Convert time series data to supervised learning problem

I have a similar dataset like the one below. Each row represents a person and there are 3 different variables m1,m2,m3 with 3 measurements each.
I am trying to frame this time series problem as a supervised learning problem so i can train an SVM and/or random forest.

My idea would be to reshape the data like this: Note that I only did for the first row on the dataset above

Basically, if there are 3 measurements per variable, I’d have 3 rows to reflect this information.

Am I going in the right direction with this approach? If not, could you point me to the right direction?

Thank you for taking your time in advance.