I need to detect plateaus in time series data online. The data I am working with represents the magnitude of acceleration of a tri-axis accelerometer. I want to find a reference time window that I can use for calibration purposes. Because of that, the system must not move and hence only gravity should influence the system.
How can I find such plateaus or is there even a more principled approach that I can take?
Why don't you use a Shewhart Control Chart (more modernly referred to as 6-sigma) with a moving variable length window to understand the process that you have.
As you find your process variability decreases markedly, by having too many results within $±1σ$ then you have a "process change" and that might be defined as a plateau. You will need to decide how many observations you require to establish a plateau.
The as you find your variability increases and your $±3σ$, you know you again have a process change and need to recalculate your limits.
I found a good solution for my problem here: https://stats.stackexchange.com/a/201315/101744
Thanks to everyone!
