An Introduction to Garmin Connect
For those who use the Garmin Connect Dashboard (https://connect.garmin.com), to synchronize their Garmin fitness devices, there is a fairly straightforward method for downloading higher-frequency data from the workout relative to heart rate, distance and GPS location that can be directly imported into Microsoft Excel for further analysis.
Getting Started with the Download
From inside of Garmin Connect (Figure 1), select a specific activity. In this example, I am picking my latest rowing workout, shown by the red arrow.
Once you have selected the specific workout, click on it and this will take you to the details of that workout. Once there, navigate over to the gear on the right-hand side, as shown by the red arrow.
The drop-down box from the arrow shows a number of export options. Select “Export to TCX”, shown by red arrow in Figure 3.
Upon selection, the file will be downloaded, as shown in Figure 4. On a Windows platform, this will be downloaded by default to the user’s downloads folder.
Once the file is downloaded, go to the file directory and locate the file you just downloaded, as shown in Figure 5.
Then, change the suffix from .TCX to .XML, as shown in Figure 6. Accept the change when prompted.
Now, open Microsoft Excel. Select the Data tab, as shown in Figure 7.
On the left-hand side, select Get External Data “From Other Sources”, and scroll down to “From XML Data Import”, as shown in Figure 8.
A dialog box will open. Navigate to your newly-created XML file. Select it, and click the series of “OK” buttons in the dialogs that come up, including the one placing the location of the start in cell $A$1. Once completed, the contents of the file will be imported into your spreadsheet. Heart rate data will be contained in column O, as shown in Figure 9. Distance & speed are contained in columns M & N, respectively. GPS latitude & longitude are contained in columns P & Q, respectively. Average speed is contained in column R.
In my next post on the subject I will describe how to manipulate these data for further analysis.