EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD
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Updated
Nov 16, 2024 - MATLAB
EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD
FP-AUD-SMARTMIC1 provides a firmware running on STM32 which acquires audio signals of four digital MEMS microphones, elaborates them by means of embedded DSP libraries and streams the processed audio to both an USB host and a loudspeaker connected to the relevant expansion board.
The BirdsEye RL/RF project enables localization of mobile radio frequency targets, e.g., drones operators, via commericial off-the-shelf sensors.
pyCAPLunar is a python package to determine the moment tensor of earthquake sources and their uncertainty by using the 3D receiver-side SGT database.
Sequential adaptive elastic net (SAEN) approach, complex-valued LARS solver for weighted Lasso/elastic-net problems, and sparsity (or model) order detection with an application to single-snapshot source localization.
Real-time EEG source localization based on Smarting mBrainTrain EEG headset and implemented in Matlab.
Source localization and connectivity analysis of high-density EEG data
ICA preprocessing & source localization for EEG. Please read wiki for detailed info:
EEG & MRI processing, Micro-States analysis & Sources localization
SDENet as Uncertainty Quantification Method for EEG Source Localization
"Octopus Realtime Encephalography Lab" is the (hard) real-time networked EEG-lab framework I have developed during my PhD Thesis at Brain Research Lab of Hacettepe University Faculty of Medicine Biophysics Lab. It is meant to be a holistic golden-standard solution for all tasks of cortical source localization/networking, brain-computer interface…
Coupled matrix-tensor factorization for integrating EEG and ffMRI on the brain cortical surface with source reconstruction
TRAP MUSIC algorithm for MEG/EEG multi-source localization
TRAP MUSIC algorithm for MEG/EEG multi-source localization
Sparsity enables subcortical source estimation, Krishnaswamy et al, PNAS 2017
The code of paper "Sequential Attention Source Identification based on Feature Representation".
Code to analyze high-density EEG and concurrent EMG/EOG datastreams during balance perturbations (replicates results from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6088363/)
Acoustic source localisation implementation
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