压电微的自传感:在有限的嵌入式系统上通过人工智能方法检测气泡
Kristjan Axelsson1, Mohammadhossien Sheikhsarraf1, Christoph Kutter1
1Fraunhofer EMFT, Hansastr. 27d, 80686 Munich, Germany.
Sensors (Basel, Switzerland)
|June 27, 2025
概括
这项研究介绍了一种新型的自我传感微系统,该系统使用人工智能检测气泡,确保准确的药物输送. 由人工智能驱动的压电隔膜准确地识别气泡,改进了微剂量系统.
科学领域:
- 生物医学工程 生物医学工程
- 嵌入式系统 嵌入式系统
- 人工智能的人工智能
背景情况:
- 压电隔膜微中的气泡会导致微升药物分配不准确,这对于胰岛素等缩药物至关重要.
- 现有的气泡检测方法增加了系统的复杂性,尺寸和成本.
- 需要一种使用压电隔膜固有的能力的自我传感方法.
研究的目的:
- 开发一种自传感微系统,用于准确检测气泡.
- 将人工智能 (AI) 方法集成到嵌入式系统中,用于实时传感.
- 为了减少微剂量系统的复杂性和成本.
主要方法:
- 开发了一种自传感微,通过利用压电隔膜在启动过程中的传感能力来实现这种功能.
- 使用STM32G491RE微控制器实现了一个电子电路来放大和采样压电陶的加载电流.
- 训练有素的人工智能算法 (TensorFlow, scikit-learn) 在来自11个注入气泡的微的数据集上,通过网格搜索优化超参数.
- 在嵌入式系统上部署训练有素的AI模型,使用STM32Cube.AI框架.
主要成果:
- 在STM32G491RE微控制器上部署的AI模型实现了99.41%的气泡检测精度.
- 嵌入式系统模型具有很小的内存 (15.23 kB) 和快速运行时间 (182 μs).
- 自传感方法成功地消除了对外部传感器的需求,简化了微剂量系统.
结论:
- 由人工智能驱动的自传感微有效地检测高精度和高效率的气泡.
- 这种创新方法显著提高了可靠性,并降低了便携式微剂量系统的成本.
- 开发的系统提供了一个有前途的解决方案,用于准确的管理关键药物,如胰岛素.
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