CN109512393A - Recurrence method, system and the storage medium of oxygen saturation measurement confidence level - Google Patents
Recurrence method, system and the storage medium of oxygen saturation measurement confidence level Download PDFInfo
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- CN109512393A CN109512393A CN201811482852.3A CN201811482852A CN109512393A CN 109512393 A CN109512393 A CN 109512393A CN 201811482852 A CN201811482852 A CN 201811482852A CN 109512393 A CN109512393 A CN 109512393A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
- A61B5/14551—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters for measuring blood gases
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7221—Determining signal validity, reliability or quality
Abstract
The invention discloses the recurrence method of oxygen saturation measurement confidence level, system and storage medium, method includes: to carry out initial configuration to data point number；According to initial configuration as a result, building linear regression model (LRM)；According to linear regression model (LRM), the confidence level of oxygen saturation measurement result is obtained；Judge whether the confidence level of oxygen saturation measurement result meets threshold requirement, if so, the confidence level of output oxygen saturation measurement result；Conversely, then performing the next step suddenly, until the confidence level of oxygen saturation measurement result meets threshold requirement；Data point number is updated；According to the update of data point as a result, being updated by recursive algorithm to linear regression model (LRM), and return to the step of executing the confidence level that oxygen saturation measurement result is obtained according to linear regression model (LRM).The present invention improves the reliability of oxygen saturation measurement result, more scientific, can be widely applied to processing of biomedical signals technical field.
Description
Technical field
The present invention relates to processing of biomedical signals technical fields, especially the recursion side of oxygen saturation measurement confidence level
Method, system and storage medium.
Background technique
The diastole of heart and contraction driving blood stream make oxygen and reduced hemoglobin (hemoglobin, Hb) through lung
It is combined into oxyhemoglobin (Oxyhemoglobin, HbO2), oxygen discharges after being transported to capillary by blood.Enough
Oxygen be realize human tissue cell metabolism, sustain life movable material base.Blood oxygen saturation is a kind of anti-
The important physiological parameter for reflecting oxygen content in blood has direct relationship with respiratory system, the circulatory system and cardio-pulmonary function.
Currently, blood oxygen saturation is widely used in Intensive Care Therapy, family health care and the sign inspection of high-risk professional such as fireman, pilot
It surveys.
The detection method of blood oxygen saturation can be divided into invasive detection and two kinds of Non-invasive detection.Wherein invasive blood oxygen saturation
Detection is mainly using Van Slyke pressure inspection method and oxygen electrode method.The main means of Non-invasive detection are that photoplethysmographic is traced
Method (photoplethysmography, PPG).Blood vessel blood volume changes with diastole and when shrinking, and causes to light absorption
The luminous intensity of the difference of rate, reflection or transmission is also in pulsating nature mechanical periodicity therewith.Pulse wave blood oxygen analysis instrument utilizes photocapacitance
Product pulse tracing is reflection or the transmitted intensity of 660nm feux rouges and 940nm infrared light, Jin Ergen by recording wavelength
Blood oxygen saturation is extrapolated according to Lambert-Beer law.In actual measurement, accurately calculating pulse blood oxygen signal characteristic value R is
The key of Non-invasive detection blood oxygen saturation is realized based on photoplethysmographic graphical method.
Traditional R value extracting method is needed pulse Wave Decomposition into two kinds of ingredients of AC/DC, and wherein alternating component reflects blood
Absorption of the HbO2 and Hb to light in liquid, flip-flop reflect non-blood tissue such as muscle, bone, fat and water etc. pair in finger tip
The absorption of light.The calculating of alternating component usually using peak-to-valley value method, that is, be approximately considered in a pulse cycle peak value and valley it
Between difference be alternating component amplitude.In measurement and alternating current-direct current decomposable process, the interference and random noise that introduce and generate
It will affect the R value precision of peak-to-valley value method calculating, it usually needs precision is improved using being averaged for multiple period peak-to-valley values, thus shadow
Ring the real-time calculated.It is proposed that a kind of method using linear regression model (LRM) calculates R value, this method is taken full advantage of
The data of all sampled points, rather than the peak-to-valley value with pulse wave is only relied only on, improve the stability of calculated result.However, light
Electro-detection is easy to be influenced by external light environment and finger tip motion artifact causes blood engorgement situation and transmission path
Variation.The case where above-mentioned factor can cause measurement result to be distorted, and lead to missing inspection and erroneous detection.Currently, blood oxygen saturation is tested
Instrument shortage analyses the reliability of measurement result scientifically, how rationally to assess the reliability of measured value, is an industry urgency
Problem to be solved.
