ecg200 {DATAstudio} | R Documentation |
Electrocardiogram Data
Description
The ecg
data frame has 200 rows and 97 columns. The data is the
result of monitoring electrical activity recorded during one heartbeat
and it consists of 200 ECG signals sampled at 96 time instants,
corresponding to 133 normal heartbeats and 67 myocardial infarction
signals.
Usage
ecg200
Format
The ecg200
data frame contains the following columns:
status
: status of the patient, where
1
identifies subjects with myocardial infarction signals, and0
identifies subjects with normal heartbeats.i1
toi96
-
measurements at instants
i1
toi96
; to my knowledge the exact unit of time is unknown and is not specified by Olszewski (2001), who gathered the data.
References
de Carvalho, M. and Martos, G. (2024). Uncovering sets of maximum dissimilarity on random process data. Transactions on Machine Learning Research, 5, 1-31.
Olszewski, R. T. (2001). Generalized feature extraction for structural pattern recognition in time-series data. Carnegie Mellon University, PhD thesis.
Examples
## Not run:
## de Carvalho and Martos (2024, TMLR; Fig. 4)
if (!require("dplyr")) install.packages("dplyr")
if (!require("ggplot2")) install.packages("ggplot2")
if (!require("tidyr")) install.packages("tidyr")
packages <- c("dplyr", "ggplot2", "tidyr")
sapply(packages, require, character = TRUE)
longECG <- ecg200
pivot_longer(cols = starts_with("i"), names_to = "instant",
values_to = "value")
mutate(instant = as.integer(sub("i", "", instant)))
# create scatter plot of pooled data
ggplot(longECG, aes(x = instant, y = value, color = factor(status))) +
geom_point(size = 1, alpha = 0.3) +
labs(color = "Status") +
scale_color_manual(values = c("0" = "red", "1" = "blue"),
labels = c("0" = "Non-diseased", "1" = "Diseased")) +
xlab("Time") +
ylab("ECG Signal") +
theme_minimal()
## End(Not run)