CN112932475A - Method and device for calculating blood oxygen saturation, electronic equipment and storage medium - Google Patents
Method and device for calculating blood oxygen saturation, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN112932475A CN112932475A CN202110139634.5A CN202110139634A CN112932475A CN 112932475 A CN112932475 A CN 112932475A CN 202110139634 A CN202110139634 A CN 202110139634A CN 112932475 A CN112932475 A CN 112932475A
- Authority
- CN
- China
- Prior art keywords
- initial
- signal
- photoplethysmography
- calculating
- oxygen saturation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 title claims abstract description 83
- 229910052760 oxygen Inorganic materials 0.000 title claims abstract description 83
- 239000001301 oxygen Substances 0.000 title claims abstract description 83
- 239000008280 blood Substances 0.000 title claims abstract description 81
- 210000004369 blood Anatomy 0.000 title claims abstract description 81
- 238000000034 method Methods 0.000 title claims description 46
- 238000013186 photoplethysmography Methods 0.000 claims abstract description 107
- 238000005070 sampling Methods 0.000 claims abstract description 39
- 238000004364 calculation method Methods 0.000 claims abstract description 35
- 238000012545 processing Methods 0.000 claims abstract description 19
- 238000007781 pre-processing Methods 0.000 claims abstract description 14
- 230000005484 gravity Effects 0.000 claims abstract description 12
- 238000005259 measurement Methods 0.000 claims description 24
- 230000008859 change Effects 0.000 claims description 20
- 238000002835 absorbance Methods 0.000 claims description 18
- 238000004590 computer program Methods 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 5
- 108010054147 Hemoglobins Proteins 0.000 description 11
- 102000001554 Hemoglobins Human genes 0.000 description 11
- 238000010586 diagram Methods 0.000 description 8
- 230000008569 process Effects 0.000 description 7
- 210000001519 tissue Anatomy 0.000 description 7
- 230000000737 periodic effect Effects 0.000 description 5
- 238000010521 absorption reaction Methods 0.000 description 4
- 238000011088 calibration curve Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 238000012986 modification Methods 0.000 description 4
- 230000004048 modification Effects 0.000 description 4
- 108010003320 Carboxyhemoglobin Proteins 0.000 description 3
- 108010061951 Methemoglobin Proteins 0.000 description 3
- 206010044565 Tremor Diseases 0.000 description 3
- 230000009471 action Effects 0.000 description 3
- 210000001367 artery Anatomy 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000033001 locomotion Effects 0.000 description 3
- 108010064719 Oxyhemoglobins Proteins 0.000 description 2
- 238000010009 beating Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 125000004122 cyclic group Chemical group 0.000 description 2
- 210000000624 ear auricle Anatomy 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000031700 light absorption Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000010349 pulsation Effects 0.000 description 2
- 230000036387 respiratory rate Effects 0.000 description 2
- 206010003658 Atrial Fibrillation Diseases 0.000 description 1
- 208000024172 Cardiovascular disease Diseases 0.000 description 1
- 208000031226 Hyperlipidaemia Diseases 0.000 description 1
- 206010020772 Hypertension Diseases 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000036772 blood pressure Effects 0.000 description 1
- 210000000988 bone and bone Anatomy 0.000 description 1
- 230000000747 cardiac effect Effects 0.000 description 1
- 230000008602 contraction Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000003205 diastolic effect Effects 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 235000019800 disodium phosphate Nutrition 0.000 description 1
- 210000002615 epidermis Anatomy 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 210000004072 lung Anatomy 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- 238000006213 oxygenation reaction Methods 0.000 description 1
- 230000000149 penetrating effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000005622 photoelectricity Effects 0.000 description 1
- 230000002028 premature Effects 0.000 description 1
- 230000000241 respiratory effect Effects 0.000 description 1
- 230000036391 respiratory frequency Effects 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 210000003491 skin Anatomy 0.000 description 1
- 210000003462 vein Anatomy 0.000 description 1
Images
Classifications
-
- 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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02416—Detecting, measuring or recording pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
-
- 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
-
- 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
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Surgery (AREA)
- Public Health (AREA)
- Pathology (AREA)
- Veterinary Medicine (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Physiology (AREA)
- Signal Processing (AREA)
- Cardiology (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Psychiatry (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Optics & Photonics (AREA)
- Power Engineering (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The application provides a calculation method and device of blood oxygen saturation, electronic equipment and a storage medium, and relates to the technical field of pulse wave signal processing. Acquiring an initial photoplethysmogram signal of a person to be tested in a preset time period by collection; adjusting the curve gravity center of the initial photoplethysmography signal to coincide with the origin of coordinates, and acquiring the preprocessed initial photoplethysmography signal; according to the sampling index value, baseline drift removal is carried out on the initial photoplethysmography signals after preprocessing, and the processed photoplethysmography signals are obtained.