Summary of the invention
In order to solve the above technical problems, it is an object of the invention to: a kind of oxygen saturation measurement of high reliablity is provided
Recurrence method, system and the storage medium of confidence level.
The technical solution that one aspect of the present invention is taken are as follows:
The recurrence method of oxygen saturation measurement confidence level, comprising the following steps:
Initial configuration is carried out to data point number；
According to initial configuration as a result, building linear regression model (LRM)；
According to linear regression model (LRM), the confidence level of oxygen saturation measurement result is obtained；
Judge whether the confidence level of oxygen saturation measurement result meets threshold requirement, if so, output blood oxygen saturation
The confidence level of measurement result；Conversely, then performing the next step suddenly, until the confidence level of oxygen saturation measurement result meets threshold value and wants
It asks；
Data point number is updated；
According to the update of data point as a result, being updated by recursive algorithm to linear regression model (LRM), and return to execution root
According to linear regression model (LRM), the step of obtaining the confidence level of oxygen saturation measurement result.
Further, it is described according to initial configuration as a result, building linear regression model (LRM) the step for, comprising the following steps:
According to initial configuration as a result, calculating intermediate parameters；
According to intermediate parameters, the fitting coefficient of equation of linear regression is calculated, equation of linear regression is obtained；
According to equation of linear regression, total sum of sguares of deviation from mean and residual sum of squares (RSS) are calculated；
According to total sum of sguares of deviation from mean and residual sum of squares (RSS), the confidence level of oxygen saturation measurement result is calculated.
Further, the update according to data point is as a result, be updated this to linear regression model (LRM) by recursive algorithm
One step, comprising the following steps:
According to the update of data point as a result, being updated to intermediate parameters；
According to updated intermediate parameters, equation of linear regression is updated；
According to updated equation of linear regression, total sum of sguares of deviation from mean and residual sum of squares (RSS) are updated；
According to updated total sum of sguares of deviation from mean and residual sum of squares (RSS), to the confidence level of oxygen saturation measurement result
It is updated.
Further, further comprising the steps of:
According to linear regression model (LRM), pulse blood oxygen signal characteristic value is generated.
Another aspect of the present invention is adopted the technical scheme that:
The recurrence system of oxygen saturation measurement confidence level, comprising:
Initialization module, for carrying out initial configuration to data point number；
Module is constructed, is used for according to initial configuration as a result, building linear regression model (LRM)；
Module is obtained, for obtaining the confidence level of oxygen saturation measurement result according to linear regression model (LRM)；
Judgment module, for judging whether the confidence level of oxygen saturation measurement result meets threshold requirement, if so, defeated
The confidence level of oxygen saturation measurement result out；Conversely, then performing the next step suddenly, until the confidence of oxygen saturation measurement result
Degree meets threshold requirement；
Update module, for being updated to data point number；
Recursion module, for according to the update of data point as a result, be updated by recursive algorithm to linear regression model (LRM),
And it returns to execution and obtains module.
Further, the building module includes:
First computing unit is used for according to initial configuration as a result, calculating intermediate parameters；
Second computing unit, for calculating the fitting coefficient of equation of linear regression, obtaining linear regression according to intermediate parameters
Equation；
Third computing unit, for calculating total sum of sguares of deviation from mean and residual sum of squares (RSS) according to equation of linear regression；
4th computing unit, for calculating oxygen saturation measurement according to total sum of sguares of deviation from mean and residual sum of squares (RSS)
As a result confidence level.
Further, the recursion module includes:
First updating unit, for the update according to data point as a result, being updated to intermediate parameters；
Second updating unit, for being updated to equation of linear regression according to updated intermediate parameters；
Third updating unit, for being put down to total sum of sguares of deviation from mean and residual error according to updated equation of linear regression
Just and it is updated；
According to updated total sum of sguares of deviation from mean and residual sum of squares (RSS), to the confidence level of oxygen saturation measurement result
It is updated.
