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Blood and Nerve Supply to the Bones01:29

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Bones are dynamic organs that require a rich supply of oxygen and nutrients. Around 5% to 10% of the cardiac output supplies blood to the bones. A typical long bone has three main sources: the nutrient artery, the metaphyseal and epiphyseal arteries, and the periosteal arteries.
Nutrient Artery
The nutrient artery is the main blood vessel that enters the diaphysis via the nutrient foramen. While most long bones have only one nutrient foramen, large bones, such as the femur, may have two. This...
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用机器人进行骨折后康复训练的膝关节硬度的疼痛状态分类

Yang Zheng1,2, Dimao He1,2, Yuan He3

  • 1School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

Sensors (Basel, Switzerland)
|August 28, 2025
PubMed
概括

电肌图 (EMG) 信号可以检测膝盖康复运动训练期间的疼痛水平. 这可以准确地估计最大角度位置 (maxAP),以改善患者骨折后的恢复.

关键词:
电肌图骨折的情况没有疼痛.模式识别运动范围

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科学领域:

  • 生物医学工程
  • 康复科学
  • 临床生物力学

背景情况:

  • 骨折后膝关节硬度限制运动范围 (ROM).
  • 最佳的运动训练需要将膝盖曲到最大角度位置 (maxAP),从而产生适当的疼痛水平.
  • 目前确定maxAP的方法依赖于患者的主观疼痛报告,这种疼痛报告可能是可变的.

研究的目的:

  • 调查在膝盖康复期间使用电肌图 (EMG) 活动检测最大角度位置 (maxAP) 的可行性.
  • 将maxAP检测转换为疼痛与无痛状态的二元分类.

主要方法:

  • 实验I:在日常运动训练中记录了12名骨折后患者的膝盖曲器和延伸器的电磁图信号.
  • 提取了EMG特征以区分疼痛和无痛状态.
  • 实验II:使用机器学习模型 (SVM,随机森林) 在7名患者的膝盖康复机器人上测试了maxAP估计.

主要成果:

  • 电磁波特征显示疼痛和无痛状态之间存在显著差异.
  • 支持矢量机 (SVM) 达到87.90%±4.55%的精度,偏差为6.5°±5.1°.
  • 随机森林模型实现了89.10%±4.39%的精度,偏差为4.5°±3.5°.

结论:

  • 疼痛诱导的EMG信号可以准确地分类疼痛状态以估计骨折后的运动能力.
  • 这种方法有可能提高机器人技术在骨折康复中的应用.
  • 基于EMG的疼痛检测提供了指导康复强度和改善ROM恢复的客观措施.