Martin J F, Volfson L B, Kirzon-Zolin V V, Schukin V G
Eli Lilly and Company, Medical Devices and Diagnostics Division, Indianapolis IN 46285.
IEEE Trans Biomed Eng. 1994 Oct;41(10):913-20. doi: 10.1109/10.324522.
The shape of the arterial pressure waveform is a non-linear function of stroke volume, heart rate and many other cardiovascular parameters. Previous attempts have been made to exploit this relationship and derive cardiac output (CO) from the arterial pressure waveform. These classical "pulse-contour" methods utilized simplifying linear assumptions, as a result they failed to adequately estimate CO over a sufficiently wide range of hemodynamic conditions. We have applied pattern recognition and image processing techniques to the problem of deriving CO from the arterial pressure waveform, thereby eliminating the need for simplifying assumptions. Computer simulations were used to develop the basic pattern recognition algorithms and compare their performance with that of published classical "pulse-contour" methods. Animal models were subsequently used to demonstrate proof of the concept. For over 200,000 individual heart beats, covering a wide range of hemodynamic conditions, the mean error, in calculated CO compared to ultrasonic flow probe determined CO, was 2.8% with a standard deviation of 9.8%.
动脉压力波形的形状是每搏输出量、心率和许多其他心血管参数的非线性函数。此前曾有人尝试利用这种关系，从动脉压力波形中推导心输出量（CO）。这些经典的“脉搏轮廓”方法采用了简化的线性假设，因此未能在足够广泛的血流动力学条件范围内充分估计CO。我们已将模式识别和图像处理技术应用于从动脉压力波形推导CO的问题，从而无需进行简化假设。通过计算机模拟来开发基本的模式识别算法，并将其性能与已发表的经典“脉搏轮廓”方法进行比较。随后使用动物模型来证明该概念。对于超过200,000次的个体心跳，涵盖广泛的血流动力学条件，与超声流量探头测定的CO相比，计算得出的CO的平均误差为2.8%，标准差为9.8%。
