A clinical observational study to verify the feasibility of WARMIE sensor in continuous skin temperature monitoring in surgical patients.
Continuous temperature monitoring has been previously described to provide many diagnostic benefits over standard temperature point-measurements.
Validation of clinical feasibility of using WARMIE Sensor in an inpatient-care environment. We aimed to verify the ease of use, reliability, comfort, and correctness of the continuous skin temperature monitoring device.
This repository contains the data and code for our paper:
Francuzik et al., (2021). WTM2020: Validation of a continous skin temperature monitor - WARMIE sensor. Name of journal/book https://doi.org/xxx/xxx
Please cite this compendium as:
Francuzik et al., (2023). Compendium of R code and data for WTM2020: Validation of a continous skin temperature monitor - WARMIE sensor. Accessed 01 Dez 2023. Online at https://doi.org/xxx/xxx
- The folder
1_data_cleaning
contains scripts and a final database used in subsequent data analysis (This can either be an Rmd file or a R script). - Exploratory data analysis is stored in the
2_EDA
folder (this should be a .Rmd file). - All exported objects from the EDA steps, as well as derived data, are
stored in the
analysis/data/derived_data
folder - All other R scripts are going to be stored in the R folder
The analysis directory contains:
- 📁 paper: R Markdown source document for
manuscript. Includes code to reproduce the figures and tables
generated by the analysis. It also has a rendered version,
paper.docx
, suitable for reading (the code is replaced by figures and tables in this file) - 📁 data: Data used in the analysis.
- 📁 figures: Plots and other illustrations
- 📁 supplementary-materials: Supplementary materials including notes and other documents prepared and collected during the analysis.
This research compendium has been developed using the statistical programming language R. To work with the compendium, you will need installed on your computer the R software itself and optionally RStudio Desktop.
The simplest way to explore the text, code and data is to click on binder to open an instance of RStudio in your browser, which will have the compendium files ready to work with. Binder uses rocker-project.org Docker images to ensure a consistent and reproducible computational environment. These Docker images can also be used locally.
You can download the compendium as a zip from from this URL:
master.zip. After unzipping: - open the .Rproj
file in RStudio - run devtools::install()
to ensure you have the
packages this analysis depends on (also listed in the
DESCRIPTION file). - finally, open
analysis/paper/paper.Rmd
and knit to produce the paper.docx
, or run
rmarkdown::render("analysis/paper/paper.Rmd")
in the R console
Text and figures : CC-BY-4.0
Code : See the DESCRIPTION file
Data : CC-BY-4.0 attribution requested in reuse
We welcome contributions from everyone. Before you get started, please see our contributor guidelines. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.