Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Understanding Sleep

Understanding Sleep

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...

You might also read

Related Articles

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

Sort by

Same author

Detecting Basilar Artery Wall Pathology in Isolated Pontine Infarction With Short-TE SWI Magnitude Images.

Stroke (Hoboken, N.J.)·2026

Same author

Exploring Nociceptive-Analgesic Balance and EEG Modulation Patterns During General Anesthesia Using Holo-Hilbert Spectral Analysis.

Pain research & management·2026

Same author

Quantifying consciousness through intrinsic probability density function.

Biological psychology·2025

Same author

Resolving transient neurophysiological signals and their interactions with adaptive time-frequency analysis.

Biological psychology·2025

Same author

Attentional dysfunction arises from right frontocentral and occipital network connectivity in Parkinson's disease.

Neuroimage. Reports·2025

Same author

Fast Rule-based NER in SpaCy for Chest Radiography Reports with CheXpert's 14 Categories<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

Role of AQP4 in ameliorating heat stress-induced cellular injury in a cell line model through active heat acclimation.

Frontiers in human neuroscience·2026

Same journal

Correction: Cognitive state monitoring for neuroadaptive information visualization.

Frontiers in human neuroscience·2026

Same journal

The synthetic self-hypothesis: dopaminergic redirection through self-face recognition in stuttering therapy.

Frontiers in human neuroscience·2026

Same journal

A randomised, placebo-controlled, triple-blind clinical trial to investigate the efficacy of <i>Ginkgo biloba</i> extract EGb 761<sup>®</sup> in cognitive impairment associated with post COVID-19 syndrome-the EGb COCOS protocol.

Frontiers in human neuroscience·2026

Same journal

Examining the independent and combined effects of autistic and ADHD traits on multisensory integration.

Frontiers in human neuroscience·2026

Same journal

Prediction of hormone receptor status in breast cancer brain metastases using an MRI-based multimodal deep learning framework.

Frontiers in human neuroscience·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 1, 2026

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

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

Evaluating and Improving Automatic Sleep Spindle Detection by Using Multi-Objective Evolutionary Algorithms.

Min-Yin Liu¹, Adam Huang², Norden E Huang^1,2

¹Department of Biomedical Sciences and Engineering, Institute of Systems Biology and Bioinformatics, National Central UniversityTaoyuan, Taiwan.

Frontiers in Human Neuroscience

|June 3, 2017

Summary

This summary is machine-generated.

Automated sleep spindle detection using multi-objective optimization shows improved performance. New hybrid methods combining Fourier and Hilbert-Huang transforms achieved F1-scores of 0.726-0.737, enhancing diagnostic accuracy for neurological disorders.

Keywords:

Hilbert-Huang transform Pareto front automatic detection multi-objective evolutionary algorithm performance assessment sleep spindles

More Related Videos

Author Spotlight: Overcoming Challenges in Drosophila Sleep Measurement Using DAM System

Author Spotlight: Overcoming Challenges in Drosophila Sleep Measurement Using DAM System

Published on: October 20, 2023

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

Related Experiment Videos

Last Updated: Mar 1, 2026

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

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

Author Spotlight: Overcoming Challenges in Drosophila Sleep Measurement Using DAM System

Author Spotlight: Overcoming Challenges in Drosophila Sleep Measurement Using DAM System

Published on: October 20, 2023

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

Area of Science:

Neuroscience
Computational Biology
Signal Processing

Background:

Sleep spindles, crucial brain activity during NREM sleep, are vital for understanding neurological disorders.
Manual identification of sleep spindles via EEG is time-consuming and lacks consistency.
Existing automated methods for sleep spindle detection show variable performance due to a lack of standardized evaluation metrics.

Purpose of the Study:

To address the lack of standardized evaluation metrics for automated sleep spindle detection.
To propose a multi-objective optimization framework for evaluating sleep spindle detection algorithms.
To improve the accuracy and reliability of automated sleep spindle detection.

Main Methods:

Employed the Strength Pareto Evolutionary Algorithm (SPEA2), a multi-objective evolutionary algorithm (MOEA).
Optimized six existing frequency-based sleep spindle detection algorithms (Fourier, CWT, HHT) and three hybrid approaches.
Utilized open-access DREAMS and MASS databases for training and testing.

Main Results:

Two novel hybrid methods combining Fourier and Hilbert-Huang transform algorithms demonstrated significant performance improvements.
Achieved F1-scores ranging from 0.726 to 0.737, indicating enhanced detection accuracy.
The multi-objective optimization approach provided a robust framework for evaluating and improving spindle detectors.

Conclusions:

Multi-objective optimization offers a promising approach to developing standardized and effective evaluation metrics for sleep spindle detection.
Hybrid methods integrating Fourier and HHT algorithms represent a significant advancement in automated sleep spindle detection.
Improved automated detection can aid in the consistent and efficient diagnosis of neurological disorders.