CN111214218A - Detection equipment for multiple physiological parameters - Google Patents
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Abstract
The embodiment of the disclosure provides a device for detecting multiple physiological parameters, which comprises a camera, a processor and a display. The camera is configured to capture video of tissue color changes. The processor is configured to decompose the video frame by frame to obtain a picture set consisting of a plurality of video pictures; performing blind source separation on the pictures in the picture set respectively to generate volume blood flow pulse wave imaging PPGi signals; and determining characteristic parameters according to the PPGi signal, and performing fitting calculation on the characteristic parameters to obtain a plurality of physiological parameters. The display is configured to present a plurality of physiological parameters, so that a user can acquire the plurality of physiological parameters through the display, the detection mode of the physiological parameters is more flexible and convenient, resources are saved, and the user can acquire the physiological parameters of the user through the camera on the handheld terminal of the user, so that the user can perform health management at any time according to requirements.
Description
Technical Field
The present disclosure relates to the technical field of medical equipment, and in particular, to a multi-physiological-parameter detection device.
Background
With the continuous development and growth of smart phones, the additional functions of the smart phones are more and more abundant, and the functions of accessories of the smart phones are more and more powerful. At present, a part of mobile phones are additionally provided with a function of measuring heart rate through a camera, but the mobile phones can only realize heart rate measurement and cannot realize the function of measuring other physiological parameters, and with the increasing attention of people on health, it is necessary to research and utilize standard equipment such as mobile phones and the like to complete more physiological parameter measurements. In addition, most of the current physiological parameter acquisition devices are independent devices which are uploaded to a mobile phone end by using a wireless transmission technology to complete integration, so that the use is inconvenient to a certain extent, corresponding expenses need to be paid additionally sometimes, and the cost is too high for users.
Disclosure of Invention
To the above technical problem that exists among the prior art, this disclosure provides a detection device of many physiological parameters for the user just can acquire a plurality of physiological parameters through the camera.
The disclosed embodiment provides a detection device of multiple physiological parameters, which includes:
a camera configured to capture video of tissue color changes;
a processor configured to perform frame-by-frame decomposition on the video to obtain a picture set composed of a plurality of video pictures; performing blind source separation on the pictures in the picture set respectively to generate volume blood flow pulse wave imaging PPGi signals; determining characteristic parameters according to the PPGi signal, and performing fitting calculation on the characteristic parameters to obtain a plurality of physiological parameters;
a display configured to present a plurality of physiological parameters.
In some embodiments, the processor is further configured to denoise the PPGi signal using a digital signal processing method.
In some embodiments, the processor is specifically configured to determine the characteristic parameter as follows:
determining a characteristic value participating in the characteristic parameter calculation according to a characteristic parameter calculation mode;
determining the characteristic parameter according to the characteristic value extracted from the PPGi signal;
wherein the characteristic values include: a peak value, a valley value, a maximum rising slope point, a first derivative maximum value, and a first derivative minimum value of the PPGi signal.
In some embodiments, the processor is specifically configured to determine the feature value as follows:
identifying the wave peak value, the wave trough value and the maximum rising slope point of the PPGi signal in each identification period by adopting a differential zero crossing point and adaptive threshold algorithm;
and adopting an adaptive threshold algorithm to identify a maximum value and a minimum value of a first derivative of the PPGi signal in each identification period.
In some embodiments, the order of identification of the feature values is as follows: the valley value, the maximum rising slope point and the first derivative maximum value, the peak value, the first derivative minimum value.
In some embodiments, the processor is specifically configured to determine the characteristic parameter as follows:
the systolic time ST is determined from the trough to peak systolic times.
In some embodiments, the processor is specifically configured to determine the characteristic parameter as follows:
the diastolic time DT is determined from the peak to trough diastolic time.
In some embodiments, the processor is specifically configured to determine the characteristic parameter as follows:
determining a heartbeat time interval PPI according to the time interval of adjacent peaks, and determining a first parameter according to the time from the first-order peak to the trough.
In some embodiments, the processor is specifically configured to determine the characteristic parameter as follows:
determining a waveform characteristic parameter K of the PPGi signal according to the following formula:
wherein, Ps, Pd, Pm are the peak value, the trough value and the average value of the PPGi signal in an identification period respectively, and the average value is determined according to the following formula
Wherein P (T) is a waveform function of the PPGi signal, and T is an identification period.
