augustobrusaca

augustobrusaca's Stars

• CMU-Perceptual-Computing-Lab/openpose

  OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

  Language:C++31.4k7.9k

• paulhibbing/PBpatterns

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• ntnu-ai-lab/harth-ml-experiments

  Baseline Machine Learning models for the Human Activity Recognition Trondheim (HARTH) dataset

  Language:Python248

• ntnu-ai-lab/SelfPAB

  Large-Scale Pre-Training for Dual-Accelerometer Human Activity Recognition

  Language:Python71

• iriseekhout/Agree

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• jhmigueles/popmetrics

  Repository for code related to population-based acceleration metrics

  Language:HTML2

• dipetkov/actigraph.sleepr

  Detect periods of sleep and non-wear from ActiGraph data

  Language:R328

• actigraph/agcounts

  Code for the technical report on the ActiLife counts algorithm.

  Language:Python3413

• actigraph/pygt3x

  Python module for reading GT3X/AGDC file format data

  Language:Python157

• jbengler/tidyplots

  Tidy Plots for Scientific Papers

  Language:R2913

• jbengler/tidyheatmaps

  Heatmaps from Tidy Data

  Language:R473

• wurli/r-best-practice

  A cheatsheet for basic best practice in R programming

  1188

• bhelsel/APHA21PA3190

  2021 American Public Health Association Presentation (Physical Activity Section 3190.0). Title of the presentation: A comparison of accelerometer cut-points to determine moderate-to-vigorous physical activity in adults with Alzheimer’s disease and related dementia. Authors: Authors: Brian Helsel, PhD, MS, CSCS, Lauren Ptomey, PhD, RD, MacKenzie Koester, MPH, CHES, Richard Washburn, PhD, Joseph Donnelly, EdD. Funding: AG061187, TL1TR002368

  Language:R1

• pydemull/activAnalyzer.nhanes

  Language:HTML1

• wadpac/GGIR

  Code corresponding to R package GGIR

  Language:R9962

• pydemull/activAnalyzer

  Language:R51

• tgbrooks/biobankAccelerometerAnalysis

  Fork of activityMonitoring/biobankAccelerometerAnalysis

  Language:Python2

• OxWearables/stepcount

  A step-counting model based on self-supervised learning for wrist-worn accelerometer data.

  Language:Jupyter Notebook2111

• Kanaries/GWalkR

  Turn your data frame into a tableau style drag and drop UI interface to build visualization in R.

  Language:TypeScript42740

• bhelsel/agcounts

  R package for extracting actigraphy counts from accelerometer data.

  Language:R105

• how-chen/Biomech

  Language:Matlab63

• motus-nfa/ActiMotus

  The repository for the source code of the Motus system

  Language:Python3

• mcomas/coda.base

  A Basic Set of Functions for Compositional Data Analysis

  Language:R7

• malucalle/coda4microbiome

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• cran/coda4microbiome

  :exclamation: This is a read-only mirror of the CRAN R package repository. coda4microbiome — Compositional Data Analysis for Microbiome Studies. Homepage: https://malucalle.github.io/coda4microbiome/ Report bugs for this package: https://github.com/malucalle/coda4microbiome/issues

  Language:R22

• github-js/acc

  Acc package for processing, visualizing, exploring, and analyzing accelerometer data

  Language:R33

• NLeSC/mcfly

  A deep learning tool for time series classification and regression

  Language:JavaScript36281

• wadpac/mcfly

  A deep learning tool for time series classification

  Language:JavaScript2

• florale/multilevelcoda-sim

  Reproduction material for the simulation study for multilevelcoda package and the manuscript "Bayesian Multilevel Compositional Data Analysis: Introduction, Evaluation, and Application".

  Language:R2

• florale/multilevelcoda

  multilevelcoda R package for Bayesian multilevel compositional data analysis

  Language:R132