Description
Technical Field
The present disclosure relates to the field of pulse wave signal technology, and in particular, to a method and an apparatus for calculating blood oxygen saturation, an electronic device and a storage medium.
Background
With the development of economy, the living standard of people is improved, high fat intake and low exercise amount become common living modes of people, and hypertension and hyperlipidemia have become the most dangerous diseases in recent years. The physiological parameters of electrocardio, blood pressure, blood oxygen and the like are important physiological parameters for preventing and analyzing cardiovascular diseases.
Currently, generally, during measurement, measurement is mainly performed by a non-invasive blood Oxygen measuring instrument, which includes a fingerstall type photoelectric sensor, wherein during measurement, the fingerstall type photoelectric sensor is required to be sleeved on a human finger, the finger is used as a transparent container for containing hemoglobin, based on a Photoplethysmography (PPG), red light with a wavelength of 660nm and near infrared light with a wavelength of 940nm are used as incident light sources, the light transmission intensity passing through a tissue bed is measured, a PPG signal of a subject is acquired, and a human blood Oxygen saturation level (SO 2) is calculated and displayed according to the PPG signal of the subject.
However, due to differences among subjects, the acquired PPG signal may have baseline drift due to respiratory rate, muscle tremor, and physiological changes in the body to various stimuli, resulting in an inaccurate calculation of blood oxygen saturation.
Disclosure of Invention
An object of the present application is to provide a method, an apparatus, an electronic device and a storage medium for calculating blood oxygen saturation, which can obtain more accurate blood oxygen saturation, in view of the above deficiencies in the prior art.
In order to achieve the above purpose, the technical solutions adopted in the embodiments of the present application are as follows:
in a first aspect, the present invention provides a method for calculating blood oxygen saturation, including:
acquiring an initial photoplethysmography signal of a person to be tested within a preset time period, wherein the initial photoplethysmography signal comprises: an initial photoplethysmography signal corresponding to the red light and an initial photoplethysmography signal corresponding to the infrared light;
adjusting the curve gravity center of the initial photoplethysmography signal to coincide with the origin of coordinates, and acquiring a preprocessed initial photoplethysmography signal;
according to the sampling index value, baseline drift removal is carried out on the preprocessed initial photoplethysmographic signal, and the processed photoplethysmographic signal is obtained;
and calculating and obtaining the blood oxygen saturation of the person to be tested according to the processed photoplethysmogram signal.
In an optional embodiment, the performing baseline wandering on the preprocessed initial photoplethysmographic signal according to the sampling index value to obtain the processed photoplethysmographic signal includes:
acquiring the average slope of the initial photoplethysmographic signal after the preprocessing according to a plurality of sampling index values;
and performing baseline-removing drift operation on the preprocessed initial photoplethysmographic signal according to the average slope to obtain the processed photoplethysmographic signal.
In an optional embodiment, the obtaining an average slope of the preprocessed initial photoplethysmographic signal according to the plurality of sampling index values includes:
using a formula
Obtaining the average slope of the preprocessed initial photoplethysmography signals, wherein t represents a sampling index value y'tDenotes the average slope, ytIndicating initial photoelectricity after pretreatmentIn the volume pulse wave signal, if the total number of samples N is an even number, x is equal to N/2, and if the total number of samples N is an odd number, x is equal to (N-1)/2.
In an optional embodiment, the calculating and acquiring the blood oxygen saturation of the person to be tested according to the processed photoplethysmographic signal includes:
calculating a correlation coefficient between the photoplethysmography signals corresponding to the red light and the infrared light according to the processed photoplethysmography signals;
screening the processed photoplethysmography signals according to the correlation coefficient and a preset threshold value to obtain screened photoplethysmography signals;
and calculating and obtaining the blood oxygen saturation of the person to be tested according to the screened photoplethysmogram signals.
In an optional embodiment, the calculating and acquiring the blood oxygen saturation of the person to be tested according to the screened photoplethysmographic signal includes:
calculating and obtaining a relative change measurement value of the absorbance of the red light and the infrared light according to the screened photoplethysmographic signals;
and calculating and obtaining the blood oxygen saturation of the person to be tested according to the relative change measurement value of the red light and the infrared light absorbance and a preset calculation formula.
