CN111833314A - Skin blood perfusion non-contact monitoring method and monitoring system under motion state - Google Patents
Skin blood perfusion non-contact monitoring method and monitoring system under motion state Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 55
- 230000008081 blood perfusion Effects 0.000 title claims abstract description 52
- 238000000034 method Methods 0.000 title claims abstract description 22
- 230000017531 blood circulation Effects 0.000 claims abstract description 28
- 230000010412 perfusion Effects 0.000 claims abstract description 27
- 238000012545 processing Methods 0.000 claims abstract description 15
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- 239000008280 blood Substances 0.000 claims description 14
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- 230000002500 effect on skin Effects 0.000 claims 2
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- 238000010586 diagram Methods 0.000 description 5
- 238000003384 imaging method Methods 0.000 description 5
- 238000010276 construction Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000008326 skin blood flow Effects 0.000 description 2
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- 238000012935 Averaging Methods 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
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- 229910052760 oxygen Inorganic materials 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 238000010587 phase diagram Methods 0.000 description 1
- 230000035790 physiological processes and functions Effects 0.000 description 1
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- A61B5/0077—Devices for viewing the surface of the body, e.g. camera, magnifying lens
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- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
- G06T2207/30104—Vascular flow; Blood flow; Perfusion
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Abstract
The invention discloses a skin blood perfusion non-contact monitoring method and system in a motion state. According to the invention, the green light source is used for providing illumination for the skin area to be monitored, the camera is used for collecting the image of the skin area to be monitored, and finally the data processing unit is used for processing the collected image, so that the blood flow perfusion amplitude image and the blood flow perfusion phase image of the skin area to be monitored are obtained, and the non-contact type effective monitoring of blood flow perfusion in a motion state is realized.
Description
Technical Field
The invention relates to a skin blood perfusion non-contact monitoring method, in particular to a skin blood perfusion non-contact monitoring method and a skin blood perfusion non-contact monitoring system in a motion state.
Background
Adequate blood perfusion is critical to human oxygen transport and homeostasis. Meanwhile, the change of the physiological function of the human body in the processes of tissue repair, wound healing and the like can also cause the dynamic change of local blood perfusion. Therefore, blood perfusion monitoring has important application value in medical and surgical care.
However, the methods available for blood perfusion monitoring, such as laser doppler imaging and laser speckle contrast analysis, are too expensive to use and expensive in practical application, and the monitoring equipment is bulky in structure.
The method for realizing blood perfusion monitoring by using camera imaging has the advantages of low cost, portability, non-contact and the like, but the current blood perfusion monitoring method based on camera imaging is still in a development stage, is only suitable for static monitoring and is not suitable for a motion scene any more, so that the practical application value of the method is greatly limited.
Disclosure of Invention
The invention provides a skin blood perfusion non-contact monitoring method in a motion state, aiming at solving the problems that the use cost and the equipment cost are very high and the monitoring equipment structure is bulky when the blood perfusion is monitored by the existing laser Doppler imaging and laser speckle contrast analysis method and the practical application value is low because the existing camera imaging method is only suitable for static monitoring.