Further, further includes:
Generation module, for generating pulse blood oxygen signal characteristic value according to linear regression model (LRM).
Another aspect of the present invention is adopted the technical scheme that:
The recurrence system of oxygen saturation measurement confidence level, comprising:
At least one processor；
At least one processor, for storing at least one program；
When at least one described program is executed by least one described processor, so that at least one described processor is realized
The recurrence method of the oxygen saturation measurement confidence level.
Another aspect of the present invention is adopted the technical scheme that:
A kind of storage medium, wherein be stored with the executable instruction of processor, the executable instruction of the processor by
For executing the recurrence method of the oxygen saturation measurement confidence level when processor executes.
The beneficial effects of the present invention are: the present invention is based on linear regression model (LRM), by recursive algorithm to linear regression model (LRM)
It is updated, finally obtains the confidence level of oxygen saturation measurement result, and then realize to the reliability assessment of measured value, avoid
The case where missing inspection caused by the disturbing factors such as motion artifact and noise influence and erroneous detection, improve oxygen saturation measurement result
Reliability, it is more scientific.
Detailed description of the invention
Fig. 1 is the step flow chart of the embodiment of the present invention.
Specific embodiment
The present invention is further explained and is illustrated with specific embodiment with reference to the accompanying drawings of the specification.For of the invention real
The step number in example is applied, is arranged only for the purposes of illustrating explanation, any restriction is not done to the sequence between step, is implemented
The execution sequence of each step in example can be adaptively adjusted according to the understanding of those skilled in the art.
Referring to Fig.1, the embodiment of the invention provides a kind of recurrence method of oxygen saturation measurement confidence level, including it is following
Step:
S1, initial configuration is carried out to data point number；
In the present embodiment, data point number n is initially configured as n=2；
S2, according to initial configuration as a result, building linear regression model (LRM)；
It is further used as the preferred embodiment of step S2, the step S2, comprising the following steps:
S20, n-th of moment point data for obtaining feux rouges and infrared light, respectively with Ird(n) and Iir(n) it indicates；In calculating
Between variable x (n)=Ird(n)(Iir(n)-IirAnd y (n)=I (n-1))rd(n)(Iir(n)-Iir(n-1)), in order to write conveniently,
It is denoted as x respectively againnAnd yn；
S21, according to initial configuration as a result, calculate intermediate parameters；
Wherein, the present embodiment is first according to the initial value of data point number, the initial value of Counting statistics amount, it may be assumed that sn,0=n,With
sn,0Represent data point number；sn,1Represent xnSum；sn,2Represent ynSum；sn,3Represent xnQuadratic sum；sn,4Generation
Table xnynSum；sn,5Represent ynQuadratic sum；
In addition, above-mentioned statistic is substantially the single order and second moment of data, the overall information in sample is reflected.
Then, according to the value for the statistic being calculated, the intermediate parameters of equation of linear regression are calculated, it may be assumed that
With
Wherein, cn,11、cn,12、cn,21And cn,22Represent the intermediate parameters during recursive algorithm is realized.
S22, according to intermediate parameters, calculate the fitting coefficient of equation of linear regression, obtain equation of linear regression；
Specifically, the present embodiment calculates equation of linear regression Y=b1+b2The fitting coefficient b in n data point of Xn,1=
cn,11sn,2+cn,12sn,4And bn,2=cn,21sn,2+cn,22sn,4.Wherein, pulse blood oxygen signal characteristic value R is parameter bn,2.Its
In, b1And b2It is the undetermined parameter of regression equation；bn,1With bn,2For the b calculated when n data point1And b2, pulse blood oxygen signal spy
Value indicative R is parameter bn,2。
S23, according to equation of linear regression, calculate total sum of sguares of deviation from mean and residual sum of squares (RSS)；
S24, according to total sum of sguares of deviation from mean and residual sum of squares (RSS), calculate the confidence level of oxygen saturation measurement result.
