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arl-eegmodels

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

braindecode

A deep learning toolbox to decode raw time-domain EEG.

brainflow

BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors

buildingexperimentspsychopy_materials

The materials that go with the book Building Experiments in PsychoPy (Peirce and MacAskill)

candlestickpattern

Calculate Simple Candle Stick Pattern

eeg_cnn

Python code for mental state recognition from EEG observations using CNN and RNN networks.

eeglearn

A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea.

eegrunt

A Collection Python EEG (+ ECG) Analysis Utilities for OpenBCI and Muse

eegsaver

An Android app that dump EEG data from a Neurosky Mindwave and saves it to Dropbox as CSV for later analysis

entropy

EntroPy: complexity of (EEG) time-series in Python

fundamental-stock-analysis-intrinsic-value

Analyze stocks like Warren Buffet and Benjamin Graham

hello-world

My first github trial

hugo-universal-theme

Port of the Universal theme to Hugo

iat-score

This R script was developed to score Implicit Association Test (IAT) data as per the guidelines of revised scoring algorithm suggested by (Greenwald, Nosek, & Banaji, 2003): Greenwald, A. G, Nosek, B. A., & Banaji, M. R. (2003). Understanding and using the Implicit Association Test: I. An improved scoring algorithm. Journal of Personality and Social Psychology, 85, 197-216. This R script will handle data files generated from INQUISIT program.

ml-for-beginners

12 weeks, 24 lessons, classic Machine Learning for all

mne-python

MNE : Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

neurohacking

Neurohacking Coursera Course

neurohacking_data

Data for Neurohacking MOOC

neurotechx-mcgill-2019

A wheelchair that is controlled via EEG brain signals and enhanced using assisted-driving

openbci_32bit_serial_trigger

Code that receives a signal on the Serial port, and inserts a trigger into the data stream.

openbci_mne

Examples of using OpenBCI boards with MNE

openbcip300

Open Brain Computer Interface project using P300 paradigm

polyemotion

Detection of emotions via openBCI

pyeeg

Python + EEG/MEG = PyEEG

python-scraping

Code samples from the book Web Scraping with Python http://shop.oreilly.com/product/0636920034391.do

python_neurosky_data_analysis

scholar-h-index

Compute the h-index and g-index for FBK employees.

ssvep_openbci

SSVEP experiment for the OpenBCI EEG device.

survey-droid

Social science research has traditionally required data that is difficult to gather; by using smartphones as data collection tools we can overcome the methodological limitations that have hampered social science research and kept important questions from being answered. Survey Droid solves this by offering researches a fully customizable system for gathering information for just about any population. The system consists of an Android app and a web iterface to control it. The Android application is capable of tracking location, calls, and incoming texts. Most importantly, it displays fully customizable surveys that adapt to pevious answers. The simple web-based front-end allows researchers to create surveys, control study options, download information, monitor subject participation, and access communications sent by participants. All together, this is a powerful tool for social science researchers, enabling them to conduct useful, targeted, and inexpensive research on almost any population. Best of all, it completely free and open source! This repo hosts experimental work and a potentially outdated version of the stable code. The most up to date stable version of this code is currently in https://github.com/tonyxiao/Survey-Droid

tidyquant

Bringing financial analysis to the tidyverse