There are 4 repositories under fnirs topic.
A Python Toolbox for Multimode Neural Data Representation Analysis - A Representational Analysis Toolbox for Neuroscience, including Neural Pattern Similarity (NPS), Representational Similarity Analysis (RSA), Spatiotemporal Pattern Similarity (STPS) & Inter-Subject Correlation (ISC)
Transformer-based fNIRS Classification. Paper: Transformer Model for Functional Near-Infrared Spectroscopy Classification
Temporal Derivative Distribution Repair: A motion correction method for fNIRS
Package for bimodal training of deep neural networks on neurological data. Pypi: https://pypi.org/project/BiModNeuroCNN/
It collects the device data from the hardware while watching test videos and stores the results for each test user.
A command line wrapper for the NIRS Brain AnalyzIR toolbox
Wrapper for MNE that makes fNIRS data analysis easier
CNN-based fNIRS classification: Rethinking Delayed Hemodynamic Responses for fNIRS Classification
Convert the data recorded by SHIMADZU(.txt) to HOMER2 readable format (.nirs)
Homer3_Broadband-fNIRs_Version by Louis Chang
Available fNIRS dataset collected by and published in Giorjiani et al., 2020 - doi: 10.1007/s00221-020-05904-w
Adjust Homer3_preprocessing data for different subjects
Python API for the ALS Voice Human-Computer and Brain-Computer Interfaces.
PyCharm script for testing triggers in Turbo-Satori. It connects to Turbo-Satori and sends rest and task triggers over a number of trials. Each new task period is its separate condition.
A classification environment which learns features of fNIRS recordings and can distinguish between children which played alone and children who played with their mothers.
Simple interpolation methods for fNIRS cerebral signal whose channels are located in a 2D space.
repository accompanies the paper "Interacting brains revisited: A cross-brain network neuroscience perspective"
This is the MATLAB function to read fNIRS signal provided on physionet
BIDS app to view a dataset content and the events file content
This project explores real multichannel functional near-infrared spectroscopy (fNIRS) data, a non-invasive neuroimaging technique.