In some embodiments, the processor is specifically configured to determine the physiological parameter as follows:
the heart rate HR is determined according to the following formula: HR ═ 60x predetermined sampling rate)/PPI.
In some embodiments, the processor is specifically configured to determine the physiological parameter as follows:
the systolic blood pressure SBP is determined according to the following formula: SBP is a · ST + b · DT + c · PPGd1DT + d · Amp + e;
diastolic pressure is determined according to the following formula
Wherein a, b, c, d and e are constants, PPGd1DT is the first parameter, and Amp is the amplitude of the peak value of the PPGi signal.
In some embodiments, the processor is specifically configured to determine the physiological parameter as follows:
blood oxygen Spo is determined according to the following formula2：
Wherein,
and
is a wavelength lambdaiThe peak and valley values of the PPGi signal are measured, g and h being constant.
In some embodiments, the processor is specifically configured to determine the physiological parameter as follows:
cardiac output CO is determined according to the following formula:
wherein m is a predetermined correction coefficient.
In some embodiments, the processor is further configured to: and determining a damage index based on the corresponding relation between the physiological parameters and the cardiovascular system so as to judge the damage according to the damage index.
In some embodiments, the processor is specifically configured to determine the damage index F according to the following formula:
where RC is the high value of the normal range of the indicator, RF is the low value of the normal range of the indicator, value is the value of the physiological parameter, power [ ] is a function of the power used to return a given number, α and β are determined for experimental calculations.
Compared with the prior art, the beneficial effects of the embodiment of the present disclosure are that: the camera collects videos with changed tissue colors, the processor decomposes the videos frame by frame to form a picture set, the pictures in the picture set are subjected to blind source separation to generate PPGi signals, and the characteristic parameters determined according to the PPGi signals are subjected to fitting calculation to finally obtain a plurality of physiological parameters (such as heart rate, blood oxygen, blood pressure, cardiac output and other physiological parameters), so that a user can obtain the physiological parameters through the display, the detection mode of the physiological parameters is more flexible and convenient, resources are saved, the user can obtain the physiological parameters of the user through the camera on the handheld terminal of the user, and the user can perform health management according to requirements at any time.
Drawings
In the drawings, which are not necessarily drawn to scale, like reference numerals may describe similar components in different views. Like reference numerals having letter suffixes or different letter suffixes may represent different instances of similar components. The drawings illustrate various embodiments generally by way of example and not by way of limitation, and together with the description and claims serve to explain the disclosed embodiments. The same reference numbers will be used throughout the drawings to refer to the same or like parts, where appropriate. Such embodiments are illustrative, and are not intended to be exhaustive or exclusive embodiments of the present apparatus or method.
FIG. 1 is a block diagram of a multi-physiological parameter detection device according to an embodiment of the present disclosure;
FIG. 2 is a flow chart of a multi-physiological parameter sensing device sensing physiological parameters according to an embodiment of the present disclosure;
FIG. 3 is a flow chart of determining a characteristic parameter according to an embodiment of the present disclosure.
The members denoted by reference numerals in the drawings:
100-detection of multiple physiological parameters; 101-a camera; 102-a processor; 103-display.
Detailed Description
For a better understanding of the technical aspects of the present disclosure, reference is made to the following detailed description taken in conjunction with the accompanying drawings. Embodiments of the present disclosure are described in further detail below with reference to the figures and the detailed description, but the present disclosure is not limited thereto.
The use of "first," "second," and similar terms in this disclosure is not intended to indicate any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element preceding the word covers the element listed after the word, and does not exclude the possibility that other elements are also covered. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
In the present disclosure, when a specific device is described as being located between a first device and a second device, there may or may not be intervening devices between the specific device and the first device or the second device. When a particular device is described as being coupled to other devices, that particular device may be directly coupled to the other devices without intervening devices or may be directly coupled to the other devices with intervening devices.
All terms (including technical or scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs unless specifically defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
The disclosed embodiment provides a device for detecting multiple physiological parameters, which comprises a camera, a processor and a display, as shown in fig. 1. As shown in fig. 1 and fig. 2, the camera is configured to acquire a video of a tissue color change (S201), and the camera may be a camera configured on any electronic device, where the electronic device may be a notebook computer, a handheld terminal, or the like, and the electronic device may be a camera having a camera function, and this application is not limited in this respect.