Specifically, the present embodiment calculates total sum of sguares of deviation from meanResidual sum of squares (RSS) SSEn=bn, 1sn,2+bn,2sn,4, confidence level coefficient Cn=1-SSEn/SSTn。
S3, according to linear regression model (LRM), obtain the confidence level of oxygen saturation measurement result；
The confidence level that the present embodiment obtains is the confidence level coefficient C being calculated in step S24n=1-SSEn/SSTn。
S4, judge whether the confidence level of oxygen saturation measurement result meets threshold requirement, if so, output blood oxygen saturation
Spend the confidence level of measurement result；Conversely, S5 is thened follow the steps, until the confidence level of oxygen saturation measurement result meets threshold value and wants
It asks.
Specifically, whether the confidence level coefficient in the present embodiment judgment step S3 reaches preset threshold, if so, executing step
Rapid S7；Conversely, then return step S5, to carry out recurrence calculation next time.
S5, data point number is updated；
Specifically, after the data point number increase of the present embodiment are as follows: n=n+1.
S6, according to the update of data point as a result, being updated by recursive algorithm to linear regression model (LRM)；
Be further used as the preferred embodiment of step S6, the step S6 the following steps are included:
S61, according to the update of data point as a result, being updated to intermediate parameters；
Specifically, the present embodiment further calculates intermediate parameters according to result n=n+1 is updated:
Firstly, the value for updating statistic is as follows using recurrence formula:
sn+1,0=sn+ 1, sn+1,1=sn,1+xn+1, sn+1,2=sn,2+yn+1,sn+1,4=sn,4
+xn+1yn+1With
Then, using recurrence formula, the value for updating intermediate parameters is as follows:
S62, according to updated intermediate parameters, equation of linear regression is updated；
Specifically, the present embodiment further calculates equation of linear regression Y=b according to updated intermediate parameters1+b2X's
Coefficient bn+1,1=cn+1,11sn+1,2+cn+1,12sn+1,4And bn+1,2=cn+1,21sn+1,2+cn+1,22sn+1,4, wherein pulse blood oxygen signal
Characteristic value R is updated to parameter bn+1,2。
S63, according to updated equation of linear regression, total sum of sguares of deviation from mean and residual sum of squares (RSS) are updated；
S64, according to updated total sum of sguares of deviation from mean and residual sum of squares (RSS), oxygen saturation measurement result is set
Reliability is updated；If confidence level at this time does not meet threshold value, S5 is returned to step, to enter in terms of recursion next time
Calculate process.
Specifically, the present embodiment further calculates total sum of sguares of deviation from mean according to updated equation of linear regressionResidual sum of squares (RSS) SSEn+1=bn+1,1sn+1,2+bn+1,2sn+1,4, confidence level coefficient Cn+1=1-
SSEn+1/SSTn+1。
It is further used as preferred embodiment, described further comprising the steps of:
S7, according to linear regression model (LRM), generate pulse blood oxygen signal characteristic value.
In the present embodiment, when judging that obtaining confidence level coefficient reaches preset threshold in step S4, pulse blood oxygen is exported
Signal characteristic value R.
Corresponding with the method for Fig. 1, the embodiment of the invention also provides a kind of recursion of oxygen saturation measurement confidence level
System, comprising:
Initialization module, for carrying out initial configuration to data point number；
Module is constructed, is used for according to initial configuration as a result, building linear regression model (LRM)；
Module is obtained, for obtaining the confidence level of oxygen saturation measurement result according to linear regression model (LRM)；
Judgment module, for judging whether the confidence level of oxygen saturation measurement result meets threshold requirement, if so, defeated
The confidence level of oxygen saturation measurement result out；Conversely, then performing the next step suddenly, until the confidence of oxygen saturation measurement result
Degree meets threshold requirement；
Update module, for being updated to data point number；
Recursion module, for according to the update of data point as a result, be updated by recursive algorithm to linear regression model (LRM),
And it returns to execution and obtains module.
It is further used as preferred embodiment, the building module includes:
First computing unit is used for according to initial configuration as a result, calculating intermediate parameters；
Second computing unit, for calculating the fitting coefficient of equation of linear regression, obtaining linear regression according to intermediate parameters
Equation；
Third computing unit, for calculating total sum of sguares of deviation from mean and residual sum of squares (RSS) according to equation of linear regression；
4th computing unit, for calculating oxygen saturation measurement according to total sum of sguares of deviation from mean and residual sum of squares (RSS)
As a result confidence level.
