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

Stages of Sleep01:22

Stages of Sleep

1.6K
Sleep progresses through distinct stages, each characterized by specific brain wave patterns and physiological responses ranging from wakefulness to stages of non-rapid eye movement, known as non-REM, to rapid eye movement, referred to as REM. Understanding these stages helps in recognizing how sleep supports various bodily and cognitive functions.
Before sleep begins, in wakefulness, the brain exhibits primarily beta waves, which are high in frequency and low in amplitude, indicating alertness...
1.6K
Sleep-Wake Cycles01:24

Sleep-Wake Cycles

3.1K
Sleep is an essential physiological process vital to maintaining overall well-being. The reticular activating system (RAS), a network of neurons in the brainstem, regulates wakefulness and sleep. While it may seem passive, sleep consists of distinct cycles, each with its unique characteristics and functions. Two key sleep phases are non-rapid eye movement (NREM) and  rapid eye movement (REM).
NREM Sleep
NREM sleep comprises four progressive stages that seamlessly merge:
3.1K
Understanding Sleep01:11

Understanding Sleep

1.8K
Sleep, an essential biological state, involves significant reductions in physical activity, sensory awareness, and interaction with the environment. This complex physiological process is primarily regulated by specific brain regions, notably the hypothalamus and pons, which govern the sleep-wake cycle or circadian rhythm.
The circadian rhythm, a nearly 24-hour cycle, is deeply influenced by environmental light cues. Light exposure directly affects the hypothalamus, which in turn regulates...
1.8K
REM Sleep Behavior Disorder01:15

REM Sleep Behavior Disorder

2.2K
REM Sleep Behavior Disorder (RBD) is a sleep disorder characterized by the absence of muscle paralysis that normally occurs during the REM phase of sleep. This absence allows individuals to physically act out their dreams, which are often vivid and disturbing. Common behaviors exhibited during episodes include kicking, punching, and yelling. These actions can be dangerous, potentially leading to injuries for the person with RBD or their bed partner.
RBD is significantly associated with...
2.2K
Management of Insomnia01:19

Management of Insomnia

745
The sleep cycle, an integral part of human health, consists of several stages with distinct characteristics and functions. It begins with a transition from wakefulness to sleep, known as the light sleep phase, followed by the restorative deep sleep phase, essential for physical recovery and growth. The cycle concludes with the Rapid Eye Movement (REM) phase, characterized by high brain activity and vivid dreaming. Insomnia, a prevalent sleep disorder, involves difficulty falling asleep, staying...
745
Substance Use Disorders Affecting Sleep01:24

Substance Use Disorders Affecting Sleep

501
Substance use disorders involve a pattern of using drugs more extensively than intended and continuing use despite harmful consequences. This includes legal substances like alcohol and nicotine, as well as illegal drugs. These disorders often involve both physical and psychological dependence, reflecting compulsive use of substances that significantly alter thoughts, feelings, and behaviors, contributing to a major public health issue.
Understanding the concepts of physical dependence,...
501

You might also read

Related Articles

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

Sort by
Same author

Perspectives on Dissemination of Sleep Knowledge and Standards Across Wider Europe and Beyond, the ESRS Assembly of National Sleep Societies Experience.

Journal of sleep research·2025
Same author

Cascades of quasi-bound states in the continuum.

Nanophotonics (Berlin, Germany)·2025
Same author

Predictors of sleepiness in a large-scale epidemiology study ESSE-RF.

Frontiers in neurology·2024
Same author

Early sleep apnea treatment in stroke (eSATIS) - a multicentre, randomised controlled, rater-blinded, clinical trial: The association of post-stroke cognition with sleep-disordered breathing and its treatment.

Journal of sleep research·2024
Same author

Are circadian rhythms in disarray in patients with chronic critical illness?

Sleep medicine: X·2024
Same author

Lifestyle management of hypertension: International Society of Hypertension position paper endorsed by the World Hypertension League and European Society of Hypertension.

Journal of hypertension·2023

Related Experiment Video

Updated: Mar 6, 2026

Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research
04:54

Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research

Published on: November 8, 2024

1.1K

Bioradiolocation-based sleep stage classification.

Alexander Tataraidze, Lyudmila Korostovtseva, Lesya Anishchenko

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 9, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a bioradar method to classify sleep stages (wakefulness, REM, light, deep sleep) using breathing and motion data. The technique shows promise for unobtrusive sleep disorder monitoring systems.

    More Related Videos

    Multi-Modal Home Sleep Monitoring in Older Adults
    07:40

    Multi-Modal Home Sleep Monitoring in Older Adults

    Published on: January 26, 2019

    8.3K
    Polygraphic Recording Procedure for Measuring Sleep in Mice
    08:45

    Polygraphic Recording Procedure for Measuring Sleep in Mice

    Published on: January 25, 2016

    25.5K

    Related Experiment Videos

    Last Updated: Mar 6, 2026

    Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research
    04:54

    Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research

    Published on: November 8, 2024

    1.1K
    Multi-Modal Home Sleep Monitoring in Older Adults
    07:40

    Multi-Modal Home Sleep Monitoring in Older Adults

    Published on: January 26, 2019

    8.3K
    Polygraphic Recording Procedure for Measuring Sleep in Mice
    08:45

    Polygraphic Recording Procedure for Measuring Sleep in Mice

    Published on: January 25, 2016

    25.5K

    Area of Science:

    • Biomedical Engineering
    • Sleep Science
    • Signal Processing

    Background:

    • Accurate sleep stage classification is crucial for diagnosing and managing sleep disorders.
    • Current polysomnography methods can be obtrusive and limit natural sleep.
    • Non-invasive monitoring techniques are needed for widespread sleep assessment.

    Purpose of the Study:

    • To develop and validate a novel method for classifying sleep stages using bioradar technology.
    • To assess the performance of the proposed method in differentiating wakefulness, REM, light, and deep sleep.
    • To evaluate the potential of bioradar for unobtrusive sleep monitoring.

    Main Methods:

    • Respiratory activity and body motion data were collected using a bioradar system.
    • A classification algorithm was developed based on the analysis of these physiological signals.
    • The method was validated against polysomnography data from 32 healthy subjects.

    Main Results:

    • The bioradar method achieved a Cohen's kappa of 0.49 for wake-REM-light-deep sleep classification.
    • Classification accuracy for wake-REM-NREM stages reached a Cohen's kappa of 0.55.
    • Sleep/wakefulness determination yielded a Cohen's kappa of 0.57.

    Conclusions:

    • Bioradar-based analysis of respiratory and motion data offers a viable approach for sleep stage classification.
    • The developed method demonstrates potential for unobtrusive sleep monitoring.
    • Further research may lead to improved diagnostics, prevention, and management of sleep disorders.