I average 20,000 steps a day.
I'm sitting here in a meeting at 3:20 pm and I only have 3,500 steps for the day. Today has been meeting hell, and this is my fourth meeting of the day. No walking around. This is driving me nuts.
Yes, I've joined the fitness tracker movement. I wouldn't normally post this on here, as it's not related to data science. Except, because of who I am, I'm making it related to data science.
I've noticed a few trends relationships in my activity data:
- I am least active on the days following a long run or other hard workout, and I had really never realized how significant that is before.
- I am sometimes EXTREMELY inactive in the office. Especially on days when I have a lot of meetings.
These observations made me think, could I use data to predict my activity level on a daily or even hourly basis?
So, I did what I do with these things. I've setup a MySQL database to track my fitness tracker data over time, along with other factors (meeting data, weight, workout plans, etc) to try to do time-series analysis on my activity level.
I'm hoping to come up with some decent, informative models, that I can use to think about my activity level. Additionally, leave a comment on this blog there's any additional factors or interesting components I should look at in my data. I'll post my models on here from time to time.
This brings me to a product idea. If I can successfully create models to predict periods of inactivity, can I create an alert based on that prediction, to nag myself into activity during that time? I don't know if it could work for the masses, but at least I could try to guilt my self into action.
And, for all of you device nerds out there, I'm currently using Google Fit on my Nexus phone, but I'm looking at getting a Garmin tracker.
Stay tuned for more on this project...