Looking for some time-series data transformation advice!
I want to know what's the best way to transform data of 9-tuples time series data of IMU (Inertia Measurement Unit) sensor, recorded from a pen drawing a straight line in 2D space into the equation that describes the direction of the pen.
Basically I'm looking for a function/algorithm that maps a 9-axes time-series data into a linear combination in the form of aX + bY + cZ, in order to know which direction the pen is moving on a 2D plane (c = 0). Note that I can label all data, hence a supervised algorithm is possible, but not necessary.
The IMU data are 9-tuple time-series data in the form of:
3 axes of linear acceleration (collected from the accelerometer)
3 axes of angular velocity (collected from the gyroscope)
3 axes of magnetic field strength (collected from the magnetometer)
Which methods should I use? How should I transform the data before modeling?
Any tip or advice would be highly appreciated. Thanks ahead! 🙂