In personalscience/cgmr: Continuous Glucose Monitor Data Analysis

knitr::opts_chunk$set(echo = TRUE)

Continuous Glucose Monitoring Package for R

Process raw CGM data from Freestyle Libreview, Levels, Nutrisense and others.

Prerequisites

Download a CSV file from Libreview.com

library(tidyverse)
library(lubridate)
library(cgmr)

cgm_sample <- glucose_df_from_libreview_csv(system.file("extdata", package = "cgmr", "Firstname1Lastname1_glucose.csv"))

glucose_records <- cgm_sample 
notes_records <- notes_df_from_glucose_table(glucose_records)

head(glucose_records)

head(notes_records)

The most important function, food_times_df_fast() looks through all glucose and notes records to return a dataframe of times during a time interval after eating a specific food, in this case "Keto Bar", which the CGM wearer entered in the Notes field of the app.

ft <- food_times_df_fast(glucose_records, notes_records, foodname = "keto bar")

ft

And of course you can easily plot the results

ft %>% ggplot(aes(x=t, y = value, color = meal)) + geom_line()

personalscience/cgmr documentation built on July 2, 2023, 12:47 a.m.