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相关概念视频

Analgesia and Pain Management01:25

Analgesia and Pain Management

628
Pain is critical to various clinical pathologies, provoking an urgent need for effective management. Pain, whether acute or chronic, is a complex neurochemical process. Its alleviation depends on the type, with nonopioid analgesics effective for mild to moderate pain, such as musculoskeletal or inflammatory pain, while neuropathic pain responds best to anticonvulsants, tricyclic antidepressants, or serotonin/norepinephrine reuptake inhibitors. For severe acute or chronic pain, opioids may be...
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Pain01:20

Pain

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Pain serves as a critical warning signal that alerts the body to potential or actual harm. When mechanical pressure on the skin is intense, such as from a sharp pinch, the sensation transitions from touch to pain. Similarly, extreme temperatures, like a hot pot handle, convert the sensation of heat into pain. Pain can also result from overstimulation of other senses, such as blinding light, loud noise, or the intense heat from habañero peppers. This ability to sense pain is essential for...
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从多模式传感器数据评估疼痛的全面研究.

Manuel Benavent-Lledo1, David Mulero-Pérez1, David Ortiz-Perez1

  • 1Department of Computer Technology, University of Alicante, 03080 Alicante, Spain.

Sensors (Basel, Switzerland)
|December 23, 2023
PubMed
概括

这项研究引入了先进的计算机视觉来客观评估疼痛,分析面部表情以提高准确性,特别是对于非沟通患者. 实现了高精度,为更好的疼痛管理铺平了道路.

关键词:
计算机视觉 计算机视觉深度学习是一种深度学习.疼痛评估疼痛的评估.模式识别 模式识别 模式识别传感器数据 传感器数据信号处理 信号处理 信号处理

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科学领域:

  • 生物医学工程 生物医学工程
  • 计算机科学 计算机科学
  • 疼痛医学 医学 疼痛医学

背景情况:

  • 传统的疼痛评估依赖于主观的患者报告,这些报告可能不准确,特别是对于有认知障碍的患者.
  • 客观的疼痛评估对于及时干预和有效的患者护理至关重要.
  • 现有的方法缺乏针对无法有效传达疼痛的个体的强大,客观的措施.

研究的目的:

  • 开发和验证用于客观疼痛评估的先进计算机视觉技术.
  • 分析生物医学传感器数据和面部表情分析之间的相关性,以检测疼痛.
  • 在已建立的数据集上使用最先进的计算机视觉来建立疼痛评估的基线.

主要方法:

  • 利用最先进的计算机视觉技术,包括基于变压器的架构,从视频数据中分析面部表情.
  • 进行患者面部表情的每和时间上下文分析.
  • 与视觉疼痛指标相关联的生物医学传感器数据.
  • 在UNBC-McMaster肩部疼痛表达档案数据库和BioVid热痛数据库中验证了方法.

主要成果:

  • 在UNBC-McMaster数据集上使用单个来估计疼痛的准确性超过96%.
  • 在疼痛估计中的F1分数,回忆和精确度指标中达到94%以上.
  • 证明了计算机视觉技术在客观疼痛评估中的有效性.
  • 提供了疼痛评估方法的比较基线.

结论:

  • 计算机视觉,特别是基于变压器的模型,为疼痛评估提供了高度准确和客观的方法.
  • 面部表情分析显著提高了疼痛检测能力,特别是对于非语言患者.
  • 这项研究为未来对自动化客观疼痛管理系统的研究提供了坚实的基础.