Calculate cumulated elevation gain for physical activities recorded by GoogleFit
oliviermirat opened this issue · comments
To solve this issue, you will need to use the solution proposed in issue #20 to get the elevation from GPS coordinates.
The aim is to calculate the cumulated elevation gain for physical activities recorded by Google Fit for Participant 1 and Participant 2.
For Participant 1, you can find the data here: https://github.com/oliviermirat/MyAIGuide/blob/master/data/raw/ParticipantData/Participant1PublicOM/GoogleFitData
For Participant 2, the data is in the confidential repo.
(for both participants, the "Activité"/"Activitie" folders seem to have the most information)
On it!
Could you clarify what the following columns measure inside the GoogleFit data:
- 'Basse latitude (°)', 'Basse longitude (°)', 'Haute latitude (°)', 'Haute longitude (°)',
- 'Poids moyen (kg)', 'Poids maximal (kg)', 'Poids minimal (kg)',
- 'Durée de l'activité "Marche à pied" (ms)', 'Durée de l'activité "Course à pied" (ms)'
Cheers :)
This would translate to:
- 'Low Latitude', 'Low Longitude", 'High Latitude', 'High Longitude'
- 'Mean Weight", "Maximum Weight', 'Minimum Weight'
- 'Duration of the activity "Walk', 'Duration of the activity 'Running'
I'm not sure what the "low" and "high" mean for the "latitude" and "longitude", but there's probably some logic behind that.
For Participant 1, it's in French for smartphone 1, and in English for smartphone 2. For Participant 2, it think it should all be in English.
Thanks a lot :)
Thanks!
I do wonder what high and low lat long mean. Does it refer to the location of highest and lowest elevation during the exercise? Because that would be very useful for calculating elevation changes.
I'm just noticing now that you're looking at the dailyAggregation subfolder: in those csv files, the high and low might refer to the beginning and end of the period represented in that line of the csv file, or something like that.
But I was thinking that the Activités subfolder might contain more precise information. But I'm not sure, some investigation is needed here.
How do we define cumulated elevation gain?
Wikipedia gives a nice definition of cumulated elevation gain: https://en.wikipedia.org/wiki/Cumulative_elevation_gain . Let me know if it doesn't make sense.
turns out that a coord to elevation function is not even needed for this issue, as the raw data contains elevation information.
I think this issue is solved. We know have a function that takes a folder containing .tcx files and the master dataframe and it updates the dataframe with (daily) elevation gains/losses and calories due to GoogleFit exercises.