Neural Network Sensordata as Input
Correct me if I'm wrong: As far as I understood, you have files of 1000 entries with 19 numerical sensor values and a type of 22 movements in each line.
You would like to predict the type of movement based on the sensor values.

Are the entries being recorded in a fixed interval?
If so, you could use an RNN.

Either way, it seems to be a classification problem. You can find a tutorial for Tensorflow here.

You can read data from csv files with pandas.read_csv.

As for the encoding of your data: If the types of movement cannot be sorted and are not related to each other, you should use one-hot encoding to present the type of movement to the NN. You can keep numerical sensor data as is, just make sure to normalize it.