标题： 一种开源的连续动脉血压测量传感器验证系统 显示英文标题

标题： An Open Source Validation System for Continuous Arterial Blood Pressure Measuring Sensors

摘要： 测量血压波形正成为一个研究更为频繁的领域。 传感器技术的发展开辟了许多能够测量高质量信号的新途径。 开发这种目标特定的传感器可能耗时、昂贵，并且难以用已知且一致的波形进行测试或验证。 本文介绍了一个开源的血压波形模拟器以及一个开源的Python验证包，以降低早期传感器开发和研究的成本。 该模拟器主要由3D打印部件组成，这项技术已成为一种广泛可用且廉价的解决方案。 模拟器的核心部分是一个3D打印的凸轮，可以根据真实的血压波形生成。 验证框架可以详细比较用于设计凸轮的信号波形与被验证传感器测得的时间序列之间的差异。 实验结果表明，所提出的模拟器在短期和长期使用中表现出了稳健性和准确性，因为它能始终如一地准确产生信号波形。 为了验证这一解决方案，我们使用了一种之前已被证明能够测量桡动脉高精度血压波形的3D力传感器。 结果显示，所测量波形与标称波形之间具有高度相似性，这意味着对比归一化信号，RMSE值范围为$0.0276 \pm 0.0047$至$0.0212 \pm 0.0023$，皮尔逊相关系数范围为$0.9933 \pm 0.0027$至$0.9978 \pm 0.0005$。 我们的验证框架可在https://github.com/repat8/cam-bpw-sim获取。 允许重现本解决方案的硬件框架可在https://github.com/repat8/cam-bpw-sim-hardware获取。 整个设计是一个开源项目，使用了免费软件开发而成。 显示英文摘要

摘要： Measuring the blood pressure waveform is becoming a more frequently studied area. The development of sensor technologies opens many new ways to be able to measure high-quality signals. The development of such an aim-specific sensor can be time-consuming, expensive, and difficult to test or validate with known and consistent waveforms. In this paper, we present an open source blood pressure waveform simulator with an open source Python validation package to reduce development costs for early-stage sensor development and research. The simulator mainly consists of 3D printed parts which technology has become a widely available and cheap solution. The core part of the simulator is a 3D printed cam that can be generated based on real blood pressure waveforms. The validation framework can create a detailed comparison between the signal waveform used to design the cam and the measured time series from the sensor being validated. The presented simulator proved to be robust and accurate in short- and long-term use, as it produced the signal waveform consistently and accurately. To validate this solution, a 3D force sensor was used, which was proven earlier to be able to measure high-quality blood pressure waveforms on the radial artery at the wrist. The results showed high similarity between the measured and the nominal waveforms, meaning that comparing the normalized signals, the RMSE value ranged from $0.0276 \pm 0.0047$ to $0.0212 \pm 0.0023$, and the Pearson correlation ranged from $0.9933 \pm 0.0027$ to $0.9978 \pm 0.0005$. Our validation framework is available at https://github.com/repat8/cam-bpw-sim. Our hardware framework, which allows reproduction of the presented solution, is available at https://github.com/repat8/cam-bpw-sim-hardware. The entire design is an open source project and was developed using free software.