The specific technical solution of the invention is as follows:
the invention provides a skin blood perfusion non-contact monitoring method in a motion state, which comprises the following steps:
step 1: collecting an image;
step 1.1: determining a skin area to be monitored;
step 1.2: using a green light source to irradiate the skin area to be monitored, and shooting the skin area to be monitored by using a camera for a time length of T to obtain N frames of skin area images to be monitored; wherein T is more than or equal to 1s, and N is more than or equal to 30;
step 2: data processing
Step 2.1: appointing a region needing blood perfusion monitoring in the 1 st frame skin region image to be monitored;
step 2.2: performing Harris characteristic point detection in a specified blood flow perfusion monitoring area to obtain a plurality of characteristic points;
step 2.3: initializing a Kanade-Lucas-Tomasi characteristic point tracker by using the plurality of characteristic points in the step 2.2;
step 2.4: tracking the images of the frames 2 to N by using a Kanade-Lucas-Tomasi characteristic point tracker to obtain the position of each characteristic point in the images of the frames 2 to N, and estimating a transformation matrix of a plurality of characteristic points in every two adjacent frames in the images of the frames 2 to N;
step 2.5: remapping the designated blood perfusion monitoring area by using the transformation matrix so as to eliminate the influence of the motion of the interested blood perfusion monitoring area;
step 2.6: obtaining gray values of all pixel points in the blood perfusion monitoring area image after the 2 nd to the N th frames are remapped and the mean value of the gray values of all the pixel points;
step 2.7: taking the mean value of the gray value degrees of all the pixel points which change along with time as a reference signal, and taking the gray value of the pixel points which change along with time as a blood volume signal for reflecting the change of blood flow;
step 2.8: performing Butterworth filtering on the reference signal and the blood volume signal within the range of 0.5Hz-3.5Hz, thereby eliminating the influence of residual motion artifacts and camera noise;
step 2.9: intercepting a period of time T in the time T as a calculated time window, and performing cross-correlation operation by using the reference signal filtered in the step 2.8 and the blood volume signal at each pixel point position after filtering, so as to obtain a blood perfusion amplitude and a blood perfusion phase at each pixel point position in the time window T;
and step 3: acquiring a blood flow perfusion image of a monitoring area;
and performing pixel rearrangement on the blood flow perfusion amplitude and the blood flow perfusion phase to obtain a blood flow perfusion amplitude image and a blood flow perfusion phase image of the monitoring area.
Further, the specific formula of the cross-correlation operation is as follows:
[C(x),LAG(x)]＝XCORR(r(t),p(x,t))
in the formula:
c (x) reflects the blood perfusion amplitude at each pixel point position x within the time window t;
lag (x) reflects the blood perfusion phase at each pixel point position x within the time window t;
XCORR denotes cross-correlation;
r (t) is a reference signal; p (x, t) is the blood volume signal at arbitrary pixel location x.
Based on the skin blood perfusion non-contact monitoring method in the motion state, the invention also provides a monitoring system, which comprises a green light source, a camera and a data processing unit;
the green light source is used for providing illumination for the skin area to be monitored;
the camera is used for acquiring images of a skin area to be monitored and communicating with the data processing unit;
the data processing unit processes the acquired images so as to obtain a blood flow perfusion amplitude image and a blood flow perfusion phase image of the region to be monitored.
Further, the wavelength of the green light source is 525 nm.
The invention has the beneficial effects that:
the method provided by the invention realizes non-contact monitoring of skin blood perfusion in a motion state, can realize blood perfusion monitoring in a motion scene, and has the characteristics of non-contact, portability, motion interference resistance, strong environmental applicability and the like.
Drawings
FIG. 1 is a block flow diagram of the present invention.
Fig. 2 is a schematic diagram of the detection of the skin region and the feature points to be monitored.
Fig. 3 is a schematic diagram of a reference signal construction process.
Fig. 4 is a schematic diagram of a process of constructing a blood volume signal for each pixel.
Fig. 5 is a schematic diagram of the cross-correlation operation process.
Fig. 6 is a graph of blood perfusion amplitude.
Fig. 7 is a blood perfusion phase diagram.
Detailed Description
To make the objects, advantages and features of the present invention more apparent, a non-contact monitoring method and a monitoring system for skin perfusion under exercise according to the present invention are further described in detail with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become more apparent from the following description. It should be noted that: the drawings are in simplified form and are not to precise scale, the intention being solely for the convenience and clarity of illustrating embodiments of the invention; second, the structures shown in the drawings are often part of actual structures.
