Sagaidachnyi A A, Fomin A V, Usanov D A, Skripal A V
Department of Nano and Biomedical Technology, Saratov State University, Astrakhanskaya st. 83, Saratov 410012, Russia.
Physiol Meas. 2017 Feb;38(2):272-288. doi: 10.1088/1361-6579/aa4eaf. Epub 2017 Jan 18.
The determination of the relationship between skin blood flow and skin temperature dynamics is the main problem in thermography-based blood flow imaging. Oscillations in skin blood flow are the source of thermal waves propagating from micro-vessels toward the skin's surface, as assumed in this study. This hypothesis allows us to use equations for the attenuation and dispersion of thermal waves for converting the temperature signal into the blood flow signal, and vice versa. We developed a spectral filtering approach (SFA), which is a new technique for thermography-based blood flow imaging. In contrast to other processing techniques, the SFA implies calculations in the spectral domain rather than in the time domain. Therefore, it eliminates the need to solve differential equations. The developed technique was verified within 0.005-0.1 Hz, including the endothelial, neurogenic and myogenic frequency bands of blood flow oscillations. The algorithm for an inverse conversion of the blood flow signal into the skin temperature signal is addressed. The examples of blood flow imaging of hands during cuff occlusion and feet during heating of the back are illustrated. The processing of infrared (IR) thermograms using the SFA allowed us to restore the blood flow signals and achieve correlations of about 0.8 with a waveform of a photoplethysmographic signal. The prospective applications of the thermography-based blood flow imaging technique include non-contact monitoring of the blood supply during engraftment of skin flaps and burns healing, as well the use of contact temperature sensors to monitor low-frequency oscillations of peripheral blood flow.
确定皮肤血流与皮肤温度动态之间的关系是基于热成像的血流成像中的主要问题。本研究假设皮肤血流的振荡是热波从微血管向皮肤表面传播的源头。这一假设使我们能够使用热波衰减和色散方程将温度信号转换为血流信号,反之亦然。我们开发了一种光谱滤波方法(SFA),这是一种基于热成像的血流成像新技术。与其他处理技术不同,SFA意味着在频域而非时域进行计算。因此,它无需求解微分方程。所开发的技术在0.005 - 0.1赫兹范围内得到了验证,包括血流振荡的内皮、神经源性和肌源性频段。文中讨论了将血流信号反向转换为皮肤温度信号的算法。文中展示了袖带阻断期间手部和背部加热期间足部的血流成像示例。使用SFA处理红外(IR)热成像图使我们能够恢复血流信号,并与光电容积脉搏波信号波形实现约0.8的相关性。基于热成像的血流成像技术的潜在应用包括在皮瓣移植和烧伤愈合过程中对血液供应进行非接触监测,以及使用接触式温度传感器监测外周血流的低频振荡。