CN112806992A - Tissue oxygen saturation monitoring system and method of self-adaptive spatial resolution spectrum - Google Patents
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Abstract
The invention belongs to the technical field of oxyhemoglobin saturation monitoring, and relates to a tissue oxyhemoglobin saturation monitoring system capable of self-adapting to spatial resolution spectrum, which comprises a light source module, a driving module, a monitoring module, a signal amplification module, a signal conversion module, a control module and a calculation module, wherein the driving module is connected with the monitoring module, the monitoring module is connected with the light source module and the signal amplification module, the signal amplification module is connected with the signal conversion module, and the control module is respectively connected with the driving module, the monitoring module and the signal conversion module and uploads data to the calculation module arranged on a PC. The invention considers the defect of tissue nonuniformity, the algorithm considers the condition of tissue nonlinearity, and the calculation precision is higher than that of tissue blood oxygen saturation obtained by the traditional spatial resolution spectrum algorithm.
Description
Technical Field
The invention belongs to the technical field of oxyhemoglobin saturation monitoring, and relates to a tissue oxyhemoglobin saturation monitoring system and method of self-adaptive spatial resolution spectrum.
Background
Oxygen is one of the substances necessary for maintaining life activities, and oxygen inhaled into the lungs of human beings maintains the normal oxygen supply of cells through various parts of the body where blood is delivered. Generally, the degree of binding between blood and oxygen in a blood vessel of a tissue may reflect the oxygenation of the tissue, and may also dynamically reflect the oxygenation of the tissue in conjunction with monitoring an indicator of tissue oxygen saturation. Tissue oxygen saturation is an important parameter of the local microcirculation of the human body, and is measured by the weighted average of the blood oxygen content in the venules and arterioles of the human body, about 60 to 70 percent of the oxygen supply in the tissues is generated by the diffusion of the microcirculation, and the normal supply of oxygen is a precondition for the normal microcirculation. Tissue homeostasis requires microcirculation to regulate blood flow and to deliver oxygen to maintain, and local oxygen supply deficiencies resulting from an imbalance in homeostasis can induce tissue pathology. The processes of foot circulatory disturbance, tumor formation, flap transplantation, etc. of a diabetic patient cause the local microcirculation of tissues to change, thereby causing the oxygen saturation of the tissues to change. Besides, in the aspects of monitoring the oxygen content of brain tissues, monitoring the oxygen content of muscle tissues and the like, the tissue oxygen saturation is required to be effectively obtained in real time so as to obtain information about tissue physiology and pathology and take corresponding treatment measures.
In clinical medicine, the blood oxygen saturation is an important parameter for judging whether a human respiratory system is normal or not and whether a human biological tissue circulatory system is in an anoxic state or not, and plays an irreplaceable role in the processes of potential disease diagnosis, health monitoring, medical rehabilitation and the like of a human body.
In most cases, circulatory disturbance of human tissues causes hypoxia, which causes serious damage to the nervous system and motor functions of the human body and is irreparable, such as brain tissue hypoxia.
The near infrared spectrum technology is a noninvasive optical technology widely applied to the assessment of tissue metabolism, and can characterize the transportation and utilization of oxygen by microcirculation. With the development of scientific technology, the near infrared light of 650- & lt 950 & gtnm is called an optical window of biological tissues. Near infrared spectroscopy has been used for over 40 years in monitoring tissue oxygen, blood oxygen, and the like. Conventional oximeters use photoplethysmography to measure the oxygen saturation in arteries, which is a measure of the respiratory condition of a patient. However, the photoplethysmography cannot measure the blood oxygen saturation of the vein, and is not suitable for a site without pulse wave.
In tissue oxygen saturation monitoring, Spatially Resolved Spectroscopy (SRS) based algorithms are widely used. In 1999, the Japan Korea company developed a tissue oxygen monitor capable of measuring the relative change of tissue oxygen content based on the algorithm of spatial resolution spectrum. The professor team of Dinghai eosin of Qinghua university breaks through the foreign technical monopoly in 2000, and a domestic organization oxygen monitoring device is independently developed based on an SRS algorithm, and the device is already cooperated with Suzhou Aiqin company for production and popularization. Currently, the organization oxygen monitor that is being withdrawn from Edwardsiella, USA, is also based on the SRS algorithm.