It is further used as preferred embodiment, the recursion module includes:
First updating unit, for the update according to data point as a result, being updated to intermediate parameters；
Second updating unit, for being updated to equation of linear regression according to updated intermediate parameters；
Third updating unit, for being put down to total sum of sguares of deviation from mean and residual error according to updated equation of linear regression
Just and it is updated；
According to updated total sum of sguares of deviation from mean and residual sum of squares (RSS), to the confidence level of oxygen saturation measurement result
It is updated.
It is further used as preferred embodiment, further includes:
Generation module, for generating pulse blood oxygen signal characteristic value according to linear regression model (LRM).
The embodiment of the invention also provides a kind of recurrence systems of oxygen saturation measurement confidence level, comprising:
At least one processor；
At least one processor, for storing at least one program；
When at least one described program is executed by least one described processor, so that at least one described processor is realized
The recurrence method of the oxygen saturation measurement confidence level.
Suitable for this system embodiment, this system embodiment is implemented content in above method embodiment
Function is identical as above method embodiment, and the beneficial effect reached and above method embodiment beneficial effect achieved
It is identical.
In addition, the embodiment of the invention also provides a kind of storage mediums, wherein being stored with the executable instruction of processor, institute
The executable instruction of processor is stated when executed by the processor for executing the recursion of the oxygen saturation measurement confidence level
Method.
It is calculated in conclusion the present invention devises a set of recursion for calculating pulse blood oxygen signal characteristic value R and confidence level coefficient C
Method.The algorithm takes full advantage of the data of all sampled points, but without storing a large amount of initial data in operation, if only retaining
Dry statistic constantly updates last calculated result with this as intermediate variable.Thus, recursive algorithm of the invention
Avoid the need to storage initial data and caused by hardware resource waste, while also greatly improving arithmetic speed.Therefore, lead to
Cross the fortune that pulse blood oxygen signal characteristic value and confidence level coefficient are calculated using the completion of recursive algorithm energy real-time high-efficiency of the invention
It calculates, realizes that rapidly and efficiently pulse blood oxygen detection provides theories integration for hardware system.
It is to be illustrated to preferable implementation of the invention, but the present invention is not limited to the embodiment above, it is ripe
Various equivalent deformation or replacement can also be made on the premise of without prejudice to spirit of the invention by knowing those skilled in the art, this
Equivalent deformation or replacement are all included in the scope defined by the claims of the present application a bit.
Claims (10)
1. the recurrence method of oxygen saturation measurement confidence level, it is characterised in that: the following steps are included:
Initial configuration is carried out to data point number；
According to initial configuration as a result, building linear regression model (LRM)；
According to linear regression model (LRM), the confidence level of oxygen saturation measurement result is obtained；
Judge whether the confidence level of oxygen saturation measurement result meets threshold requirement, if so, output oxygen saturation measurement
As a result confidence level；Conversely, then performing the next step suddenly, until the confidence level of oxygen saturation measurement result meets threshold requirement；
Data point number is updated；
According to the update of data point as a result, being updated by recursive algorithm to linear regression model (LRM), and execution is returned according to line
Property regression model, obtain oxygen saturation measurement result confidence level the step of.
2. the recurrence method of oxygen saturation measurement confidence level according to claim 1, it is characterised in that: at the beginning of the basis
The step for beginningization configuration result, building linear regression model (LRM), comprising the following steps:
According to initial configuration as a result, calculating intermediate parameters；
According to intermediate parameters, the fitting coefficient of equation of linear regression is calculated, equation of linear regression is obtained；
According to equation of linear regression, total sum of sguares of deviation from mean and residual sum of squares (RSS) are calculated；
According to total sum of sguares of deviation from mean and residual sum of squares (RSS), the confidence level of oxygen saturation measurement result is calculated.
