIR

zc.sb

See GGIR

zc.order

See GGIR

actilife_LFE

See GGIR

Value

Dataframe with metric values in columns average per epoch (ws3)

Author(s)

Vincent T van Hees <v.vanhees@accelting.com>

Examples

  Gx = runif(n=10000,min=0,max=2)
  Gy = runif(n=10000,min=1,max=3)
  Gz = runif(n=10000,min=0,max=2)
  data = cbind(Gx, Gy, Gz)
  metrics2do = data.frame(do.bfen=TRUE,do.enmo=TRUE,do.lfenmo=FALSE,
  do.en=FALSE,do.hfen=FALSE,do.hfenplus=FALSE,do.mad=FALSE,do.anglex=FALSE,
  do.angley=FALSE,do.anglez=FALSE,do.roll_med_acc_x=FALSE,
  do.roll_med_acc_y=FALSE,do.roll_med_acc_z=FALSE,
  do.dev_roll_med_acc_x=FALSE,do.dev_roll_med_acc_y=FALSE,
  do.dev_roll_med_acc_z=FALSE,do.enmoa=FALSE,
  do.lfx=FALSE, do.lfy=FALSE, do.lfz=FALSE, 
  do.hfx=FALSE, do.hfy=FALSE, do.hfz=FALSE, 
  do.bfx=FALSE, do.bfy=FALSE, do.bfz=FALSE,
  do.zcx=FALSE, do.zcy=FALSE, do.zcz=FALSE, 
  do.brondcounts=FALSE, do.neishabouricounts=FALSE)
  
  extractedmetrics = g.applymetrics(data,n=4,sf=40,ws3=5,metrics2do)

GGIR documentation built on Oct. 17, 2023, 1:12 a.m.