Further, with continuing reference to fig. 2, the processor is configured to perform frame-by-frame decomposition on the video to obtain a picture set composed of a plurality of video pictures (S202), that is, by performing frame-by-frame decomposition on the obtained picture set, the situation of tissue color change in the video can be displayed one by one. Based on the above step S202, blind source separation is performed on the pictures in the picture set to generate a volume flow pulse wave imaging PPGi signal (S203), and as will be understood by those skilled in the art, blind source separation refers to separation of an unobserved original signal from a plurality of observed mixed signals. That is, blind source separation is performed on pictures in the picture set, and a PPGi signal can be generated.
Continuing with the step S203, with reference to fig. 2, determining characteristic parameters according to the PPGi signal, and performing fitting calculation on the characteristic parameters to obtain a plurality of physiological parameters (S204). It should be noted that, as known to those skilled in the art, fitting refers to knowing several discrete function values of a certain function, and by adjusting several undetermined coefficients in the function, the difference (least-squares sense) between the function and a known point set is minimized. By performing the fitting calculation on the characteristic parameters, a plurality of physiological parameters (such as heart rate, blood oxygen, blood pressure, cardiac output and other physiological parameters) can be obtained, so that a user can obtain the plurality of physiological parameters through the electronic device with the camera instead of obtaining one physiological parameter singly. Further, the display is configured to present a plurality of the above physiological parameters (S205), so that the user can monitor and manage the health of the user based on the physiological parameters such as heart rate, blood oxygen, blood pressure, cardiac output, etc. displayed by the display.
The camera collects videos with changed tissue colors, the processor decomposes the videos frame by frame to form a picture set, the pictures in the picture set are subjected to blind source separation to generate PPGi signals, and the characteristic parameters determined according to the PPGi signals are subjected to fitting calculation to finally obtain a plurality of physiological parameters (such as heart rate, blood oxygen, blood pressure, cardiac output and other physiological parameters), so that a user can obtain the physiological parameters through the display, the detection mode of the physiological parameters is more flexible and convenient, resources are saved, the user can obtain the physiological parameters of the user through the camera on the handheld terminal of the user, and the user can perform health management according to requirements at any time.
In some embodiments, continuing with fig. 2, the processor is further configured to denoise the PPGi signal using a digital signal processing method (S206). It should be noted that, as known to those skilled in the art, digital signal processing is to convert the motion change of an object into a series of numbers and extract useful information therefrom by using a calculation method, so as to meet the requirements of our practical application. The digital signal processing has the advantages of high processing precision, flexible function change, stable performance and high processing efficiency. In addition, in the process of digitalization and transmission, a real digital image is often influenced by interference of imaging equipment and external environment noise, and the noise in the digital image can be effectively reduced by adopting image denoising processing. That is, the embodiment of the present disclosure performs denoising processing on the PPGi signal by using a digital signal processing method, so as to obtain the PPGi signal with better quality.
In some embodiments, the processor is configured to determine the characteristic parameter (as shown in fig. 3) as follows: first, step S301 is executed to determine the feature values participating in feature parameter calculation according to the feature parameter calculation method. Then, step S302 is performed to determine the feature parameter according to the feature value extracted from the PPGi signal. Wherein the characteristic values include: the peak value, the valley value, the maximum rising slope point, the first derivative maximum value and the first derivative minimum value of the PPGi signal.
It can be understood that the calculation mode of each feature parameter is different, and the calculation mode for one feature parameter can determine the feature value participating in the calculation of the feature parameter, so as to obtain the feature value required by the calculation of the feature parameter in a targeted manner, thereby improving the operation efficiency. And finally determining the specific numerical value of the characteristic parameter through the acquired corresponding characteristic value and a calculation mode based on the characteristic parameter. Specifically, based on the above-mentioned feature values such as the peak value, the valley value, the maximum rising slope point, the first derivative maximum value, and the first derivative minimum value, a plurality of feature parameters can be calculated to determine a plurality of physiological parameters.
