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

1.7K
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...
1.7K
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

2.4K
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...
2.4K

You might also read

Related Articles

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

Sort by
Same author

Vorinostat: a histone deacetylases (HDAC) inhibitor ameliorates traumatic brain injury by inducing iNOS/Nrf2/ARE pathway.

Folia neuropathologica·2018
Same author

Synthesis, crystal structure and antimicrobial activity of 2-((2-(4-(1H-1,2,4-triazol-1-yl)phenyl)quinazolin-4-yl)oxy)-N-phenylacetamide derivatives against phytopathogens.

Molecular diversity·2018
Same author

The efficacy of anti-VEGF antibody-modified liposomes loaded with paeonol in the prevention and treatment of hypertrophic scars.

Drug development and industrial pharmacy·2018
Same author

Downregulation of Blimp1 inhibits the maturation of bone marrow-derived dendritic cells.

International journal of molecular medicine·2018
Same author

Multiple Kernel Learning Based Classification of Parkinson's Disease With Multi-Modal Transcranial Sonography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2018
Same author

Transcranial Sonography Based Diagnosis Of Parkinson's Disease Via Cascaded Kernel RVFL.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2018
Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
See all related articles

Related Experiment Video

Updated: Mar 27, 2026

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

Joint collaborative representation based sleep stage classification with multi-channel EEG signals.

Xiao Liu, Jun Shi, Yiheng Tu

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 7, 2016
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel Joint Collaborative Representation (JCR) model for sleep stage classification using electroencephalography (EEG) signals. JCR effectively fuses multi-channel EEG features, outperforming traditional methods for improved sleep analysis.

    More Related Videos

    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
    11:25

    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Published on: July 26, 2013

    44.3K
    Author Spotlight: IntelliSleepScorer &#8212; 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

    Related Experiment Videos

    Last Updated: Mar 27, 2026

    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
    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding
    11:25

    Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

    Published on: July 26, 2013

    44.3K
    Author Spotlight: IntelliSleepScorer &#8212; 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

    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Machine Learning

    Background:

    • Multi-channel electroencephalography (EEG) signals are crucial for sleep stage classification.
    • Effectively fusing and representing multi-channel EEG features remains a significant challenge.
    • Traditional coding-based feature representation methods like sparse representation (SR) have limitations.

    Purpose of the Study:

    • To propose and evaluate a new Joint Collaborative Representation (JCR) model for sleep stage classification.
    • To effectively fuse multi-channel EEG features using the JCR model.
    • To compare the performance of JCR with existing methods like SR.

    Main Methods:

    • Employed Collaborative Representation (CR) as a feature representation method.
    • Developed a novel Joint CR (JCR) model to fuse multi-view data, capturing individual and inter-view information.
    • Applied the JCR model to fuse and represent multi-channel EEG signal features for sleep stage classification.

    Main Results:

    • Collaborative Representation (CR) features demonstrated superior performance compared to Sparse Representation (SR) features.
    • The proposed JCR model achieved the best performance in sleep stage classification.
    • JCR effectively fused multi-channel EEG signals, leading to enhanced classification accuracy.

    Conclusions:

    • The JCR model offers an effective approach for fusing multi-channel EEG features for sleep stage classification.
    • JCR outperforms SR and other methods by leveraging both individual and correlative information across multiple views.
    • This work advances the application of advanced feature representation techniques in sleep analysis using EEG.