Wearable Accelerometer Data Processing And Classification

GGIR

Code corresponding to R package GGIR

Sundararajan-SleepClassification-2021

Classification of sleep stages using accelerometer data

oss-dev-webinar-series-pb-field

Agenda and Notes for Webinar Series for OSS developers in physical behavior research field

hsmm4acc

Behaviour detection in wearable movement sensor data

millenniumcohort-acc

Scripts for processing accelerometer data from Millenium cohort study

GGIRread

Functions for reading accelerometer data files

psg-ncl-acc-spt-detection-eval

whitehall-acc-spt-detection-eval

Code for processing the accelerometer data from the Whitehall Study II

patientGGIR

Functions to generate patient-oriented reports from GGIR output

LIDStoolkit

R package to aid with LIDS analysis

mcfly

A deep learning tool for time series classification

movement-sequence-mapping

Code base for deriving movement sequences from accelerometer (Actigraph) data and mapping them to symbolic classes, as originally described in: https://doi.org/10.1249/mss.0000000000001849

sklearn-hierarchical-classification

Hierarchical classification module based on scikit-learn's interfaces

profileGGIR

Code to aid profiling GGIR

actipy

Python tool to process Axivity, GENEActiv, and Actigraph files

barcode-mapping

Barcode mapping function from Xinhui Wang for 2019 paper doi: 10.1249/MSS.0000000000001849

code-published-studies

Code from published papers

mechanicalshakerexperiments

read.gt3x

R-package for reading Actigraph's binary activity data

sleepsight-analytics-pipeline

Pipeline for processing data from sleepsight wearables

testGGIR

Testing Routine for GGIR

Verisense-Toolbox

Tools and utilities to analyse Verisense data