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Management of Insomnia01:19

Management of Insomnia

229
The sleep cycle, an integral part of human health, consists of several stages with distinct characteristics and functions. It begins with a transition from wakefulness to sleep, known as the light sleep phase, followed by the restorative deep sleep phase, essential for physical recovery and growth. The cycle concludes with the Rapid Eye Movement (REM) phase, characterized by high brain activity and vivid dreaming. Insomnia, a prevalent sleep disorder, involves difficulty falling asleep, staying...
229
Insomnia01:27

Insomnia

78
Insomnia is a prevalent sleep disorder characterized by difficulty falling asleep, frequent awakenings during the night, and waking up too early without being able to return to sleep. People with insomnia often experience these disruptions at least three nights a week for at least one month. Chronic insomnia, which lasts for at least three months, can lead to increased anxiety, which in turn can worsen sleep difficulties, creating a cycle of sleeplessness and stress.
Multiple factors contribute...
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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
Stages of Sleep01:22

Stages of Sleep

163
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...
163
Narcolepsy01:07

Narcolepsy

85
Narcolepsy is a chronic sleep disorder characterized by pervasive, uncontrolled sleepiness and other sleep disturbances. One of its hallmark symptoms is an abrupt transition to REM sleep upon falling asleep, which causes symptoms typically associated with this phase to occur unexpectedly during wakefulness. These include the following symptoms, which typically last from a minute or two to half an hour.
85
Sedatives and Hypnotics Drugs: Miscellaneous Agents01:17

Sedatives and Hypnotics Drugs: Miscellaneous Agents

143
Sedatives and hypnotics encompass a wide range of substances, each with its unique mechanism of action, uses, and potential adverse effects.
Melatonin congeners like ramelteon (Rozerem) and tasimelteon (Hetlioz) selectively bind to melatonin receptors (MT1 and MT2) and thus mimic the actions of melatonin, a hormone that regulates sleep-wake cycles. Tasimelteon is primarily used for non-24-hour sleep-wake disorder, common in blind patients. They are also used to treat conditions like insomnia...
143

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相关实验视频

Updated: May 24, 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

9.9K

在睡眠微观结构中使用循环交替模式对失眠进行分类.

Rajkumar Nagaiah, Ritika Jain

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    概括

    这项研究表明,分析睡眠微观结构,特别是循环交替模式 (CAP),可以准确地识别失眠. 这些发现为诊断失眠患者的睡眠不稳定和唤醒提供了一种新的方法.

    科学领域:

    • 神经科学是一个神经科学.
    • 睡眠医学 睡眠医学
    • 计算生物学 计算生物学

    背景情况:

    • 睡眠不稳定和唤醒是诊断失眠的关键指标.
    • 循环交替模式 (CAP) 反映了睡眠微观结构,但它们在失眠分类中的作用还未得到充分研究.
    • 来自睡眠宏观和微观结构的定量指标对于理解睡眠障碍至关重要.

    研究的目的:

    • 探索不同CAP子阶段的有用性,以区分患有失眠的个体与健康的对照.
    • 使用睡眠微结构模式开发失眠的分类模型.
    • 评估机器学习模型在主体独立失眠分类中的性能.

    主要方法:

    • 利用来自CAP睡眠数据库的睡眠数据,包括9名失眠患者和16名健康受试者.
    • 从睡眠宏观结构和微观结构模式中提取了定量指标,专注于CAP子阶段.
    • 采用支持矢量机 (SVM) 分类器与线性内核进行分类任务.

    主要成果:

    • 使用80%-20%的验证方法实现了90 ± 10%的高分类准确性.
    • 通过一个离开一个主体的交叉验证策略,获得了88 ± 12%的准确性.
    • 与CAP数据库中关于失眠分类的现有研究相比,表现优越.

    更多相关视频

    A Chronic Sleep Fragmentation Model using Vibrating Orbital Rotor to Induce Cognitive Deficit and Anxiety-Like Behavior in Young Wild-Type Mice
    06:23

    A Chronic Sleep Fragmentation Model using Vibrating Orbital Rotor to Induce Cognitive Deficit and Anxiety-Like Behavior in Young Wild-Type Mice

    Published on: September 22, 2020

    5.3K
    Multi-Modal Home Sleep Monitoring in Older Adults
    07:40

    Multi-Modal Home Sleep Monitoring in Older Adults

    Published on: January 26, 2019

    7.6K

    相关实验视频

    Last Updated: May 24, 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

    9.9K
    A Chronic Sleep Fragmentation Model using Vibrating Orbital Rotor to Induce Cognitive Deficit and Anxiety-Like Behavior in Young Wild-Type Mice
    06:23

    A Chronic Sleep Fragmentation Model using Vibrating Orbital Rotor to Induce Cognitive Deficit and Anxiety-Like Behavior in Young Wild-Type Mice

    Published on: September 22, 2020

    5.3K
    Multi-Modal Home Sleep Monitoring in Older Adults
    07:40

    Multi-Modal Home Sleep Monitoring in Older Adults

    Published on: January 26, 2019

    7.6K

    结论:

    • 睡眠的微观结构模式,特别是CAP子阶段,对于分类失眠非常有价值.
    • 提出的方法提供了一种可靠的,独立于对象的失眠诊断方法.
    • 测量CAP阶段A和B的变化可以通过方便的睡眠监测来帮助确认失眠的诊断.