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相关概念视频

Assessment of Respiration01:23

Assessment of Respiration

1.1K
The respiratory system's basic structures and primary functions lay the foundation for nurses' comprehensive respiratory assessments. This assessment includes subjective and objective data to gauge the patient's respiratory health.
Subjective Assessment: Nurses interview the patient to gather information directly during the subjective assessment. It includes questions about the individual's medical history, medications, and symptoms, focusing on past respiratory conditions like...
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Assessment of Ventilation I: Respiratory Rate01:20

Assessment of Ventilation I: Respiratory Rate

1.1K
Assessment of Ventilation
A Ventilation assessment is critical for monitoring a patient's health status. Respiration, one of the most accessible vital signs, provides insights into the function of numerous body systems and can indicate serious health issues, such as brainstem injuries from head trauma.
Critical Guidelines for Assessing Ventilation:
1.1K
Respiratory Assessment: Purpose and Indications01:19

Respiratory Assessment: Purpose and Indications

1.1K
Respiratory assessment is a cornerstone of nursing assessments, crucial for the early detection of patient deterioration. This evaluation transcends routine procedures, representing a critical skill nurses must master to ensure optimal patient care.
Objectives and Importance:
The primary goal of respiratory assessment is to evaluate patients at early risk of clinical deterioration. Since respiratory distress often precedes other signs of declining health, breathing patterns and sounds become a...
1.1K
Oxygen Delivering System I: Nasal Cannula and Face Mask01:26

Oxygen Delivering System I: Nasal Cannula and Face Mask

347
The human body requires oxygen to function, and when the natural process of respiration is hindered, external devices, including the following, are needed to help deliver this vital gas.
Nasal Cannula
A nasal cannula is a lightweight tube split at one end into two prongs and placed in the nostrils. It is typically used to deliver low to medium levels of oxygen.
Suggested flow rate: The suggested flow rate for a nasal cannula typically ranges between 1 and 6 L/min.
Oxygen percentage setting:...
347
Physiological Control of Respiration01:23

Physiological Control of Respiration

2.1K
Introduction
Breathing, a seemingly passive process, is regulated by the respiratory center in the brainstem. This center coordinates the involuntary control of respirations, which means it occurs without conscious effort, ensuring a smooth and uninterrupted pattern.
Regulation of Ventilation
The body maintains ventilation by monitoring levels of carbon dioxide (CO2), oxygen (O2), and hydrogen ion concentration (pH) in the arterial blood. Among these factors, the level of CO2 plays a crucial...
2.1K
Asthma-I: Introduction01:29

Asthma-I: Introduction

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Asthma is a chronic respiratory ailment that requires careful management due to its varying symptoms and influencing factors. It is characterized by airway inflammation, bronchial hyperresponsiveness, and reversible airflow obstruction, leading to symptoms like wheezing, shortness of breath, chest tightness, and coughing. The symptom frequency and intensity may vary considerably over time. It is also linked to immune system responses to allergens and irritants, highlighting the complex...
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Additive Manufacturing-Enabled Low-Cost Particle Detector
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人工智能-物联网低成本污染监测传感器网络,帮助患有呼吸系统问题的公民.

Santiago Felici-Castell1, Jaume Segura-Garcia1, Juan J Perez-Solano1

  • 1Escola Tècnica Superior d'Enginyeria, Universitat de València, Campus de Burjassot, 46100 Valencia, Spain.

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概括

这项研究将低成本空气质量 (AQ) 传感器与5G和AI集成,以预测24小时的空气质量,从而实现早期公共卫生警告. 多长短期内存 (LSTM) 网络实现了最佳的预测准确性.

关键词:
这就是为什么物联网物联网物联网.这是LSTM的LSTM.WSN WSN 在线新闻空气污染 空气污染人工智能的人工智能是人工智能.预测 预测 预测 预测低成本的传感器神经网络的神经网络的神经网络

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Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies
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Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
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相关实验视频

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Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India
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科学领域:

  • 环境科学 环境科学
  • 计算机科学 计算机科学
  • 传感器技术 传感器技术

背景情况:

  • 低成本的空气质量 (AQ) 传感器为无线传感器网络 (WSN) 提供了灵活性和能源效率.
  • 传统的AQ监测面临着数据复杂性和易出错的挑战,尽管低成本传感器可以提高空间和时间采样的潜力.
  • 由于呼吸和过敏问题日益增加,城市地区越来越需要先进的AQ监测.

研究的目的:

  • 将低成本的AQ传感器与5G通信和人工智能 (AI) 进行实时监控.
  • 开发24小时前的AQ读数预测模型,以提供早期公共卫生警告.
  • 评估用于AQ预测的不同神经网络架构的性能.

主要方法:

  • 利用了低成本 AQ 传感器和 5G 通信基础设施的网络.
  • 应用人工智能 (AI) 技术,特别是卷积神经网络 (CNN) 和深度神经网络 (DNN).
  • 评估了四种神经网络架构:多线性,多密度,多卷积和多长短期记忆 (LSTM) 网络,在一个全面的数据集上进行训练.

主要成果:

  • 对于大多数预测的AQ参数,平均估计误差约为7.2%.
  • 多LSTM网络在24小时前的AQ预测中表现最佳.
  • 具体的污染物显示出较低的误差:CO2 (0.1%),PM10 (2.4%),PM2.5 (2.4%),PM1.0 (2.4%),NO2 (6.7%) 等.

结论:

  • 低成本AQ传感器,5G和AI (特别是多LSTM) 的整合对于准确的短期空气质量预测是有效的.
  • 这种方法可以显著提高AQ监测,特别是在城市环境中,通过提供及时的早期警告.
  • 该研究验证了先进的人工智能模型的潜力,以提高公共卫生应用中低成本传感器数据的实用性.