贝叶斯优化为机器人以程序前规划为基础的计划 左心室附属体闭塞
Ran Hao1, Yuttana Itsarachaiyot1, M Cenk Çavuşoğlu1
1Department of Electrical, Computer, and Systems Engineering, Case Western Reserve University, Cleveland, OH.
概括
这项研究引入了贝叶斯优化方法,用于机器人左心房附属物阻塞规划. 它优化了设备植入轨迹,以减少心房动患者中风风险.
科学领域:
- 医疗机器人 医疗机器人
- 心血管干预 心血管干预
- 计算优化计算优化
背景情况:
- 心房动增加了通过血栓栓塞的中风风险.
- 左心房尾阻塞 (LAAAO) 是一个关键的干预措施,以减轻这种风险.
- 有效的LAAAO需要精确的程序前规划,以实现最佳的设备植入.
研究的目的:
- 为机器人LAAAO提出一种基于贝叶斯优化 (BO) 的新的程序前规划方法.
- 为了提高识别最佳跨septal穿孔部位和阻塞轨迹的效率和准确性.
- 通过智能规划,提高LAAAO程序的成功率.
主要方法:
- 为机器人LAAAO开发基于BO的计划器.
- 顺序优化跨septal穿孔位置在卵巢.
- 使用代线性二次调节器进行局部轨迹优化.
- 在真实心脏解剖模型的模拟环境中进行评估.
主要成果:
- 骨组织规划器有效地采样并优化了横septal穿孔位置.
- 有效地执行了阻塞轨迹的局部优化.
- 该方法在模拟的心脏环境中证明了可行性.
结论:
- 建议的贝叶斯优化方法为机器人LAAAO中的程序前规划提供了一种有效的方法.
- 这种智能规划可以提高程序的成功和患者的安全.
- 需要在临床环境中进一步验证.
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