sherazkhan Goto Github PK

experiment-jspsych

a base example for a jspsych experiment

eye-tracking-webgazer.js

Collect eye movement data using a webcam.

fastapi

FastAPI framework, high performance, easy to learn, fast to code, ready for production

fieldtrip

The MATLAB software toolbox for MEG and EEG analysis

fitbit-sleep-study

Download Fitbit data and analyze it with pySpark

flutter-course-resources

Learn to Code While Building Apps - The Complete Flutter Development Bootcamp

functional-random-forest

Functional Analysis with Random Forests

get-data-from-ms-band-2

Objective C code for iOS app to get sensor's data from the Microsoft Band 2 and send it as a csv file by email.

ggir

Code corresponding to R package GGIR

git_config

A git config file and bash prompt configuration for using git, plus some general tips.

golem

Golem is creating a global market for computing power.

goose2-data-processing

Contains multiple tools to process data acquired from various sensors

grapher

Code that implements efficient knowledge graph extraction from the textual descriptions

grasp-and-lift-eeg-challenge

Code and documentation for the winning sollution at the Grasp-and-Lift EEG Detection challenge

gratings_meg_decoding

Using matlab to decode the MEG data, which were the result of showing grating images to test takers and record the MEG data of their brain. The experiments were held in McGovern Institue for Brain Research(http://mcgovern.mit.edu), supervised by Dr. Pantazis(pantazis [AT] mit (DOT) edu), and codes were published by Sheng Qin(shengqin [AT] mit (DOT) edu).

gt3x-file-format

Documentation of the ActiGraph .gt3x file format

hand_tracking

Minimal Python interface for Google's Mediapipe HandTracking pipeline

headpos_averager

Project to calculate average/median headposition MaxFilter wrapper

hello-dispy

Looking into distributed task computing

hmm-mar

Toolbox for segmentation and characterisation of transient connectivity

homework

Assignments for CS294-112.

hpimon

realtime HPI monitor for MEG

hugadb

Database for human gait analysis consisting of continues recordings of combined activities, such as walking, running, taking stairs up and down, sitting down, and so on; and the data recorded are segmented and annotated. Data were collected from a body sensor network consisting of six wearable inertial sensors (accelerometer and gyroscope) located on the right and left thighs, shins, and feet. Additionally, two EMG sensors were used on the quadriceps (front thigh) to measure muscle activity.

impress

Tal group processing code

impresspy

imu-position-tracking

Position Tracking With IMU

ipynb_playground

Various ipython notebooks

jadhav-2016-data-analysis

Code for analysis on data from Jadhav et al. 2016

jn

jr-tools