What does the below phrase in the lstm blog mean? - Data Science
I think, with "series", the authors refer to time series data in their dataset. In this case, it should be x, y, z, angular velocity and maybe other features for each participant.

"Splitting data into fixed windows of 2.56 seconds (128 data points) with 50% overlap." I would translate to:
Every 2.56 seconds aggregate each series of the data over the next 5.12 seconds. 

You can imagine windowing basically as a timestamp-based data aggregation technique that is often used for stream data processing to reduce data and fix granularity of the data. The stream analytics windowing function documentation contains visualizations, which should help you to understand what is meant. I think, in the blog, the authors mean what Microsoft calls "hopping windows".

I read that windowing is a time series feature engineering topic. So maybe, it might help, if you learn more about feature engineering.