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Introducing Biosignals Notebooks

Introducing Biosignals Notebooks

Learn signal processing techniques in a step by step methodology
supported by Jupyter NotebookPython and PLUX devices.

Researchers are explorers, generating new questions and searching for answers in a constant fight against the unknown.
However, research work should not be a solo journey and new knowledge can only be achieved when supported by the mastery of past discoveries.
Knowing the secrets of human body and physiology is probably one of the most fascinating scientific objectives. Indeed, our body is an amazing source of information, which can be accessed through 1) dedicated sensors and devices (hardware) together with 2) software tools/functionalities.
PLUX recently made software tools/functionalities even more accessible to you with biosignalsnotebooks.
biosignalsnotebooks is our newest collection of interactive and tutorial-like code samples with the purpose to help students and researchers interested in recording, processing, and classifying biosignals using Python.
 
Go to Biosignals Notebooks | plux.info
Go to Biosignals Notebooks | GitHub
 
With this resource, PLUX provides to his users a way to start an amazing journey into physiological signal processing methodologies.
The examples are set on a level of complexity covering and guiding through topics for beginners (e.g. How to load data from a .TXT file?) up to biosignals experts (e.g. Fatigue Evaluation using data collected with EMG sensor).
biosignalsnotebooks are freeopen-source, and classified in different difficulty levels, making it easy to be integrated into biosignal based education programs.
Visit the biosignalsnotebooks website for more information and subscribe to the new mailing to be notified when new notebooks are published.
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