The traditional tissue oxygen saturation calculation method of spatially resolved spectroscopy assumes that the tissue is uniform, however, the tissue is not, and the tissue absorbs near infrared light differently in different regions. Therefore, the conventional tissue oxygen saturation algorithm of spatially resolved spectroscopy may bring errors. Tissue oximetry probes need to be designed separately for people of different body weights, which does not add cost or complexity to the use.
Disclosure of Invention
The invention aims to provide a tissue oxygen saturation monitoring system and method of self-adaptive spatial resolution spectrum, which consider the defect of tissue nonuniformity, take the nonlinear condition of the tissue into consideration, and have higher calculation accuracy than the tissue oxygen saturation obtained by the traditional spatial resolution spectrum algorithm.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a tissue oxygen saturation monitoring system of self-adaptive spatial resolution spectrum, which comprises a light source module, a driving module, a monitoring module, a signal amplification module, a signal conversion module, a control module and a calculation module, wherein the light source module is connected with the driving module, the monitoring module is connected with the signal amplification module, the signal amplification module is connected with the signal conversion module, and the control module is respectively connected with the driving module, the monitoring module and the signal conversion module and uploads data to the calculation module arranged on a PC;
the light source module is used for emitting light with the wavelength of 760nm or 840 nm;
the driving module is used for driving a light source in the light source module to emit light and switching the light source according to preset time;
the monitoring module consists of a plurality of detectors and is used for collecting light intensity signals reflected by the light source after reaching the detection part;
the calculation module is used for calculating the tissue oxygen saturation in the monitoring process by adopting a maximum coefficient determination method.
Preferably, the preset time is 500 ms.
The invention also provides a tissue oxygen saturation monitoring method based on the self-adaptive spatial resolution spectrum of the tissue oxygen saturation monitoring system, which comprises the following steps:
step 1: arranging n detectors in a monitoring module, and grouping every five adjacent detectors into a group;
step 2: the driving module drives the light source module to turn on a light source with the wavelength of 760nm and turn off the light source with the wavelength of 840 nm;
and step 3: the detector starts to collect light intensity signals reflected by the light source after reaching the detection part;
and 4, step 4: the light intensity collected by the detector is amplified by the signal amplification module, and the light signal is converted into an electric signal by the signal conversion module, transmitted to the control module and then uploaded to the calculation module on the PC;
and 5: the calculation module performs linear regression on the monitoring data of the first group of detectors to obtain the corresponding slope k of the monitoring data of the first group of detectors under a 760nm light source1And determining the coefficient
Step 6: when the driving module is presetThe light source module is driven to turn on a light source with the wavelength of 840nm, the light source with the wavelength of 760nm is turned off, the step 3 to the step 4 are repeated, the calculation module performs linear regression on the monitoring data of the first group of detectors, and the slope k corresponding to the monitoring data of the first group of detectors under the 840nm light source is obtained2And determining the coefficient
And 7: the whole monitoring process is circulated to obtain n-4 determining coefficientsAnd n-4 decision coefficientsWill determine the coefficientsAnd determining the coefficientSlope k corresponding to the respective maximum1And slope k2For solving for tissue oxygen saturation during monitoring.
Compared with the prior art, the invention has the beneficial effects that:
the tissue oxygen saturation monitoring method of the self-adaptive spatial resolution spectrum considers the defect of tissue nonuniformity, the algorithm considers the condition of tissue nonlinearity, the calculation accuracy is higher than that of the tissue oxygen saturation obtained by the traditional spatial resolution spectrum algorithm, the tissue oxygen saturation can be monitored in a non-invasive manner, the pain of a patient is relieved, and the defect of cross infection caused by bed monitoring is avoided.
