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

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

Estimation of Total Sleep Time From Respiratory Event Intervals in Sleep Disordered Breathing.

Journal of sleep research·2026
Same author

Assessment of out-of-field doses in pediatric radiotherapy.

Radiological physics and technology·2026
Same author

Slow-SPEED: protocol for three randomised trials of remotely delivered exercise to prevent Parkinson's disease.

NPJ Parkinson's disease·2026
Same author

Papilledema and related clinical and paraclinical visual assessment in cerebral venous and sinus thrombosis versus idiopathic intracranial hypertension.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology·2026
Same author

Transarterial Chemoembolization in Hepatocellular Carcinoma: Lessons from a 10-Year Real-World Retrospective Study.

Journal of hepatocellular carcinoma·2026
Same author

Model-based rigid and nonrigid volumetric image registration for image-guided interventions.

International journal of computer assisted radiology and surgery·2026

相关实验视频

Updated: Jul 27, 2025

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

在临床人群中,用于可穿戴睡眠分期的计算效率高的算法.

Pedro Fonseca1,2, Marco Ross3,4, Andreas Cerny4

  • 1Philips Research Eindhoven, High Tech Campus 34, 5656AE, Eindhoven, The Netherlands. pedro.fonseca@philips.com.

Scientific reports
|June 6, 2023
PubMed
概括

一个新的算法使用心脏信号和身体运动来有效地分阶段睡眠. 它的准确性与旧方法相似,但速度快50倍,有助于睡眠诊断.

更多相关视频

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
08:36

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

12.1K
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

573

相关实验视频

Last Updated: Jul 27, 2025

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
Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
08:36

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments

Published on: August 8, 2019

12.1K
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

573

科学领域:

  • 生物医学工程 生物医学工程
  • 计算神经科学是一种神经科学.
  • 睡眠医学 睡眠医学

背景情况:

  • 准确的睡眠分期对于诊断睡眠障碍至关重要.
  • 传统的多睡眠学是资源密集的.
  • 开发高效,非侵入性睡眠监测工具是必不可少的.

研究的目的:

  • 开发和验证一个计算效率高的算法,用于4类睡眠阶段.
  • 与现有方法相比,评估性能和执行时间.
  • 探索神经网络在从生理信号中发现睡眠阶段模式方面的潜力.

主要方法:

  • 使用加速计来测量身体运动,以及用于测量心脏活动 (心跳间隔,心率) 的光电图 (PPG) 传感器.
  • 训练了一个神经网络,将睡眠阶段 (清醒,N1/N2,N3,REM) 分类为30秒的时段.
  • 验证了算法与多睡眠学 (PSG) 相比,并将执行时间与基于心率变化 (HRV) 的算法进行了比较.

主要成果:

  • 实现了0.638的时代-每时代卡帕 (κ) 的中位数,准确率为77.8%.
  • 证明了与之前开发的基于HRV的算法相当的性能.
  • 与基于HRV的方法相比,展示了50倍更快的执行时间.

结论:

  • 神经网络算法有效地将心脏和运动数据映射到睡眠阶段,而无需先前的领域知识.
  • 该算法的效率和性能使其适合在睡眠诊断中实际实施.
  • 这种方法为可访问和自动化睡眠分析提供了新的可能性,即使在患有睡眠病理的患者中也是如此.