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相关概念视频

Neural Control of Respiration01:18

Neural Control of Respiration

5.4K
The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
5.4K

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相关实验视频

Updated: May 1, 2026

Author Spotlight: Innovations in iTUG Test for Enhanced Risk Assessment and Cognitive Insights
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一个基于动作的TinyML嵌入式咳检测系统

Maha S Diab, Esther Rodriguez-Villegas

    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

    这项研究介绍了一种可穿戴的微型机器学习 (TinyML) 系统,用于使用加速度计数据检测咳. 该系统实现了高精度,使得设备上的推断能够用于呼吸系统疾病监测.

    科学领域:

    • 生物医学工程 生物医学工程
    • 机器学习 机器学习
    • 可穿戴技术可穿戴技术
    • 呼吸系统健康 呼吸系统健康

    背景情况:

    • 咳检测对于监测慢性呼吸道疾病至关重要.
    • 将咳检测算法集成到可穿戴设备中是一个关键的研究目标.
    • 现有的方法需要改进,以便在设备上有效实施.

    研究的目的:

    • 提出一个可穿戴的微型机器学习 (TinyML) 咳检测系统.
    • 为了利用加速度计运动数据来识别咳事件.
    • 为了实现设备上的推断,实时进行呼吸监测.

    主要方法:

    • 从使用北欧Thingy:53物联网平台的5个受试者收集了加速度计数据.
    • 预处理信号并提取了18个时间域特征.
    • 训练了一个两层隐藏的神经网络;在nRF5340 SoC上使用Edge Impulse部署模型.

    主要成果:

    • 实现了高性能:94.38%的精度,93.92%的灵敏度,94.84%的特异性,94.35%的F1分数.
    • 量子化模型在1个月内实现了推断.
    • 与TFLite相比,EON编译器模型显示出更高的资源效率 (1.4KB RAM,14.8KB Flash).

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    Methods for Detecting Cough and Airway Inflammation in Mice
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    Methods for Detecting Cough and Airway Inflammation in Mice

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    Minimally Invasive Murine Laryngoscopy for Close-Up Imaging of Laryngeal Motion During Breathing and Swallowing
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    结论:

    • 提议的TinyML系统使用可穿戴加速计数据有效检测咳.
    • 在设备上部署是可行的,具有高精度和低延迟.
    • 该系统为远程和持续的呼吸系统健康监测提供了一个有希望的解决方案.