Compared with the existing blood oxygen monitor, the dual-wavelength blood oxygen probe can be respectively designed according to people with different weights so as to be self-adaptive to the people with different weights, and the applicability is wide; the system can be suitable for monitoring the fields of muscular oxygen, cerebral oxygen and the like, and can also be applied to the fields of free flap postoperative monitoring, foot circulation problem monitoring of diabetes patients, research on the relation between a tumor formation mechanism and oxygen saturation and the like.
Drawings
Fig. 1 is a system block diagram of a tissue oxygen saturation monitoring system of the present invention.
Fig. 2 is a schematic circuit diagram of the connections between the modules of the tissue oxygen saturation monitoring system of the present invention.
Fig. 3 is a graph of changes in tissue oxygen saturation calculated by a monitoring process in accordance with an embodiment of the present invention.
Detailed Description
The following examples are intended to illustrate the invention, but are not intended to limit the scope of the invention. Unless otherwise specified, the technical means used in the examples are conventional means well known to those skilled in the art. The test methods in the following examples are conventional methods unless otherwise specified.
The behavior of photons in tissue can be described using diffusion approximation equations in the principles of conventional Spatially Resolved Spectroscopy (SRS). Assuming that the tissue is a semi-infinite homogeneous medium and the signal from the light source is an impulse function, the intensity of the light distributed over the surface of the tissue can be expressed by the following equation:
wherein: r is the intensity of the reflected light, x represents the position from the light source, t represents time, λ represents the wavelength of the light, μsIs the scattering coefficient, muaIs the absorption coefficient, c is the speed of light, D is 1/3 (mu)a+μs) Is the scattering coefficient.
Then the intensity of the light monitored at x is the integral of R (x, t, λ) over t and the attenuation of the light is defined as the logarithm of the intensity, so the value of the attenuation of the intensity a (x, λ) can be described by the following equation:
the attenuation value of the light intensity differentiates x to obtain the rule of light intensity space resolution, and the analytical solution is shown as (3), which is the principle of monitoring the tissue oxygen saturation by the space resolution spectrum.
Since oxyhemoglobin and reduced hemoglobin in tissue are the main substances for near-infrared light absorption, the absorption coefficient can be expressed as follows:
wherein:is the extinction coefficient of reduced hemoglobin at wavelength lambda,is the extinction coefficient, C, of oxyhaemoglobin having a wavelength of lambdaHbIs the concentration of the reduced hemoglobin,is the concentration of oxyhemoglobin. At different wavelengths, musMay be approximately equal.
Tissue oxygen saturation can be obtained in combination with equation (5):
in the process of solving the tissue oxygen saturation degree by using the formulas (5) and (6), the key point is how to obtainWhen the attenuation of the light intensity varies linearly, the slope can replace the value of the differential. But if the attenuation of the light intensity is not linearly changing, there will be an error in using the slope instead of the differentiation. The invention provides a tissue oxygen saturation monitoring system and a tissue oxygen saturation monitoring method based on a spatial resolution spectrum technology based on the problem of calculation errors of the spatial resolution spectrum technology.
Example one
As shown in fig. 1, the system for monitoring tissue oxygen saturation based on adaptive spatial resolution spectroscopy of the present invention includes a light source module 101, a driving module 102, a monitoring module 103, a signal amplification module 104, a signal conversion module 105, a control module 106 and a calculation module 107, wherein the light source module 101 is connected to the driving module 102, the monitoring module 103 is connected to the signal amplification module 104, the signal amplification module 104 is connected to the signal conversion module 105, and the control module 106 is respectively connected to the driving module 102, the monitoring module 103 and the signal conversion module 105, and uploads data to the calculation module disposed on a PC;
the light source module 101 is used for emitting light with the wavelength of 760nm or 840 nm;
the driving module 102 is used for driving the light source in the light source module to emit light and switching the light source according to preset time;
the monitoring module 103 is composed of a plurality of detectors and is used for collecting light intensity signals reflected by the light source after reaching the detection part;
the calculation module 107 is used for calculating the tissue oxygen saturation in the monitoring process by adopting a maximum decision coefficient method.
