Sleep disorders and COVID-19.

Circadian disturbances, sleep difficulties and the COVID-19 pandemic.

Sleep disorders and COVID-19

This article presents a study on the efficiency of implementing classifiers for the detection of sleep apnea moments based on a minute-to-minute Electrocardiogram (ECG) signal, detailing the comparison of the accuracy for different classifiers. At each ECG signal, a Sgolay filter was applied to extract the Heart Rate Variability (HRV) and the ECG-Derived Respiration (EDR) and they were used for the training, testing and validation of the classifiers. The same features were extended in a second phase in order to understand if all the classified features were important. According to the results obtained, the best accuracy was 82.12%, with a sensitivity and a specificity of 88.41% and 72.29%, respectively. This study shows the importance of choosing the right classifier for a specific problem as well as choosing and using the best features for a better accuracy. These promising early-stage results may lead to complementary studies to improve the classifiers for a possible real-world application. The performance of the proposed model was compared with other approaches used for the detection of sleep apnea.

/pdf/classifier-precision-analysis-for-sleep-apnea-detection-2o16vj97dp.pdf

Classifier Precision Analysis for Sleep Apnea Detection Using ECG Signals

Circadian disturbances, sleep difficulties and the COVID-19 pandemic

Management of sleep apnea in New York City during the COVID-19 pandemic.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Jacqueline Thorpy

Author Tools

Chat about Author

Papers

Management of sleep apnea in New York City during the COVID-19 pandemic.