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超声波辅助骨切割参数对动物骨切割时间和温度的影响
Mazaher Aghdasta1, Maghsoud Shalvandi1
1Department of Mechanical Engineering, University of Tabriz, Iran.
概括
这项关于超声波骨切割的研究发现,更高的振动幅度和刃刀片显著减少了和老鼠股骨的切割时间和温度. 人工神经网络 (ANN) 模型准确预测了这些结果.
科学领域:
- 生物医学工程 生物医学工程
- 手术技术 手术技术
- 材料科学 材料科学 材料科学
背景情况:
- 优化骨切割对于手术效率和患者的结果至关重要.
- 了解输入参数对切割性能的影响对于开发先进的外科工具至关重要.
研究的目的:
- 分析输入参数对超声波骨切割切割时间和温度的影响.
- 为了优化超声波外科刀设计和骨切割过程.
- 使用人工神经网络 (ANN) 模型预测切割反应.
主要方法:
- 使用Abaqus软件设计和模拟了两个超声波外科手术刀.
- 在和老鼠的股骨上进行了切骨实验,使用潮湿和干燥模式.
- 使用了不同振动幅度的刀和尖刀片 (18,22.5,27μm) 和一个ANN模型进行分析.
主要成果:
- 增加的振动幅度 (18~27微米) 将切割时间缩短了30~40%和切割温度缩短了19~30%.
- 刃刀片的切割时间缩短了52-72%,温度降低了50-70%,相比于刃刀片.
- ANN模型的预测与切割时间和温度的实验数据有很强的一致性.
结论:
- 更高的振动幅度和刀片在超声波骨切割过程中有效地减少切割时间和温度.
- 开发的ANN模型为预测骨切割性能提供了可靠的工具.
- 这些发现为优化超声波外科刀具设计和在骨科手术中的应用提供了洞察力.
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