Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Stages of Sleep01:22

Stages of Sleep

178
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...
178
Sleep-Wake Cycles01:24

Sleep-Wake Cycles

1.2K
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:
1.2K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Honokiol and Its Emerging Role in Breast Cancer Therapy.

Cancers·2026
Same author

Nano-engineered Ag@MgO embedded chitosan hydrogel patch for potent antibacterial activity, antibiofilm activity, and infected wound healing.

Journal of materials chemistry. B·2026
Same author

Comment on "Assessing the environmental, financial, and social impact of immediate-release morphine tablets compared to oral morphine solution" by Tahir et al.

The International journal of pharmacy practice·2026
Same author

Differential Expression of hsa-miR-34c-5p, hsa-miR-200b-3p, hsa-miR-320a-3p and Their Target Genes Determine Survival in Clear-Cell Renal Cell Carcinoma.

Annals of surgical oncology·2026
Same author

Comment on "Use of bundle for prevention of infiltration in peripheral intravenous catheters in hospitalized children: A scoping review".

Journal of infection prevention·2026
Same author

ASO Author Reflections: MicroRNAs and Their Target Genes as a Potential Biomarker and Determine Survival in Clear Cell Renal Cell Carcinoma.

Annals of surgical oncology·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jun 14, 2025

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
10:56

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Published on: August 2, 2017

10.0K

有效的睡眠阶段识别使用零碎线性EEG信号减少:用于睡眠障碍诊断的新算法

Yash Paul1, Rajesh Singh2, Surbhi Sharma3

  • 1Department of Information Technology, Central University of Kashmir, Ganderbal 191201, India.

Sensors (Basel, Switzerland)
|August 29, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种使用半波方法的新算法,可以从脑电图 (EEG) 信号中准确检测睡眠阶段. 这种高效的方法实现了高精度,有助于诊断睡眠障碍和实时监测.

关键词:
这就是ADASYN.这是一个EEGEEGEEGEEGEEGEEGEEG.K-最近的邻居在SMOTE中使用.欧几里德距离是什么意思我们有半导体.睡眠状态是指睡眠状态.

更多相关视频

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

474
Polygraphic Recording Procedure for Measuring Sleep in Mice
08:45

Polygraphic Recording Procedure for Measuring Sleep in Mice

Published on: January 25, 2016

23.6K

相关实验视频

Last Updated: Jun 14, 2025

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
10:56

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Published on: August 2, 2017

10.0K
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

474
Polygraphic Recording Procedure for Measuring Sleep in Mice
08:45

Polygraphic Recording Procedure for Measuring Sleep in Mice

Published on: January 25, 2016

23.6K

科学领域:

  • 神经科学是一个神经科学.
  • 生物医学工程 生物医学工程
  • 信号处理 信号处理

背景情况:

  • 准确的睡眠阶段检测对于诊断睡眠障碍至关重要.
  • 目前使用脑电图 (EEG) 信号识别睡眠阶段的方法在效率和准确性方面存在局限性.
  • 信号处理的进步为改善睡眠分析提供了潜力.

研究的目的:

  • 开发一种使用EEG信号准确识别睡眠阶段的新高效算法.
  • 引入半波法作为数据减少技术,以简化EEG信号,同时保持关键特征.
  • 评估拟议算法的性能,并将其与现有方法进行比较.

主要方法:

  • 一种线性数据减少技术,即半波方法,应用于时间域中的EEG信号.
  • 一个包含六个统计特征的特征向量从缩小的零碎线性表示中提取出来.
  • 使用MIT-BIH多人睡眠数据库进行测试,并评估了各种分类器,其中K-Nearest Neighbor (KNN) 显示出卓越的性能.

主要成果:

  • 拟议的算法在多睡眠数据库上实现了高性能指标,平均灵敏度为94.82%,特异性为96.65%,准确度为95.73%.
  • 半波法有效地减少了EEG信号的复杂性,同时保留了用于睡眠阶段分类的关键信息.
  • 当与拟议的特征提取方法集成时,K-Nearest Neighbor分类器表现出最佳性能.

结论:

  • 开发的算法提供了使用EEG信号进行睡眠阶段检测的计算效率高和准确的方法.
  • 该方法在实时睡眠监测应用和临床采用方面显著有前途.
  • 这一进步有助于改善睡眠障碍的认识,检测和管理.