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Minicourse EDTH-JA19

AI-driven methods for the interpretable analysis of fNIRS signals in Python

Javier Andreu-Perez

with Javier Fumanal-Idocin

About this course

In this mini-course, we will present a toolbox that permits the use of AI-powered data analytics methods for multivariate pattern analysis of fNIRS data. Unlike other methods, this mini-course leverages exFuzzy, a groundbreaking Python toolbox that enables the creation of interpretable logic statements directly from fNIRS data, facilitating a seamless transition from data collection to publication.

Learning Outcomes

  • Learn the foundations of fuzzy logic
  • Dive into fNIRS data analysis with Python
  • Perform multivariate-pattern analysis

Course Plan

Level: Introductory

Pre-Requisites: Basic programming skills
Course Duration: 3 hours

Delivery Plan


Why enrol on this course?

This minicourse aims to provide notions to the fNIRS community about the ex-fuzzy foundations through hands-on exercises.