Abstract:
This paper presents a sleep stage recognition system for Awake, rapid eye movement (REM) and non-REM (NREM) sleep detection. Two respiratory variability (RV) features are...Show MoreMetadata
Abstract:
This paper presents a sleep stage recognition system for Awake, rapid eye movement (REM) and non-REM (NREM) sleep detection. Two respiratory variability (RV) features are extracted from oro-nasal airflow signals provided in the sleep-EDF (Expanded) database. A two layer system with threshold comparison classifier is implemented. This system achieved state-of-the-art performance with simple features and classifiers. The average accuracy of 74.00%±5.30% and Cohen's kappa coefficient of 0.49±0.08 were achieved with 21 recordings. In the end, the measure of sleep efficiency was calculated and the average absolute error was 3.61%±3.66%.
Published in: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Date of Conference: 16-20 August 2016
Date Added to IEEE Xplore: 18 October 2016
ISBN Information:
ISSN Information:
PubMed ID: 28268909
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Sleep Stages ,
- Respiratory Signals ,
- Cohen’s Kappa ,
- Rapid Eye Movement ,
- Sleep Efficiency ,
- Respiratory Variables ,
- Average Absolute Error ,
- Cohen's Kappa Coefficient ,
- Sleep Quality ,
- Electromyography ,
- Heart Rate Variability ,
- Sleep Time ,
- Target Class ,
- Future Data ,
- Polysomnography ,
- Electrooculogram ,
- Sleep Study ,
- Additional Rules
- MeSH Terms
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Sleep Stages ,
- Respiratory Signals ,
- Cohen’s Kappa ,
- Rapid Eye Movement ,
- Sleep Efficiency ,
- Respiratory Variables ,
- Average Absolute Error ,
- Cohen's Kappa Coefficient ,
- Sleep Quality ,
- Electromyography ,
- Heart Rate Variability ,
- Sleep Time ,
- Target Class ,
- Future Data ,
- Polysomnography ,
- Electrooculogram ,
- Sleep Study ,
- Additional Rules
- MeSH Terms
