From 69832fc36f991806ea62f1c30dc4ecf79c4d9997 Mon Sep 17 00:00:00 2001 From: Julius Date: Sat, 27 Mar 2021 21:40:05 +0100 Subject: [PATCH] README.md --- README.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) create mode 100644 README.md diff --git a/README.md b/README.md new file mode 100644 index 0000000..67cd28b --- /dev/null +++ b/README.md @@ -0,0 +1,16 @@ +## Semesterproject of the lecture "Semesterproject Signal processing and Analysis +of human brain potentials (eeg) WS 2020/21 + +This repository holds the code of the semesterproject as well as the report. +The main files are 'preprocessing_and_cleaning.py', 'erp_analysis.py' and 'decoding_tf_analyis.py'. +The files hold: +- preprocessing_and_cleaning.py : Holds the pre-processing pipeline of the project. By executing the file all subjects are pre-processed. Subjects 001, 003, 014 are pre-processd with manually selected pre-processing information, all other subjects are pre-processed with the given pre-processing information. Details can be found in the comments of the code. +- erp_analysis.py : Hold the code for the erp-analysis. Computes the peak-differences and t-tests for several experimental contrasts. Details can be found in the comments of the code. +- decoding_tf_analysis.py : Holds the code for the decoding and time-frequency analysis. Details can be found in the comments of the code. + +The folder 'utils' holds helper functions for some plots needed for the analysis and to load data, generate strings etc. and holds the code given in the lecture. +The folder 'test' holds mostly unittests that test helper functions and one function which visually checks if N170 peaks are extracted correctly. + +For the code to work properly, the N170 dataset needs to be provided. +When first running the analysis, it may take a while. After running it one time the data is cached, so that it can be reused if the analysis should be executed again. Be careful though, as a parameter has to be explicitly set in the code, so that the already computed data is used. This parameter is a boolean given to each analysis function which caches data. +