3. the recurrence method of oxygen saturation measurement confidence level according to claim 1, it is characterised in that: described according to number
The update at strong point is as a result, the step for being updated linear regression model (LRM) by recursive algorithm, comprising the following steps:
According to the update of data point as a result, being updated to intermediate parameters；
According to updated intermediate parameters, equation of linear regression is updated；
According to updated equation of linear regression, total sum of sguares of deviation from mean and residual sum of squares (RSS) are updated；
According to updated total sum of sguares of deviation from mean and residual sum of squares (RSS), the confidence level of oxygen saturation measurement result is carried out
It updates.
4. the recurrence method of oxygen saturation measurement confidence level according to claim 1, it is characterised in that: further include following
Step:
According to linear regression model (LRM), pulse blood oxygen signal characteristic value is generated.
5. the recurrence system of oxygen saturation measurement confidence level, it is characterised in that: include:
Initialization module, for carrying out initial configuration to data point number；
Module is constructed, is used for according to initial configuration as a result, building linear regression model (LRM)；
Module is obtained, for obtaining the confidence level of oxygen saturation measurement result according to linear regression model (LRM)；
Judgment module, for judging whether the confidence level of oxygen saturation measurement result meets threshold requirement, if so, output blood
The confidence level of oxygen saturation measurements result；Conversely, then performing the next step suddenly, until the confidence level of oxygen saturation measurement result is full
Sufficient threshold requirement；
Update module, for being updated to data point number；
Recursion module, for the update according to data point as a result, being updated by recursive algorithm to linear regression model (LRM), and return
Receipt row obtains module.
6. the recurrence system of oxygen saturation measurement confidence level according to claim 5, it is characterised in that: the building mould
Block includes:
First computing unit is used for according to initial configuration as a result, calculating intermediate parameters；
Second computing unit, for calculating the fitting coefficient of equation of linear regression, obtaining linear regression side according to intermediate parameters
Journey；
Third computing unit, for calculating total sum of sguares of deviation from mean and residual sum of squares (RSS) according to equation of linear regression；
4th computing unit, for calculating oxygen saturation measurement result according to total sum of sguares of deviation from mean and residual sum of squares (RSS)
Confidence level.
7. the recurrence system of oxygen saturation measurement confidence level according to claim 5, it is characterised in that: the recursion mould
Block includes:
First updating unit, for the update according to data point as a result, being updated to intermediate parameters；
Second updating unit, for being updated to equation of linear regression according to updated intermediate parameters；
Third updating unit is used for according to updated equation of linear regression, to total sum of sguares of deviation from mean and residual sum of squares (RSS)
It is updated；
According to updated total sum of sguares of deviation from mean and residual sum of squares (RSS), the confidence level of oxygen saturation measurement result is carried out
It updates.
8. the recurrence system of oxygen saturation measurement confidence level according to claim 5, it is characterised in that: further include:
Generation module, for generating pulse blood oxygen signal characteristic value according to linear regression model (LRM).
9. the recurrence system of oxygen saturation measurement confidence level, it is characterised in that: include:
At least one processor；
At least one processor, for storing at least one program；
When at least one described program is executed by least one described processor, so that at least one described processor is realized as weighed
Benefit requires the recurrence method of oxygen saturation measurement confidence level described in any one of 1-4.
10. a kind of storage medium, wherein being stored with the executable instruction of processor, it is characterised in that: the processor is executable
Instruction be used to execute when executed by the processor such as oxygen saturation measurement confidence level of any of claims 1-4
Recurrence method.
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| WO2020114190A1 (en) * | 2018-12-05 | 2020-06-11 | 深圳技术大学 | Recursion method and system for confidence degree of blood oxygen saturation measurement, and storage medium |
| CN112545461A (en) * | 2020-12-05 | 2021-03-26 | 深圳市美的连医疗电子股份有限公司 | Method, device and system for detecting non-invasive hemoglobin concentration value and computer readable storage medium |
| CN112603287A (en) * | 2020-12-16 | 2021-04-06 | 南昌逸勤科技有限公司 | Heart rate curve correction method and device applied to wearable equipment |
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| CN112603287A (en) * | 2020-12-16 | 2021-04-06 | 南昌逸勤科技有限公司 | Heart rate curve correction method and device applied to wearable equipment |
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