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  3. 生物力学和生理学参数作为生物标志物的证据,以区分使用传感器设备的非特异性部疼痛和无特异性部疼痛的个体:系统性审查与元分析
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  3. 生物力学和生理学参数作为生物标志物的证据,以区分使用传感器设备的非特异性部疼痛和无特异性部疼痛的个体:系统性审查与元分析

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生物力学和生理学参数作为生物标志物的证据,以区分使用传感器设备的非特异性部疼痛和无特异性部疼痛的个体:系统性审查与元分析

Ali Cihan Dagli1, Beyza Yazgan Dagli2, Emad Al-Yahya3

  • 1School of Health Sciences, University of Nottingham, Nottingham, United Kingdom; Cyber-physical Health and Assistive Robotics Technologies Research Group, University of Nottingham, United Kingdom.

The journal of pain
|September 6, 2025

在PubMed 上查看摘要

概括
此摘要是机器生成的。

不特定的部疼痛与可测量的运动和生理变化有关. 基于传感器的生物机械和生理标志物有望识别部疼痛并改善评估.

关键词:
生物标志物生物机械现象电肌图部疼痛生理现象

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科学领域:

  • 生物医学工程
  • 肌肉骨健康
  • 康复科学

背景情况:

  • 部疼痛是一个普遍的全球健康问题,由于未确定的原因,通常被归类为非特异性疼痛.
  • 疼痛可以显著影响运动模式和生理功能,表明潜在的客观生物标记.
  • 传感器技术的进步允许精确,客观地测量这些生物机械和生理变化.

研究的目的:

  • 系统地审查和综合传感器测量生物机械和生理参数的证据,以区分非特异性部疼痛与对照.
  • 评估这些参数在识别非特异性部疼痛的个体中的区分性表现.
  • 探索这些参数作为临床评估和康复的客观生物标志物的潜力.

主要方法:

  • 在六个主要数据库中进行了系统的文献搜索,包括灰色文献和参考列表.
  • 包括53项观察性研究进行定性综合,其中27项正在进行元分析.
  • 使用机器学习和统计技术来评估所识别的参数的差异性性能.

主要成果:

  • 分析证实了非特异性部疼痛与部运动范围减少,关节位置感受受受损以及步态参数变化 (步长,步速) 之间的强烈联系.
  • 增加的肌肉电动图和心率变化降低也与部疼痛有显著的关联.
  • 使用步态和电肌谱参数,特别是机器学习,分类研究显示了高分辨率 (71.9-90%的准确性).

结论:

  • 与非特异性部疼痛相关的生物机械和生理变化可以作为客观生物标志物.
  • 这些来自传感器的参数显示出提高部疼痛临床评估的巨大潜力.
  • 需要进一步验证,以充分确定这些生物标志物的实用性,以指导康复战略.