In an alternative embodiment, the method further comprises:
according to the screened photoplethysmography signals, calculating and obtaining autocorrelation coefficients of the photoplethysmography signals corresponding to the screened red light, or autocorrelation coefficients of the photoplethysmography signals corresponding to the screened infrared light;
generating a red light autocorrelation waveform or an infrared light autocorrelation waveform according to the autocorrelation coefficient of the photoplethysmographic signal corresponding to the screened red light or the autocorrelation coefficient of the photoplethysmographic signal corresponding to the screened infrared light;
and calculating and obtaining the pulse rate of the person to be tested according to the red light autocorrelation waveform or the infrared light autocorrelation waveform.
In an optional embodiment, the calculating and acquiring the pulse rate of the person to be tested according to the red light autocorrelation waveform or the infrared light autocorrelation waveform includes:
and calculating and obtaining the pulse rate of the person to be tested according to the red light autocorrelation waveform or the first period waveform in the infrared light autocorrelation waveform.
In a second aspect, the present invention provides a device for measuring blood oxygen saturation, comprising:
the acquisition module is used for acquiring and acquiring an initial photoplethysmogram signal of a person to be tested in a preset time period, wherein the initial photoplethysmogram signal comprises: an initial photoplethysmography signal corresponding to the red light and an initial photoplethysmography signal corresponding to the infrared light;
the adjusting module is used for adjusting the curve gravity center of the initial photoplethysmographic signal to coincide with the origin of coordinates, and acquiring the preprocessed initial photoplethysmographic signal;
the processing module is used for carrying out baseline wandering on the preprocessed initial photoplethysmography signals according to the sampling index value to obtain the processed photoplethysmography signals;
and the calculation module is used for calculating and acquiring the blood oxygen saturation of the person to be tested according to the processed photoplethysmogram signals.
In an optional embodiment, the processing module is specifically configured to obtain an average slope of the preprocessed initial photoplethysmographic signal according to a plurality of the sampling index values;
and performing baseline-removing drift operation on the preprocessed initial photoplethysmographic signal according to the average slope to obtain the processed photoplethysmographic signal.
In an alternative embodiment, the processing module is specifically adapted to use a formula
Obtaining the average slope of the preprocessed initial photoplethysmography signals, wherein t represents a sampling index value y'tDenotes the average slope, ytAnd the initial photoplethysmographic signal after preprocessing is shown, wherein if the total number of samples N is an even number, x is equal to N/2, and if the total number of samples N is an odd number, x is equal to (N-1)/2.
In an optional embodiment, the calculating module is specifically configured to calculate, according to the processed photoplethysmography pulse wave signal, a correlation coefficient between the photoplethysmography pulse wave signal corresponding to the red light and the photoplethysmography pulse wave signal corresponding to the infrared light after the processing;
screening the processed photoplethysmography signals according to the correlation coefficient and a preset threshold value to obtain screened photoplethysmography signals;
and calculating and obtaining the blood oxygen saturation of the person to be tested according to the screened photoplethysmogram signals.
In an optional embodiment, the calculation module is specifically configured to calculate and obtain a measurement value of a relative change in absorbance of red light and infrared light according to the filtered photoplethysmographic pulse wave signal;
and calculating and obtaining the blood oxygen saturation of the person to be tested according to the relative change measurement value of the red light and the infrared light absorbance and a preset calculation formula.
In an optional embodiment, the calculating module is further configured to calculate and obtain an autocorrelation coefficient of the photoplethysmography signal corresponding to the filtered red light or an autocorrelation coefficient of the photoplethysmography signal corresponding to the filtered infrared light according to the filtered photoplethysmography signal;
generating a red light autocorrelation waveform or an infrared light autocorrelation waveform according to the autocorrelation coefficient of the photoplethysmographic signal corresponding to the screened red light or the autocorrelation coefficient of the photoplethysmographic signal corresponding to the screened infrared light;
and calculating and obtaining the pulse rate of the person to be tested according to the red light autocorrelation waveform or the infrared light autocorrelation waveform.
In an optional embodiment, the calculating module is specifically configured to calculate and obtain a pulse rate of the person to be tested according to the red light autocorrelation waveform or a first periodic waveform in the infrared light autocorrelation waveform.
In a third aspect, the present invention provides an electronic device comprising: a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, when an electronic device runs, the processor and the storage medium are communicated through the bus, and the processor executes the machine-readable instructions to execute the steps of the blood oxygen saturation calculation method according to any one of the foregoing embodiments.
In a fourth aspect, the present invention provides a storage medium having a computer program stored thereon, the computer program being executed by a processor to perform the steps of the method for calculating blood oxygen saturation as described in any one of the preceding embodiments.
