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

Understanding Sleep01:11

Understanding Sleep

447
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...
447
Blind Procedures02:07

Blind Procedures

10.7K
Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...
10.7K
Sleep-Wake Cycles01:24

Sleep-Wake Cycles

1.5K
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:
1.5K
Sleepwalking and Sleep Talking01:17

Sleepwalking and Sleep Talking

228
Somnambulism, commonly known as sleepwalking, involves individuals engaging in activities ranging from simple walking to more complex behaviors such as driving. Sleepwalking typically occurs during the slow-wave sleep stages 3 and 4 early in the night when the person is not dreaming, contradicting the myth that sleepwalkers are acting out their dreams.
Factors that increase the likelihood of sleepwalking include sleep deprivation and alcohol consumption. Contrary to common beliefs, it is safe...
228

You might also read

Related Articles

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

Sort by
Same author

Burnout Risk Prediction through Wearable Devices: An Initial Assessment.

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

Toward burnout prevention with Bayesian mixed-effects regression analysis of longitudinal data from wearables: a preliminary study.

Frontiers in digital health·2025
Same author

Synthetic electrocardiograms for Brugada syndrome: from data generation to expert cardiologists evaluation.

European heart journal. Digital health·2025
Same author

Overcoming data scarcity in life-threatening arrhythmia detection through transfer learning.

Communications medicine·2025
Same author

Designing digital health interventions with causal inference and multi-armed bandits: a review.

Frontiers in digital health·2025
Same author

Release velocity ImprovemenT with a new Metronome guIding chest COmpressions: The RITMICO simulation study.

Resuscitation plus·2025
Same journal

Nighttime light exposure is associated with metabolic dysfunction in schizophrenia: A cross-sectional analysis of the LENS study.

Sleep·2026
Same journal

Sleep Need Outcompetes Preparation: Reframing Sleep Initiation Through Naturalistic Behaviour.

Sleep·2026
Same journal

The Quest for Automated Pediatric Sleep Scoring: Are We There Yet?

Sleep·2026
Same journal

Sex Differences in the Sleep Architecture and Sleep-Disordered Breathing in C57BL/6 J Mice.

Sleep·2026
Same journal

Differential Effects of Prenatal Depression and Anxiety on Infant Sleep: Dual-Pathway Mechanisms Involving the HPA Axis and the Gut-Brain Axis.

Sleep·2026
Same journal

Metabolic Syndrome and Obstructive Sleep Apnea: Two Sides of the Same Coin.

Sleep·2026
See all related articles

Related Experiment Video

Updated: Aug 10, 2025

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

588

Multi-scored sleep databases: how to exploit the multiple-labels in automated sleep scoring.

Luigi Fiorillo1,2, Davide Pedroncelli3, Valentina Agostini3

  • 1Department of Mathematics, Statistics and Computer Science, Institute of Computer Science, University of Bern, Bern, Switzerland.

Sleep
|February 10, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method to improve automated sleep scoring by incorporating multiple expert scorer knowledge. The approach enhances model performance by better adapting to scorer consensus, leading to more accurate sleep analysis.

Keywords:
automatic sleep stage classificationdeep learningmachine learningmulti-scored sleep databases

More Related Videos

Polygraphic Recording Procedure for Measuring Sleep in Mice
08:45

Polygraphic Recording Procedure for Measuring Sleep in Mice

Published on: January 25, 2016

23.9K
Multi-Modal Home Sleep Monitoring in Older Adults
07:40

Multi-Modal Home Sleep Monitoring in Older Adults

Published on: January 26, 2019

7.7K

Related Experiment Videos

Last Updated: Aug 10, 2025

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

588
Polygraphic Recording Procedure for Measuring Sleep in Mice
08:45

Polygraphic Recording Procedure for Measuring Sleep in Mice

Published on: January 25, 2016

23.9K
Multi-Modal Home Sleep Monitoring in Older Adults
07:40

Multi-Modal Home Sleep Monitoring in Older Adults

Published on: January 26, 2019

7.7K

Area of Science:

  • Artificial Intelligence
  • Medical Informatics
  • Sleep Medicine

Background:

  • Inter-scorer variability presents a significant challenge in automated sleep scoring.
  • Current systems often train on single-scorer or averaged consensus labels, losing valuable information on scorer disagreement.

Purpose of the Study:

  • To develop a method for integrating multiple expert scorer knowledge into deep learning models for polysomnogram scoring.
  • To optimize model training by leveraging the full information from scorer consensus.

Main Methods:

  • Trained lightweight deep learning models on multi-scored polysomnography databases.
  • Utilized label smoothing with a soft-consensus (LSSC) distribution to incorporate multiple scorer insights.
  • Introduced averaged cosine similarity (ACS) to evaluate model-generated hypnodensity graphs against scorer consensus.

Main Results:

  • Model performance improved across all tested databases using the LSSC approach.
  • Achieved an increase in ACS (up to 6.4%) indicating better alignment of model outputs with scorer consensus.

Conclusions:

  • The proposed LSSC approach enhances model adaptability to scorer consensus in sleep scoring.
  • Future research will explore diverse scoring architectures and large-scale multi-scored datasets.