A skin blood perfusion non-contact monitoring system in a motion state comprises a green light source, a camera and a data processing unit; a green light source (the wavelength of the green light source is 525nm in the embodiment) is used for providing illumination for the skin area to be monitored; the camera is used for acquiring images of a skin area to be monitored and communicating with the data processing unit; the data processing unit processes the acquired images so as to obtain a blood flow perfusion amplitude image and a blood flow perfusion phase image of the region to be monitored. In this embodiment, the data processing unit is a computer.
Based on the system, the specific monitoring process is shown in fig. 1:
step 1: collecting an image;
step 1.1: determining a skin area to be monitored;
step 1.2: turning on a green light illuminating source and covering the skin area to be monitored; opening a camera, aligning the camera to a skin area to be monitored, and obtaining N frames of skin area images to be monitored, wherein the shooting time is T; wherein T is more than or equal to 1s, and N is more than or equal to 30;
step 2: processing data;
step 2.1: as shown in fig. 2, an area to be subjected to blood flow perfusion monitoring is specified in a first frame of skin area image to be monitored (the area in this embodiment is a human hand, where a rectangular frame represents the specified skin blood flow perfusion monitoring area, and a cross represents detected Harris feature points for motion tracking), and Harris feature point detection is performed in the specified blood flow perfusion monitoring area to obtain a plurality of feature points;
step 2.2: initializing a Kanade-Lucas-Tomasi characteristic point tracker by using the plurality of characteristic points in the step 2.1;
step 2.3: tracking the images of the frames 2 to N by using a Kanade-Lucas-Tomasi characteristic point tracker to obtain the position of each characteristic point in the images of the frames 2 to N, and estimating a transformation matrix of a plurality of characteristic points in every two adjacent frames in the images of the frames 2 to N;
step 2.4: remapping the appointed blood perfusion monitoring area by using the transformation matrix in the step 2.3, thereby eliminating the influence of the motion of the interested blood perfusion monitoring area;
step 2.5: obtaining gray values of all pixel points in the blood perfusion monitoring area image after the 2 nd to the N th frames are remapped and the mean value of the gray values of all the pixel points;
step 2.6: taking the mean value of the gray value degrees of all the pixel points which change along with time as a reference signal, and taking the gray value of the pixel points which change along with time as a blood volume signal for reflecting the change of blood flow;
step 2.7: performing Butterworth filtering on the reference signal and the blood volume signal within the range of 0.5Hz-3.5Hz to eliminate the influence of residual motion artifacts and camera noise, wherein the reference signal construction process is detailed in figure 3, and the blood volume signal construction process is detailed in figure 4;
step 2.8: intercepting a period of time T in the time T as a time window for calculation, and performing cross-correlation operation by using the reference signal r (T) filtered in step 2.7 and the blood volume signal p (x, T) of each pixel point position x after filtering, as shown in fig. 5, in the graph, a curve represents a reference signal constructed by averaging the pixel gray values of a specified area, and a curve B represents a blood volume change curve of each pixel point of the specified area;
[C(x),LAG(x)]＝XCORR(r(t),p(x,t))
in the formula: XCORR represents cross-correlation, the cross-correlation coefficient C (x) in the calculation result reflects the blood perfusion amplitude of each pixel point position x in the time window t, and the lag LAG (x) in the calculation result reflects the blood perfusion phase of each pixel point position x in the time window t;
and step 3: acquiring a blood flow perfusion image of a monitoring area;
performing pixel rearrangement on the cross-correlation coefficient C (x) reflecting blood perfusion and the phase LAG (x) in step 3.1 to obtain a blood perfusion amplitude image C (m, n) (as shown in fig. 6, the number in the image indicates the strength of pulsation characteristics, which represents the distribution of blood flow in skin, and also represents whether the blood perfusion of skin is sufficient, and effective monitoring of non-contact blood perfusion intensity in a motion state is realized), and a phase image LAG (m, n) (as shown in fig. 7, the image shows a blood perfusion phase map, the number of which represents the time characteristic of skin blood perfusion, and represents the appearance of skin blood flow arrival sequence, and effective monitoring of non-contact blood perfusion phase in a motion state is realized), wherein m x n x.
