I got myself a Garmin watch at the beginning of the year, to collect various metrics automatically. The watch uses the built in heart rate monitor/sensors to de

I got myself a Garmin watch at the beginning of the year, to collect various metrics automatically. The watch uses the built in heart rate monitor/sensors to derive various data specifically: - sleep hours (including the sleep phase type: deep sleep etc) - stress amounts (via heart rate variability) - energy levels ("Body battery" in Garmin speak) I've been feeling quite drained the last couple of weeks so I wanted to see if the data I've collected over the last 3 months or so would match what I was subjectively feeling. Interestingly Garmin does not provide any functionality to analyze long term trends, but there's an open source project to extract data from Garmin [0]. I used the tool to generate some graphs [1] that, do indeed, seem to indicate a rising level of stress over the last few months. I'm going to try the moving average next to see if it's better than the naive approach I used, but ultimately my goal is the same as author's. I want a warning to sound off based on sleep/stress/energy levels trends. I have a tendency to overdo things sometimes. My theory is that a day off taken before some critical level is better than a week off after the burn out. Here's the PR with the Jupyter notebook that generates the graph in the link based on Garmin Data [2]. [0] https://github.com/tcgoetz/GarminDB https://github.com/tcgoetz/GarminDB [1] https://imgur.com/a/Q7MJqMB https://imgur.com/a/Q7MJqMB [2] https://github.com/tcgoetz/GarminDB/pull/155 https://github.com/tcgoetz/GarminDB/pull/155