DigitalBiomarkerDiscoveryPipeline's repositories
Human-Activity-Recognition
Multimodal human activity recognition using wrist-worn wearable sensors.
Digital_Health_Data_Repository
The DHDR (Digital Health Data Repository) is a repository with sample data for use with the DBDP.
Heart-Rate-Variability
Calculates time and frequency domain heart rate variability metrics (validated in Kubios) from RR interval (ECG) or IBI (PPG).
Pre-process
Pre-processing methods for mHealth and wearables data.
cgmquantify
Functions to calculate glucose summary metrics, glucose variability metrics (as defined in clinical publications), and visualizations to visualize trends in CGM data.
Exploratory-Data-Analysis
Tools for exploratory data analysis of wearables and mHealth data.
Data-Compression-Toolbox
The Wearables Data Compression Toolbox is designed to share data compression algorithms that have been evaluated on wearables data.
Resting-Heart-Rate
Estimation of resting heart rate.
nutritionSearchTool
nutrition search tool that uses food2vec
CovIdentify
Functions to extract features from wearable data to track and predict infectious disease status.
wearablecompute
wearablecompute is an open source Python package containing over 50 data and domain-driven features that can be computed from wearables and mHealth sensor data.
Case_Studies
DBDP Case Studies
DigitalBiomarkerDiscoveryPipeline.github.io
Check out our website at dbdp.org! It is hosted here on GitHub pages.
Model-Development
General methods for machine learning for digital biomarker discovery.
systematic-digital-biomarker-literature-search
this contains a file which was used to filter authors from a pubmed search for a systematic review based on the location of the author (requiring 50% USA led) and that one author from the USA was an academic
wearablevar
Wearable Variability Package for Python
cgmquantify-R
Functions to calculate glucose summary metrics, glucose variability metrics (as defined in clinical publications), and visualizations to visualize trends in CGM data. (In R)
DeepPostures
Deep Learning Methods for Identifying Human Postures from Hip-Worn Accelerometer Data
devicely
Devicely: A Python package for reading, timeshifting and writing sensor data