Swamy Gokul, Ling Qi, Li Tongtong, Mukkamala Ramakrishna
Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA.
Am J Physiol Heart Circ Physiol. 2007 May;292(5):H2257-64. doi: 10.1152/ajpheart.01159.2006. Epub 2007 Jan 5.
We have developed a new technique to estimate the clinically relevant aortic pressure waveform from multiple, less invasively measured peripheral artery pressure waveforms. The technique is based on multichannel blind system identification in which two or more measured outputs (peripheral artery pressure waveforms) of a single-input, multi-output system (arterial tree) are mathematically analyzed so as to reconstruct the common unobserved input (aortic pressure waveform) to within an arbitrary scale factor. The technique then invokes Poiseuille's law to calibrate the reconstructed waveform to absolute pressure. Consequently, in contrast to previous related efforts, the technique does not utilize a generalized transfer function or any training data and is therefore entirely patient and time specific. To demonstrate proof of concept, we have evaluated the technique with respect to four swine in which peripheral artery pressure waveforms from the femoral and radial arteries and a reference aortic pressure waveform from the descending thoracic aorta were simultaneously measured during diverse hemodynamic interventions. We report that the technique reliably estimated the entire aortic pressure waveform with an overall root mean squared error (RMSE) of 4.6 mmHg. For comparison, the average overall RMSE between the peripheral artery pressure and reference aortic pressure waveforms was 8.6 mmHg. Thus the technique reduced the RMSE by 47%. As a result, the technique also provided similar improvements in the estimation of systolic pressure, pulse pressure, and the ejection interval. With further successful testing, the technique may ultimately be employed for more precise monitoring and titration of therapy in, for example, critically ill and hypertension patients.
我们开发了一种新技术，可从多个经微创测量的外周动脉压力波形中估算出具有临床相关性的主动脉压力波形。该技术基于多通道盲系统识别，即对单输入多输出系统（动脉树）的两个或多个测量输出（外周动脉压力波形）进行数学分析，以便将共同的未观测输入（主动脉压力波形）重构到任意比例因子范围内。然后，该技术调用泊肃叶定律将重构波形校准为绝对压力。因此，与之前的相关研究不同，该技术不使用广义传递函数或任何训练数据，因此完全针对特定患者和特定时间。为了证明概念的可行性，我们对四只猪进行了评估，在不同的血流动力学干预过程中，同时测量了股动脉和桡动脉的外周动脉压力波形以及降主动脉的参考主动脉压力波形。我们报告称，该技术能够可靠地估算整个主动脉压力波形，总体均方根误差（RMSE）为4.6 mmHg。作为对比，外周动脉压力波形与参考主动脉压力波形之间的平均总体RMSE为8.6 mmHg。因此，该技术将RMSE降低了47%。结果，该技术在收缩压、脉压和射血间期的估算方面也有类似的改善。经过进一步的成功测试，该技术最终可能用于对危重症患者和高血压患者等进行更精确的治疗监测和滴定。
