I have xyz axis for gyro and accelerometer data, and i want to detect between whether the travel path was circular or square
Have not tried anything, want initial ideas
The way I would approach this would be:
First compute some characteristics about my data such as:

centroid of my points
max distance between two points
...

Then create reference shapes with that data, for example a circle with its center being the computed centroid of my points, and its diameter being the max distance,...
Then try to find how close to each reference shape is every point in my path to compute the standard deviation between each reference shape and my path. This might be more or less difficult depending on how complicated your reference shapes are.
Finally I would just pick the shape with the smallest standard deviation.
This might not be very optimal though, since it involves quite a lot of computation, especially if you have a lot of point in your path.
How can i distinguish between square and circular shapes from accelerometer and gyroscope sensor data using python?