Learn to Work with Next Gen. Neurotech Data ‘fNIRS’ with this Easy Tutorial

This post explains how to get started with fNIRS sensing data specifically oxygenated hemoglobin “HbO2/HbO” data for analyzing a data stream from a sensor, in this case Blueberry.

The goal here is to help with understanding how to take the sensor data signal and get to a point where clear increases and decreases in thinking intensity are shown during a period of use. In this tutorial we will use a sample dataset to start with.

In this post we explore two core concepts with fNIRS data:

1. Experiments to determine a clean ‘brain activity’ signal
2. Comparing ‘brain activity’ with a secondary source of data, typing speed

The image below shows the ideal change in HbO2 blood oxygenation for an intensity of thought increase.

If you want to learn more about fNIRS you can read about it here.

Thanks to python and scikit learn this can be done quite fast! This tutorial walks you through an open source Jupyter notebook and a few methods to get started. Find the Github public repo here.

7 Steps to Get to an Estimated Brain Activity Signal

Steps 1–6 Filtration and initial brain activity signal…