BabySS {wavethresh} | R Documentation

## Physiological data time series.

### Description

Two linked medical time series containing 2048 observations sampled every 16 seconds recorded from 21:17:59 to 06:27:18. Both these time series were recorded from the same 66 day old infant by Prof. Peter Fleming, Dr Andrew Sawczenko and Jeanine Young of the Institute of Child Health, Royal Hospital for Sick Children, Bristol. `BabyECG`, is a record of the infant's heart rate (in beats per minute). `BabySS` is a record of the infant's sleep state on a scale of 1 to 4 as determined by a trained expert monitoring EEG (brain) and EOG (eye-movement). The sleep state codes are 1=quiet sleep, 2=between quiet and active sleep, 3=active sleep, 4=awake.

### Format

The `BabyECG` time series is a nice example of a non-stationary time series whose spectral (time-scale) properties vary over time. The function `ewspec` can be used to anaylse this time series to inspect the variation in the power of the series over time and scales.

The `BabySS` time series is a useful independent time series that can be associated with changing power in the `BabyECG` series. See the discussion in Nason, von Sachs and Kroisandt.

### RELEASE

Version 3.9 Copyright Guy Nason 1998

### SEE ALSO

`ewspec`

### EXAMPLES

#

# Plot the BabyECG data with BabySS overlaid

#

# Note the following code does some clever scaling to get the two

# time series overlaid.

#

myhrs <- c(22, 23, 24, 25, 26, 27, 28, 29, 30)

mylab <- c("22", "23", "00", "01", "02", "03", "04", "05", "06")

initsecs <- 59 + 60 * (17 + 60 * 21)

mysecs <- (myhrs * 3600)

secsat <- (mysecs - initsecs)/16

mxy <- max(BabyECG)

mny <- min(BabyECG)

ro <- range(BabySS)

no <- ((mxy - mny) * (BabySS - ro[1]))/(ro[2] - ro[1]) + mny

rc <- 0:4

nc <- ((mxy - mny) * (rc - ro[1]))/(ro[2] - ro[1]) + mny

plot(1:length(BabyECG), BabyECG, xaxt = "n", type = "l", xlab =

"Time (hours)", ylab = "Heart rate (beats per minute)")

lines(1:length(BabyECG), no, lty = 3)

axis(1, at = secsat, labels = mylab)

axis(4, at = nc, labels = as.character(rc))

#

# Sleep state is the right hand axis

# #

### Source

Institute of Child Health, Royal Hospital for Sick Children, Bristol.

### References

Nason, G.P., von Sachs, R. and Kroisandt, G. (1998). Wavelet processes and adaptive estimation of the evolutionary wavelet spectrum. Technical Report, Department of Mathematics University of Bristol/ Fachbereich Mathematik, Kaiserslautern.

[Package wavethresh version 4.0-2 Index]