In one possible embodiment, the predetermined time is 500 ms.
The tissue oxygen saturation monitoring method based on the self-adaptive spatial resolution spectrum of the system comprises the following steps:
step 1: arranging n detectors in the monitoring module 103, and grouping every five adjacent detectors into a group;
step 2: the driving module 102 drives the light source module 101 to turn on a light source with a wavelength of 760nm and turn off a light source with a wavelength of 840 nm;
and step 3: the detector starts to collect light intensity signals reflected by the light source after reaching the detection part;
and 4, step 4: the light intensity collected by the detector is amplified by the signal amplification module 104, and the light signal is converted into an electric signal by the signal conversion module 105, transmitted to the control module 106 and then uploaded to the calculation module on the PC;
and 5: the calculation module 107 performs linear regression on the first group of detector monitoring data to obtain the corresponding slope k of the first group of detector monitoring data under the 760nm light source1And determining the coefficient
Step 6: the driving module 102 drives the light source module 101 to turn on the light source with the wavelength of 840nm according to the preset time, turns off the light source with the wavelength of 760nm, the steps 3-4 are repeated, the calculation module performs linear regression on the monitoring data of the first group of detectors, and the slope k corresponding to the monitoring data of the first group of detectors under the 840nm light source is obtained2And determining the coefficient
And 7: the whole monitoring process is circulated to obtain n-4 determining coefficientsAnd n-4 decision coefficientsWill determine the coefficientsAnd determining the coefficientSlope k corresponding to the respective maximum1And slope k2Substituting equation (5) and equation (6) is used to solve for tissue oxygen saturation during monitoring.
In the step 5 of the invention, the linear regression adopts a least square method, and the calculation formula is as follows:
wherein: k is the slope of the linear regression and b is the longitudinal intercept.
Determining the coefficient r2Generally, the fitting degree of the linear regression equation and the original data is measured, and the calculation formula is as follows:
it should be noted that the tissue oxygen saturation monitoring system of the present invention further includes a power module for providing operating voltage to the modules.
As an implementable mode, the light source module adopts a dual-wavelength light source customized by hamamatsu; the driving module controls the ULN2003 to drive the light source by adopting a GPIO port of the STM32, so that the purpose of switching the light source is achieved; the monitoring module 103 consists of 12 BPW34S photodetectors; the signal amplification module 104 adopts an AD626 chip to form a module; the signal conversion module 105 adopts the built-in ADC of the STM32 to complete the conversion from the analog signal to the digital signal; the control module 106 employs STM 32; the calculation module 107 adopts upper computer software written by labview. The schematic circuit diagram of the connection between the modules of the tissue oxygen saturation monitoring system of the invention is shown in fig. 2. A tissue oxygen saturation monitoring system is set up, the working voltage is 5V, and monitoring basic data are shown in table 1. For one subject, the venous occlusion experiment was performed as described below, with the self-made probe (i.e., light source module 101 and monitoring module 103) placed on the forearm surface of the subject, and the cuff of a mercury sphygmomanometer was used to attach to the forearm of the subject. Starting the monitoring system, inflating the cuff after 40s, blocking the vein when the mercury column of the 90s mercury sphygmomanometer reaches 90mHg, deflating the cuff of the sphygmomanometer after lasting 2min, and continuously detecting the blood oxygen saturation after the sphygmomanometer is deflated, wherein the whole process lasts for 6 min. The 760nm and 840nm wavelength light sources were switched every 500ms and monitored continuously for 6 minutes, with the monitoring data shown in table 2.
TABLE 1 monitoring of basic data
TABLE 2 monitoring data corresponding to different groups
TABLE 3 calculation results for different groups
As can be seen from Table 3, according to the algorithm of the present invention, the slope corresponding to the maximum decision coefficient is found and used instead of the slopeIs theoretically optimal. When the coefficient is maximum, the corresponding slopes are respectively K1=-0.5906、K2-0.5622. Will K1、K2Substituted into equations (5) and (6), respectivelyAndthe tissue oxygen saturation can be solved, and the calculation result is shown in table 4 and fig. 3.