The beneficial effect of this application is:
in the calculation method, the apparatus, the electronic device and the storage medium for blood oxygen saturation, an initial photoplethysmographic signal of a person to be tested in a preset time period is acquired by collecting, where the initial photoplethysmographic signal includes: an initial photoplethysmography signal corresponding to the red light and an initial photoplethysmography signal corresponding to the infrared light; adjusting the curve gravity center of the initial photoplethysmography signal to coincide with the origin of coordinates, and acquiring the preprocessed initial photoplethysmography signal; according to the sampling index value, baseline drift removal is carried out on the initial photoplethysmogram signal after preprocessing, and the processed photoplethysmogram signal is obtained.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic flowchart of a method for calculating blood oxygen saturation according to an embodiment of the present application;
fig. 2 is a schematic flow chart of another calculation method of blood oxygen saturation provided by the embodiment of the present application;
fig. 3 is a schematic diagram of a photoplethysmographic signal according to an embodiment of the present disclosure;
fig. 4 is a schematic flowchart of another calculation method of blood oxygen saturation according to an embodiment of the present application;
fig. 5 is a schematic flowchart of another calculation method of blood oxygen saturation according to an embodiment of the present application;
fig. 6 is a schematic flowchart of a further calculation method of blood oxygen saturation according to an embodiment of the present application;
FIG. 7 is a diagram illustrating a red light autocorrelation waveform according to an embodiment of the present disclosure;
fig. 8 is a functional block diagram of a device for calculating blood oxygen saturation according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Before introducing this application, the relevant terms referred to in this application will first be explained.
Pulse rate: the frequency of the beating of the finger arteries is the same as the heart rate under the normal condition, the heart rate is the frequency of the beating of the heart, generally, a person beats 60-90 times per minute, but under the conditions of exercise, stress and the like, the condition of accelerating the heartbeat occurs, and the pulse rate is lower than the heart rate when atrial fibrillation or premature contraction occurs.
Blood Oxygen saturation (Oxygen saturation, SaO 2): the percentage of the volume of oxygenated hemoglobin (HbO2) bound by oxygen in blood to the volume of total conjugated reduced hemoglobin (Hb), i.e. the concentration of blood oxygen in blood, which is an important physiological parameter of the respiratory cycle, and the monitoring artery SaO2 can estimate the oxygenation of the lung and the oxygen carrying capacity of hemoglobin to monitor whether the tissues of our human body are healthy. The oxygen consumed by the human body mainly comes from hemoglobin (four hemoglobin exists in normal blood: oxyhemoglobin (HbO2), reduced hemoglobin (Hb), carboxyhemoglobin (CoHb) and methemoglobin (MetHb), wherein the reduced hemoglobin reversibly combines with the oxygen, and the carboxyhemoglobin and the methemoglobin do not combine with the oxygen, and the oxygen saturation of the blood of a person to be tested is generally measured by a non-invasive oximeter in the prior art.
The nondestructive blood oxygen measuring instrument: the measurement process usually does not need to draw blood from a patient, and the working principle is based on a Photoplethysmography (PPG) technology, and the double-beam transmission method is adopted to measure the blood oxygen saturation according to the difference of the light absorption rate of blood with different oxygen contents to different wavelengths. A typical oximeter has two light emitting diodes facing the part to be measured (usually finger tip or ear lobe) of a patient, wherein one diode emits a red light beam with a wavelength of 660nm, and the other diode emits a near infrared light beam with a wavelength of 905, 910 or 940nm, and because the absorption rates of the two wavelengths by the oxygen-containing hemoglobin are greatly different from those of oxygen-free hemoglobin (the absorption rate of 660mm red light by the reduced hemoglobin is relatively strong, and the absorption length of 910nm infrared light is relatively weak), by using this property, the arterial oxygen saturation of the tissue (SaO2) is calculated by detecting the ratio of the absorbance change rates of different wavelengths of red light and infrared light at the part of the peripheral tissue of the human body, such as finger or ear lobe, but because the biological tissue is a complex optical system with strong scattering, weak absorption and anisotropy, the ratio of the Lamborborborborber-Lambert law (Beer-Lambert/IR and arterial saturated blood oxygen law) is not completely satisfied The functional relation of the degree (SaO2) is linear relation), thereby causing the difficulty of establishing a mathematical model expressing the relation between the relative change measurement values of the red light and the infrared light absorbance and the arterial oxygen saturation (SaO2), only determining the corresponding relation between the relative change measurement values of the red light and the infrared light absorbance and the SaO2 through an experimental method, namely a calibration curve, completing the pre-calibration of the oximeter before leaving factory through the calibration curve, and further calculating the blood oxygen saturation according to the calibration curve during actual measurement. Most pulse oximeter manufacturers experimentally obtain an empirical calibration curve to complete the product.
