Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Sleep Apnea01:21

Sleep Apnea

833
Sleep apnea is a condition where breathing stops intermittently during sleep, often leading to significant health issues. Each episode can last from 10 to 20 seconds or more and is frequently accompanied by a brief arousal from sleep. This disturbance, largely unnoticed by the individual, can lead to severe daytime fatigue. Commonly, individuals seek help after being informed by their partners about loud snoring and noticeable breathing pauses during sleep.
The condition is more prevalent among...
833
Electrocardiogram01:29

Electrocardiogram

9.6K
An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
9.6K
Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

5.1K
Holter monitoring is a continuous electrocardiography (ECG) recording that tracks the heart's electrical activity over an extended period, generally 24 to 48 hours. This noninvasive diagnostic tool detects irregular heart rhythms that may not be captured during a standard ECG performed in a clinical setting.DeviceThe Holter monitor is a portable, small device connected to several electrodes on the patient's chest. These electrodes detect the heart's electrical signals and transmit them to the...
5.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

[Separation and determination of furanocoumarins in shatian pomelo juice by HPLC-MS].

Se pu = Chinese journal of chromatography·2007
Same author

Effect of neuregulin-1 on histopathological and functional outcome after controlled cortical impact in mice.

Journal of neurotrauma·2007
Same author

Decreased expression of ING2 gene and its clinicopathological significance in hepatocellular carcinoma.

Cancer letters·2007
Same author

Compound Salvia droplet pill, a traditional Chinese medicine, for the treatment of unstable angina pectoris: a systematic review.

Medical science monitor : international medical journal of experimental and clinical research·2007
Same author

Ezrin silencing by small hairpin RNA reverses metastatic behaviors of human breast cancer cells.

Cancer letters·2007
Same author

The effect of nitric oxide on metal release from metallothionein-3: gradual unfolding of the protein.

Journal of biological inorganic chemistry : JBIC : a publication of the Society of Biological Inorganic Chemistry·2007

Related Experiment Video

Updated: Apr 16, 2026

Through-the-Wall Blood Sampling Method to Minimize Sleep Disruption in Clinical Settings
06:39

Through-the-Wall Blood Sampling Method to Minimize Sleep Disruption in Clinical Settings

Published on: June 13, 2025

621

An obstructive sleep apnea detection approach using kernel density classification based on single-lead

Lili Chen1, Xi Zhang, Hui Wang

  • 1College of Engineering, Peking University, 100871, Beijing, China, chenlili@coe.pku.edu.cn.

Journal of Medical Systems
|March 4, 2015
PubMed
Summary
This summary is machine-generated.

A new kernel density method effectively detects obstructive sleep apnea (OSA) using electrocardiogram (ECG) signals. This convenient approach shows high accuracy for home-based screening of this common cardiovascular disease risk factor.

More Related Videos

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

Published on: December 11, 2019

9.2K
Drug-Induced Sleep Endoscopy DISE with Target Controlled Infusion TCI and Bispectral Analysis in Obstructive Sleep Apnea
07:54

Drug-Induced Sleep Endoscopy DISE with Target Controlled Infusion TCI and Bispectral Analysis in Obstructive Sleep Apnea

Published on: December 6, 2016

20.9K

Related Experiment Videos

Last Updated: Apr 16, 2026

Through-the-Wall Blood Sampling Method to Minimize Sleep Disruption in Clinical Settings
06:39

Through-the-Wall Blood Sampling Method to Minimize Sleep Disruption in Clinical Settings

Published on: June 13, 2025

621
Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

Published on: December 11, 2019

9.2K
Drug-Induced Sleep Endoscopy DISE with Target Controlled Infusion TCI and Bispectral Analysis in Obstructive Sleep Apnea
07:54

Drug-Induced Sleep Endoscopy DISE with Target Controlled Infusion TCI and Bispectral Analysis in Obstructive Sleep Apnea

Published on: December 6, 2016

20.9K

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Sleep Medicine

Background:

  • Obstructive sleep apnea (OSA) is prevalent and often undiagnosed, increasing cardiovascular disease risk.
  • Polysomnography (PSG) is the gold standard for OSA diagnosis but is costly and inconvenient.
  • There is a need for accessible, reliable OSA screening methods.

Purpose of the Study:

  • To develop a convenient, non-parametric kernel density-based approach for OSA detection.
  • To utilize single-lead electrocardiogram (ECG) recordings for OSA screening.
  • To validate the proposed method using a public sleep apnea database.

Main Methods:

  • Physiologically interpretable features were extracted from RR intervals of ECG signals.
  • A kernel density classifier was employed for apnea event detection.
  • An iterative algorithm automatically selected bandwidths for density estimation.

Main Results:

  • The kernel density classifier achieved a mean accuracy of 82.07%.
  • Mean sensitivity was 83.23% and mean specificity was 80.24%.
  • The method demonstrated good performance using only two features.

Conclusions:

  • The proposed kernel density approach offers a convenient and effective method for OSA detection.
  • It achieves comparable performance to existing methods with fewer features.
  • This technique shows potential for widespread home-based OSA screening and diagnosis.