diff --git a/README.md b/README.md
index 4045ae3..9054a57 100644
--- a/README.md
+++ b/README.md
@@ -1,12 +1,27 @@
-In this folder you can find 4 scripts that can be used to transfrom 24/7 .cwa accelerometer data to intensity plots. The methods are based on the Rowland et al. 2018 article 'Beyond Cut Points: Accelerometer Metrics that Capture the Physical Activity Profile. 
+In this folder you can find 4 scripts that can be used to transfrom 24/7 .csv accelerometer data to intensity plots. The methods are based on the Rowland et al. 2018 article 'Beyond Cut Points: Accelerometer Metrics that Capture the Physical Activity Profile. 
 
 The scripts should be run in the following order:
 
-1. DailyCutter.py   -   ...
+1. DailyCutter.py   -   This script is used to transform single week .csv files (input) into individual day-files (output)
+                        The WeekPath should be set to the folder containing the week-files of the patient 
+                        The ScriptPath should be set to the folder containing the 'formules.py' script. This script holds
+                        all functions used in the analysis.
+
+2. plotter.py       -   This is the second script used in the analysis and is the script that performs the most. 
+                        Before getting started, the os.chdir(___) should be set to the 'formules.py' pathway
+                        The rootdir should be set to the folder containing 7 individual .csv day-files
+                        The PtName variable should be set accordingly to the name of the files used. This possibly changes 
+                        between different weeks/different patients.
+                        Finally, the CheckWeel.to_csv(___) should be filled with the used weeknumber, to save the 
+                        parameters of the trendline for each different week.
+                        After changing these variables to your liking, the script should run automatically, using the 
+                        folder with individual days as input and saving the plots for individual days as well as an 
+                        overview of the entire week as output.
+
+3. Totalplotter.py  -   After running the plotter.py script you should have ended up with 6 .csv files with parameters 
+                        of the trendlines. Make sure that these files are saved within the same folder and set the path
+                        of this folder as the rootdir in this script.
+                        Change the names in the plt.title(___) and plt.savefig(___) commands accordingly and run the scripts
+                        The output will be a plot of all 6 weeks in one figure.
 
 
-2. plotter.py       -   ...
-
-
-3. Totalplotter.py  -   ...     
-