Claims (4)
1. A skin blood perfusion non-contact monitoring method under a motion state is characterized by comprising the following steps:
step 1: collecting an image;
step 1.1: determining a skin area to be monitored;
step 1.2: using a green light source to irradiate the skin area to be monitored, and shooting the skin area to be monitored by using a camera for a time length of T to obtain N frames of skin area images to be monitored; wherein T is more than or equal to 1s, and N is more than or equal to 30;
step 2: data processing
Step 2.1: appointing a region needing blood perfusion monitoring in the 1 st frame skin region image to be monitored;
step 2.2: performing Harris characteristic point detection in a specified blood flow perfusion monitoring area to obtain a plurality of characteristic points;
step 2.3: initializing a Kanade-Lucas-Tomasi characteristic point tracker by using the plurality of characteristic points in the step 2.2;
step 2.4: tracking the images of the frames 2 to N by using a Kanade-Lucas-Tomasi characteristic point tracker to obtain the position of each characteristic point in the images of the frames 2 to N, and estimating a transformation matrix of a plurality of characteristic points in every two adjacent frames in the images of the frames 2 to N;
step 2.5: remapping the designated blood perfusion monitoring area by using the transformation matrix so as to eliminate the influence of the motion of the interested blood perfusion monitoring area;
step 2.6: obtaining gray values of all pixel points in the blood perfusion monitoring area image after the 2 nd to the N th frames are remapped and the mean value of the gray values of all the pixel points;
step 2.7: taking the mean value of the gray value degrees of all the pixel points which change along with time as a reference signal, and taking the gray value of the pixel points which change along with time as a blood volume signal for reflecting the change of blood flow;
step 2.8: performing Butterworth filtering on the reference signal and the blood volume signal within the range of 0.5Hz-3.5Hz, thereby eliminating the influence of residual motion artifacts and camera noise;
step 2.9: intercepting a period of time T in the time T as a calculated time window, and performing cross-correlation operation by using the reference signal filtered in the step 2.8 and the blood volume signal at each pixel point position after filtering, so as to obtain a blood perfusion amplitude and a blood perfusion phase at each pixel point position in the time window T;
and step 3: acquiring a blood flow perfusion image of a monitoring area;
and performing pixel rearrangement on the blood flow perfusion amplitude and the blood flow perfusion phase to obtain a blood flow perfusion amplitude image and a blood flow perfusion phase image of the monitoring area.
2. The ambulatory dermal blood perfusion non-contact monitoring system as recited in claim 1, further comprising: the specific formula of the cross-correlation operation is as follows:
[C(x),LAG(x)]＝XCORR(r(t),p(x,t))
in the formula:
c (x) reflects the blood perfusion amplitude at each pixel point position x within the time window t;
lag (x) reflects the blood perfusion phase at each pixel point position x within the time window t;
XCORR denotes cross-correlation;
r (t) is a reference signal; p (x, t) is the blood volume signal at arbitrary pixel location x.
3. A monitoring system based on the non-contact method for monitoring skin perfusion under exercise of claim 1, wherein: the system comprises a green light source, a camera and a data processing unit;
the green light source is used for providing illumination for the skin area to be monitored;
the camera is used for acquiring images of a skin area to be monitored and communicating with the data processing unit;
the data processing unit processes the acquired images so as to obtain a blood flow perfusion amplitude image and a blood flow perfusion phase image of the region to be monitored.
4. The ambulatory dermal blood perfusion non-contact monitoring system of claim 3, wherein: the wavelength of the green light source is 525 nm.
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| CN113712581A (en) * | 2021-09-14 | 2021-11-30 | 上海联影医疗科技股份有限公司 | Perfusion analysis method and system |
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