SpO2_Apnea_Det_ORDA.zip (514.33 kB)

A Dirichlet Process Mixture Model for Autonomous Sleep Apnea Detection using Oxygen Saturation Data

software

posted on 2021-04-13, 13:22 authored by Zhenglin Li, Mihaylova, Lyudmila S

The codes are for the conference paper 'A Dirichlet Process Mixture Model for Autonomous Sleep Apnea Detection using Oxygen Saturation Data'.

Funding

Research England’s Connecting Capability Fund award CCF18-7157- Promoting the Internet of Things via Collaboration between HEIs and Industry (Pitch-In)

History

References

Ethics

There is no personal data or any that requires ethical approval

Policy

The data complies with the institution and funders' policies on access and sharing

Sharing and access restrictions

The data can be shared openly

Data description

The file formats are open or commonly used

Methodology, headings and units

There is a readme.txt file describing the methodology, headings and units

Usage metrics

Read the peer-reviewed publication

A Dirichlet Process Mixture Model for Autonomous Sleep Apnea Detection using Oxygen Saturation Data

Department of Automatic Control and Systems Engineering

Department of Automatic Control and Systems Engineering

Categories

Artificial intelligence not elsewhere classified

Keywords

Sleep apnoea detection Dirichlet process mixture model variational inference Artificial Intelligence and Image Processing

Licence

Exports