In some embodiments, the processor is configured to determine the characteristic value as follows: identifying the peak value, the trough value and the maximum rising slope point of the PPGi signal in each identification period by adopting a differential zero crossing point and an adaptive threshold algorithm, wherein the peak value from positive to negative of the differential is understood as the trough from negative to positive; and adopting an adaptive threshold algorithm to identify a first derivative maximum value and a first derivative minimum value of the PPGi signal in each identification period. It will be appreciated that the identification period may be a heart beat period. The first derivative maximum value and the first derivative minimum value are both maximum and minimum values determined by first deriving the waveform function of the PPGi signal.
It should be noted that, as known to those skilled in the art, the adaptive threshold algorithm is a method for performing image calculation by using an image local threshold instead of a global threshold, and is specifically directed to a picture with too large variation in light and shadow or a picture with less obvious color difference in a range. In performing the adaptive threshold algorithm, a dynamically updated adaptive threshold is first introduced, which is determined based on the peak value in the last identification period and which may be updated once per unit time to detect the above-mentioned feature value within the range of the adaptive threshold. The updating in the unit time may be to update the adaptive threshold once every second, or to update the adaptive threshold once every two seconds, which is not specifically limited in the present application. By adopting the self-adaptive threshold algorithm, the algorithm complexity can be effectively reduced, and the operation efficiency is improved.
It can be understood that the peak value, the trough value, and the maximum rising slope point of the PPGi signal in each identification period are identified by using a differential zero-crossing point and an adaptive threshold algorithm, where the differential zero-crossing point is an algorithm commonly used for solving the peak value, the trough value, and the maximum rising slope point of the regularity signal, and this application is not described herein in detail.
In some embodiments, the identification order of the feature values is as follows: (1) a wave trough value; (2) a maximum rising slope point and a first derivative maximum; (3) a wave peak value; (4) a first derivative minimum. It can be understood that the trough value is an identification starting point in an identification period, and the amount of computation can be effectively reduced by adopting the identification sequence, so that the computation efficiency is improved.
In some embodiments, the processor is configured to determine the following characteristic parameters as follows:
(1) the systolic time ST is determined from the trough to peak systolic times.
(2) The diastolic time DT is determined from the peak to trough diastolic time.
It will be appreciated that each contraction and relaxation of the heart constitutes a cardiac cycle. The systolic time ST is determined by the systolic time from trough to peak, and the diastolic time DT is determined by the diastolic time from peak to trough.
(3) Determining a heartbeat time interval PPI according to the time interval of adjacent peaks, and determining a first parameter according to the time from the first-order peak to the trough. The heartbeat time interval PPI is a difference between a highest point and a lowest point, i.e., a potential difference from a positive peak to a negative peak. That is, the heartbeat time interval PPI is determined by the time interval of adjacent peaks.
(4) Determining a waveform characteristic parameter K of the PPGi signal according to the following formula:
wherein, Ps, Pd, Pm are the peak value, the trough value and the average value of the PPGi signal in an identification period respectively, and the average value is determined according to the following formula
Wherein P (T) is a waveform function of the PPGi signal, and T is an identification period.
In some embodiments, the processor is configured to determine the following physiological parameters as follows:
(1) the heart rate HR is determined according to the following formula: HR ═ 60x predetermined sampling rate)/PPI.
It will be appreciated that the sampling rate is selected according to the sampling law. It will be appreciated by those skilled in the art that the sampled values may contain all the information of the original signal as long as the sampling frequency is greater than or equal to twice the highest frequency of the valid signal, so that the sampled signal may be restored to the original signal without distortion. The appropriate sampling rate can be obtained through the method.
Based on the above steps, the heart rate can be determined by calculating the determined heart beat time interval PPI and the predetermined sampling rate, wherein the heart rate refers to the number of heart beats per minute in a resting state of a normal person.
(2) The systolic blood pressure SBP is determined according to the following formula:
SBP＝a·ST+b·DT+c·PPGd1DT+d·Amp+e，
it can be understood that the systolic pressure SBP is the pressure in the artery rising when the human heart contracts, and in the middle period of the heart contraction, the pressure in the artery is the highest, and the pressure of blood on the inner wall of the blood vessel is called the systolic pressure SBP.
