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相关概念视频

Sleep Apnea01:21

Sleep Apnea

151
Sleep apnea is a condition where breathing stops intermittently during sleep, often leading to significant health issues. Each episode can last from 10 to 20 seconds or more and is frequently accompanied by a brief arousal from sleep. This disturbance, largely unnoticed by the individual, can lead to severe daytime fatigue. Commonly, individuals seek help after being informed by their partners about loud snoring and noticeable breathing pauses during sleep.
The condition is more prevalent among...
151
Pulse rhythm01:30

Pulse rhythm

796
Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...
796

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相关实验视频

Updated: Jul 1, 2025

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
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A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

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节能睡眠呼吸暂停检测使用基于可穿戴手光电解剖学的超维计算框架.

Tian Chen, Jingtao Zhang, Zeju Xu

    IEEE transactions on bio-medical engineering
    |March 14, 2024
    PubMed
    概括

    一种新的超维计算方法使用可穿戴PPG设备提供了高效的睡眠呼吸暂停检测. 这种方法显著降低了用于广泛家庭监控的内存,延迟和能源消耗.

    科学领域:

    • 生物医学工程 生物医学工程
    • 信号处理 信号处理
    • 机器学习 机器学习

    背景情况:

    • 睡眠呼吸暂停综合征 (SAS) 是一种普遍存在的睡眠障碍,与严重的神经认知和心血管问题有关.
    • 当前的SAS诊断工具往往是繁而昂贵的,导致诊断不足.
    • 可穿戴式光电显微镜 (PPG) 提供了大规模SAS查的潜力,但现有的算法资源密集.

    研究的目的:

    • 使用可穿戴PPG数据开发一种节能方法来检测睡眠呼吸暂停.
    • 解决当前算法在内存和能耗方面的局限性.
    • 为了实现可扩展的,长期的,基于家庭的睡眠呼吸暂停监测.

    主要方法:

    • 提出了一种利用超维计算 (HDC) 的节能SAS检测方法.
    • 引入了一种新的一维区块本地二进制模式 (1D-BlockLBP) 编码方案,灵感来自认知块.
    • 将1D-BlockLBP与HDC结合起来,以有效地捕获PPG设备的脉冲率信号动态.

    主要成果:

    • 在睡眠呼吸暂停片段检测中达到70.17%的准确性,与传统方法相比.
    • 证明了资源使用的显著减少:在ARM Cortex-M4处理器上减少了67倍的内存占用,减少了68倍的延迟,节省了93倍的能量.

    更多相关视频

    Multi-Modal Home Sleep Monitoring in Older Adults
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    Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
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    相关实验视频

    Last Updated: Jul 1, 2025

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    A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

    Published on: April 19, 2019

    11.6K
    Multi-Modal Home Sleep Monitoring in Older Adults
    07:40

    Multi-Modal Home Sleep Monitoring in Older Adults

    Published on: January 26, 2019

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    Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
    05:51

    Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health

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  • 验证了HDC和1D-BlockLBP在高计算效率下保护关键信号特性的有效性.

    • 结论:

    • 提出的基于HDC的方法为SAS检测提供了一个计算效率高的解决方案.
    • 1D-BlockLBP编码有效地保留了脉冲率信号的基本特征.
    • 这种方法提高了一致的,基于家庭的睡眠呼吸暂停监测和患者护理的可行性.