Juggluco
- let you export continuous glucose monitoring values. Here I describe how
- you can use these data to generate a picture of you glucose percentiles
- with the R package Iglu.
-
First you have to save
- your streaming data. In Juggluco for Android you can select Export from
- the left middle menu and press Stream to save it in some file. You need to
- save in mg/dL so before you save it you should set mg/dL in Settings. The
- resulting graph is also in mg/dL. This file you can then transfer to you
- computer.
-
You can also run cmdline
- juggluco on you computer. Setting it to receive glucose values via IP/TCP
- connection by selecting Mirror in the left middle menu and adding a
- connection with you computers' IP and Stream checked. On you computer you
- press
-
juggluco -ra
- Set unit to mg/dL:
-
juggluco -G
- Make it a receiver and run in the background by pressing:
-
juggluco&
-
If the data are
- transferred to the computer, you can press
First you have to
- install the statistics computing language R and preferentially Rstudio
- which are both freely available on the web. The only drawback is that the
- installation takes a lot of time.
-
Under ubuntu (which also
- runs under Windows 10), you can press
Use for directory the
- full name of your current directory, for stream.tsv the file you have your
- stream data in and for 3MH0042XDKM the name of the sensor you want to
- show.
cgmdata<-data.frame(streamdata$Sensorid,as.POSIXct(streamdata$UnixTime, origin="1970-01-01"),streamdata$mg.dL)
-colnames(cgmdata)[1]<-"id"
-colnames(cgmdata)[2]<-"time"
-colnames(cgmdata)[3]<-"gl"
- unique(cgmdata$id) # to see the sensor id's
-agp(dplyr::filter(cgmdata,id=="3MH0042XDKM")) # display one particular sensor
-
If you want the analyze a period that is not restricted to a single
- sensor, you can do the following:
Juggluco
+let you export continuous glucose monitoring values. Here I describe
+how you can use these data to generate a picture of you glucose
+percentiles with the R
+package Iglu.
+
First you have to
+save your streaming data. In Juggluco for Android you can select
+Export from the left middle menu and press Stream to save it in some
+file. You need to save in mg/dL so before you save it you should set
+mg/dL in Settings. The resulting graph is also in mg/dL. This file
+you can then transfer to your computer.
First you have to
+install the statistics computing language R and preferentially
+Rstudio which are both freely available on the web. The only drawback
+is that the installation takes a lot of time.
+
+
Under ubuntu
+(which also runs under Windows 10), you can press
+Use for directory the full name of your current directory, for
+stream.tsv the file you have your stream data in and for 3MH0042XDKM
+the name of the sensor you want to show.
+
setwd("directory")
+streamdata<-read.csv("stream.tsv",header=TRUE,sep='\t');
+cgmdata<-data.frame(streamdata$Sensorid,as.POSIXct(streamdata$UnixTime, origin="1970-01-01"),streamdata$mg.dL)
+colnames(cgmdata)[1]<-"id"
+colnames(cgmdata)[2]<-"time"
+colnames(cgmdata)[3]<-"gl"
+unique(cgmdata$id) # to see the sensor id's
+agp(dplyr::filter(cgmdata,id=="3MH0042XDKM")) # display one particular sensor
+If you want the analyze a period that is not restricted to a single
+sensor, you can do the following:
Replace 2021-01-26 with the start date and 2021-02-26 with the end date.
-
-
Later you can put the
- above in file and run it by opening it in rstudio, select everything and
- press run. To see the display, press on the plots penal at the right side.
- Resize it so everything is visible and save it with export. You can also
- cut and past to command line R, but adjusting the size of the image is
- then more difficult.
-
- History
- data. Not scanned often enough for full data. Misses a lot of hypo's
- also because the history data are less extream as the scans and stream
-
-
- Bluetooth
- stream. 10% hypoglycemia, instead of the 4% shown in the history data
-
-
-
+agp(dplyr::filter(cgmdata2,time>="2021-01-26"&time<"2021-02-26"))
+Replace 2021-01-26 with the start date and 2021-02-26 with the end
+date.
+
+
Later you can put
+the above in file and run it by opening it in rstudio, select
+everything and press run. To see the display, press on the plots
+penal at the right side. Resize it so everything is visible and save
+it with export. You can also cut and past to command line R, but
+adjusting the size of the image is then more difficult.
+
+
+History data. Not scanned often enough
+for full data. Misses a lot of hypo's also because the history data
+are less extream as the scans and stream
+
+
+Bluetooth stream. 10% hypoglycemia,
+instead of the 4% shown in the history data
+
- 
-