(3) The diastolic pressure DBP is determined according to the following equation:
it is understood that the above-mentioned diastolic pressure DBP is the pressure generated when the artery vessel is elastically retracted when the heart of the human is in diastole, which is called the diastolic pressure DBP.
The a, b, c, d and e are constants, and can be repeatedly verified according to an experiment result to obtain appropriate values of the a, b, c, d and e; PPGd1DT is the first parameter, namely the time from the peak to the trough of the first guide wave; amp is the amplitude of the peak value of the PPGi signal, which is the amplitude corresponding to the point corresponding to the peak value.
(4) Blood oxygen Spo is determined according to the following formula2：
Wherein,
and
is a wavelength lambdaiAnd measuring the peak value and the valley value of the PPGi signal, wherein g and h are constants, and the g and h can be repeatedly verified according to the experimental result to obtain the proper values of g and h.
It is understood that the blood oxygen mentioned above refers to oxygen in blood.
(5) Cardiac output CO is determined according to the following formula:
where m is a predetermined correction coefficient, which is determined by experimental calculation. The cardiac output CO is the volume of blood pumped per minute in the left or right ventricle, i.e. the product of heart rate and stroke volume.
It is understood that the correction coefficient is a coefficient which is added to the calculation formula in order to reflect the actual performance as much as possible when the data calculation, the formula expression, and the like deviate due to the ideal and real conditions, the investigation, and the like.
In some embodiments, the processor is further configured to: and determining a damage index based on the corresponding relation between the physiological parameters and the cardiovascular system so as to judge the damage according to the damage index. It can be understood that physiological parameters such as heart rate, blood oxygen, blood pressure and cardiac output all have corresponding relations with the cardiovascular system, when the heart rate, the blood oxygen, the blood pressure and the cardiac output are abnormal, it is indicated that the corresponding cardiovascular system may have diseases, an injury index is determined according to the corresponding relation of the physiological parameters and the cardiovascular system, and the current cardiovascular hazard condition is determined according to the injury index, so that the user can further know the health condition of the user.
In practice, the processor is configured to determine the damage index F according to the following formula:
RC is a high value of a normal range of the index, RF is a low value of the normal range of the index, value is a numerical value of a physiological parameter, power [ ] is a function of power for returning given numbers, α and β are determined by experimental calculation, the damage index F corresponding to each physiological parameter is provided, and the damage index F is compared with a threshold value in the normal range, so that the damage index F of the physiological parameter to the heart and blood vessels is provided, a user can complete disease risk prediction based on the damage index F, and self health is further managed.
Moreover, although exemplary embodiments have been described herein, the scope thereof includes any and all embodiments based on the disclosure with equivalent elements, modifications, omissions, combinations (e.g., of various embodiments across), adaptations or alterations. The elements of the claims are to be interpreted broadly based on the language employed in the claims and not limited to examples described in the present specification or during the prosecution of the application, which examples are to be construed as non-exclusive. It is intended, therefore, that the specification and examples be considered as exemplary only, with a true scope and spirit being indicated by the following claims and their full scope of equivalents.
The above description is intended to be illustrative and not restrictive. For example, the above-described examples (or one or more versions thereof) may be used in combination with each other. For example, other embodiments may be used by those of ordinary skill in the art upon reading the above description. In addition, in the foregoing detailed description, various features may be grouped together to streamline the disclosure. This should not be interpreted as an intention that a disclosed feature not claimed is essential to any claim. Rather, the subject matter of the present disclosure may lie in less than all features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the detailed description as examples or embodiments, with each claim standing on its own as a separate embodiment, and it is contemplated that these embodiments may be combined with each other in various combinations or permutations. The scope of the disclosure should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.
The above embodiments are merely exemplary embodiments of the present disclosure, which is not intended to limit the present disclosure, and the scope of the present disclosure is defined by the claims. Various modifications and equivalents of the disclosure may occur to those skilled in the art within the spirit and scope of the disclosure, and such modifications and equivalents are considered to be within the scope of the disclosure.
Claims (15)
1. A device for detecting multiple physiological parameters, comprising:
a camera configured to capture video of tissue color changes;
a processor configured to perform frame-by-frame decomposition on the video to obtain a picture set composed of a plurality of video pictures; performing blind source separation on the pictures in the picture set respectively to generate volume blood flow pulse wave imaging PPGi signals; determining characteristic parameters according to the PPGi signal, and performing fitting calculation on the characteristic parameters to obtain a plurality of physiological parameters;
a display configured to present a plurality of physiological parameters.
