The University of Sheffield
Browse
- No file added yet -

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

Download (514.33 kB)
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

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

    Department of Automatic Control and Systems Engineering

    Categories

    Keywords

    Sleep apnoea detectionDirichlet process mixture modelvariational inferenceArtificial Intelligence and Image Processing

    Licence

    GPL 3.0+

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC