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Introductory journey through OpenSignals, explaining/demonstrating how signals can be acquired in real-time.
The importance of choosing a proper sampling frequency, resolution is another parameter that must be configured prior to acquisition.
In the following steps it will be demonstrated how the sampling rate choice affect signal morphology.
In the current Jupyter Notebook it will be demonstrated how the user can store in a file the previously acquired signals.
It will be explained how to load/transpose the data inside .h5 file to a Python list, that can easily be manipulated in the processing operations.
In the current Jupyter Notebook we continue the interaction with OpenSignals , demonstrating how the previously acquired/stored files can be loaded.
In this Jupyter Notebook it will be explained how to load/transpose the data inside .txt file to a Python list, which consists in a step that precedes all processing operations.
In the current Jupyter Notebook a detailed procedure for accessing file metadata (.txt and .h5) is explained, together with a simplified approach through the use of a biosignalsnotebooks specialized function.