TABLE 4 calculated tissue oxygen saturation during monitoring time
Before vein occlusion, the tissue oxygen saturation is high, in the vein occlusion, venous blood cannot flow back into a body, the oxygen content in an arm is reduced, the tissue oxygen saturation is reduced, after a vein occlusion experiment is finished, the venous blood flows back into the body, the oxygen content in the arm is increased, and the tissue oxygen saturation is increased. As can be seen from fig. 3, the calculation result is the same as the analysis result, which indicates that the tissue oxygen saturation monitoring algorithm of the adaptive spatial resolution spectrum provided by the present invention can effectively monitor the arm tissue oxygen saturation in real time.
The variance is used for measuring the deviation degree of the calculation result and reflecting the accuracy of the calculation result, through calculation, the variance of the saturation of the tissue sample measured by the algorithm is 0.0012%, and the variance of the collected data obtained by using the traditional SRS algorithm is 0.0187%. Therefore, the error of the algorithm provided by the invention is smaller by one order of magnitude than that of the traditional algorithm, and the calculation result precision is higher.
The above-mentioned embodiments are merely preferred embodiments of the present invention, which are merely illustrative and not restrictive, and it should be understood that other embodiments may be easily made by those skilled in the art by replacing or changing the technical contents disclosed in the specification, and therefore, all changes and modifications that are made on the principle of the present invention should be included in the scope of the claims of the present invention.
Claims (3)
1. A tissue oxygen saturation monitoring system of self-adaptive spatial resolution spectrum is characterized by comprising a light source module, a driving module, a monitoring module, a signal amplification module, a signal conversion module, a control module and a calculation module, wherein the light source module is connected with the driving module, the monitoring module is connected with the signal amplification module, the signal amplification module is connected with the signal conversion module, and the control module is respectively connected with the driving module, the monitoring module and the signal conversion module and uploads data to the calculation module arranged on a PC;
the light source module is used for emitting light with the wavelength of 760nm or 840 nm;
the driving module is used for driving a light source in the light source module to emit light and switching the light source according to preset time;
the monitoring module consists of a plurality of detectors and is used for collecting light intensity signals reflected by the light source after reaching the detection part;
the calculation module is used for calculating the tissue oxygen saturation in the monitoring process by adopting a maximum coefficient determination method.
2. The adaptive spatially resolved spectroscopic tissue oxygen saturation monitoring system of claim 1 wherein said predetermined time is 500 ms.
3. The tissue oxygen saturation monitoring method based on the adaptive space-resolved spectroscopy of the tissue oxygen saturation monitoring system according to any one of claims 1 to 2, characterized by comprising the following steps:
step 1: arranging n detectors in a monitoring module, and grouping every five adjacent detectors into a group;
step 2: the driving module drives the light source module to turn on a light source with the wavelength of 760nm and turn off the light source with the wavelength of 840 nm;
and step 3: the detector starts to collect light intensity signals reflected by the light source after reaching the detection part;
and 4, step 4: the light intensity collected by the detector is amplified by the signal amplification module, and the light signal is converted into an electric signal by the signal conversion module, transmitted to the control module and then uploaded to the calculation module on the PC;
and 5: the calculation module performs linear regression on the monitoring data of the first group of detectors to obtain monitoring data of the first group of detectorsAccording to the corresponding slope k under 760nm light source1And determining the coefficient
Step 6: the driving module drives the light source module to turn on a light source with the wavelength of 840nm according to preset time, turns off the light source with the wavelength of 760nm, the step 3 to the step 4 are repeated, the calculation module performs linear regression on the monitoring data of the first group of detectors, and the slope k corresponding to the monitoring data of the first group of detectors under the 840nm light source is obtained2And determining the coefficient
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