2. The multi-physiological parameter detection device of claim 1, wherein the processor is further configured to denoise the PPGi signal using digital signal processing methods.
3. The multi-physiological parameter detection device according to claim 1, wherein the processor is specifically configured to determine the characteristic parameter as follows:
determining a characteristic value participating in the characteristic parameter calculation according to a characteristic parameter calculation mode;
determining the characteristic parameter according to the characteristic value extracted from the PPGi signal;
wherein the characteristic values include: a peak value, a valley value, a maximum rising slope point, a first derivative maximum value, and a first derivative minimum value of the PPGi signal.
4. The multi-physiological parameter detection device according to claim 3, wherein the processor is specifically configured to determine the characteristic value as follows:
identifying the wave peak value, the wave trough value and the maximum rising slope point of the PPGi signal in each identification period by adopting a differential zero crossing point and adaptive threshold algorithm;
and adopting an adaptive threshold algorithm to identify a maximum value and a minimum value of a first derivative of the PPGi signal in each identification period.
5. The multi-physiological parameter detection device according to claim 4, wherein the identification order of the characteristic values is as follows in sequence: the valley value, the maximum rising slope point and the first derivative maximum value, the peak value, the first derivative minimum value.
6. The multi-physiological parameter detection device according to claim 3, wherein the processor is specifically configured to determine the characteristic parameter as follows:
the systolic time ST is determined from the trough to peak systolic times.
7. The multi-physiological parameter detection device according to claim 6, wherein the processor is specifically configured to determine the characteristic parameter as follows:
the diastolic time DT is determined from the peak to trough diastolic time.
8. The multi-physiological parameter detection device according to claim 7, wherein the processor is specifically configured to determine the characteristic parameter as follows:
determining a heartbeat time interval PPI according to the time interval of adjacent peaks, and determining a first parameter according to the time from the first-order peak to the trough.
9. The multi-physiological parameter detection device according to claim 8, wherein the processor is specifically configured to determine the characteristic parameter as follows:
determining a waveform characteristic parameter K of the PPGi signal according to the following formula:
wherein Ps, Pd, Pm are the peak value, the trough value and the average value of the PPGi signal in an identification period, respectively, and the average value Pm is determined according to the following formula:
wherein P (T) is a waveform function of the PPGi signal, and T is an identification period.
10. The multi-physiological parameter detection device according to claim 9, wherein the processor is specifically configured to determine the physiological parameter as follows:
the heart rate HR is determined according to the following formula: HR ═ 60x predetermined sampling rate)/PPI.
11. The multi-physiological parameter detection device according to claim 9, wherein the processor is specifically configured to determine the physiological parameter as follows:
the systolic blood pressure SBP is determined according to the following formula: SBP is a · ST + b · DT + c · PPGd1DT + d · Amp + e;
the diastolic pressure DBP is determined according to the following equation:
wherein a, b, c, d and e are constants, PPGd1DT is the first parameter, and Amp is the amplitude of the peak value of the PPGi signal.
12. The multi-physiological parameter detection device according to claim 9, wherein the processor is specifically configured to determine the physiological parameter as follows:
blood oxygen Spo is determined according to the following formula2：
Wherein,
and
is a wavelength lambdaiThe peak and valley values of the PPGi signal are measured, g and h being constant.
13. The multi-physiological parameter detection device according to claim 11, wherein the processor is specifically configured to determine the physiological parameter as follows:
cardiac output CO is determined according to the following formula:
wherein m is a predetermined correction coefficient.
14. The multi-physiological parameter detection device according to any one of claims 10 to 13, wherein the processor is further configured to: and determining a damage index based on the corresponding relation between the physiological parameters and the cardiovascular system so as to judge the damage according to the damage index.
15. The multi-physiological parameter detection device according to claim 14, wherein the processor is specifically configured to determine the impairment index F according to the following formula:
where RC is the high value of the normal range of the indicator, RF is the low value of the normal range of the indicator, value is the value of the physiological parameter, power [ ] is a function of the power used to return a given number, α and β are determined for experimental calculations.
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