Wherein, when the non-invasive oximeter works, two light emitting diodes in the oximeter can emit 660nm red light and 940nm infrared light, and illuminate the part containing artery blood vessels alternately in a time-sharing way, the red light and the infrared light can be reflected to a photosensitive sensor in the oximeter after penetrating through skin tissues, and the transmitted light intensity is detected by a photoelectric tube and the signals of the two wavelengths are separated, so as to obtain a direct current component and an alternating current component corresponding to the two wavelengths respectively, wherein, the direct current component is caused by light absorption caused by non-volatile tissues such as epidermis, muscles, bones and veins, the alternating current component is caused by periodic changes of HbO2 and Hb concentration of arterial blood along with the pulsation of the blood, the alternating current component can represent the change of the blood volume between the systolic period and the diastolic period of the cardiac period, and the alternating current component depends on the heart rate, the blood oxygen saturation can be calculated according to the dc component and the ac component corresponding to the red light and the infrared light, respectively. Of course, it should be noted that the heart rate may also be obtained by calculating according to the pulsation law of the alternating current component.
However, when the existing non-invasive oximeter is used to measure the blood oxygen saturation of a subject, due to the individual difference of the subject, the acquired PPG signal may generate baseline drift due to respiratory frequency, muscle tremor and physiological changes in the body to various stimuli, so that the calculation result of the blood oxygen saturation is not accurate enough.
Fig. 1 is a schematic flow chart of a method for calculating blood oxygen saturation level according to an embodiment of the present disclosure, an execution main body of the method may be a processing device, the processing device may be a terminal or a server, for example, the terminal may be any one of a desktop computer, a laptop computer, a tablet computer, a smart phone, an oxyhemoglobin saturation measuring instrument, an intelligent wearable device (a watch, a bracelet, an earphone), a heart rate belt, and the like, and the processing device may also be another type of device having a processing function, which is not limited in this embodiment of the present disclosure. As shown in fig. 1, the method for calculating the blood oxygen saturation level may include:
s101, acquiring an initial photoplethysmogram signal of a person to be tested in a preset time period.
Wherein the initial photoplethysmography pulse wave signal comprises: an initial photoplethysmographic signal corresponding to red light and an initial photoplethysmographic signal corresponding to infrared light.
Optionally, an initial Photoplethysmography (PPG) pulse wave signal of the subject within a preset time period may be acquired based on a PPG technique, and the acquired initial Photoplethysmography pulse wave signal may include an initial Photoplethysmography pulse wave signal corresponding to red light and an initial Photoplethysmography pulse wave signal corresponding to infrared light. The red light may be a 660nm red light beam, and the infrared light may be a 905, 910, or 940nm near-infrared light beam, which is not limited herein. The preset time period may be 1 minute, 2 minutes, 5 minutes, etc. according to an actual application scenario, and is not limited herein. In some embodiments, the signal value in the initial photoplethysmographic signal may indicate the intensity of the reflected light, or alternatively, may indicate a voltage value corresponding to the intensity of the reflected light, which is not limited herein. It can be understood that, in the case of the reflected light intensity, the voltage value corresponding to each reflected light intensity can be calculated according to the preset relationship between the reflected light intensity and the voltage.
S102, adjusting the curve gravity center of the initial photoplethysmographic signal to coincide with the origin of coordinates, and obtaining the initial photoplethysmographic signal after preprocessing.
After acquiring and acquiring an initial photoplethysmographic signal of a person to be tested within a preset time period, acquiring a curve gravity center of the initial photoplethysmographic signal, and coinciding the curve gravity center with a coordinate origin of a coordinate system where the initial photoplethysmographic signal is located, so that the preprocessed initial photoplethysmographic signal can be approximately symmetrical based on a vertical coordinate axis, which is convenient for subsequent calculation, wherein a horizontal axis of the coordinate system where the initial photoplethysmographic signal is located can represent a sampling number, and a vertical axis can represent a signal amplitude, but not limited thereto.
And S103, according to the sampling index value, performing baseline wandering on the preprocessed initial photoplethysmographic signal to obtain the processed photoplethysmographic signal.
The sampling index value may be understood as an index value corresponding to the initial photoplethysmographic signal after the preprocessing, and a value range of the sampling index value may be obtained according to a sampling number of the initial photoplethysmographic signal, for example, sampling is performed in a preset time period, which is not limited herein. It can be understood that, since the center of gravity of the curve of the preprocessed initial photoplethysmographic pulse wave signal coincides with the origin of coordinates, some of the curve is located on the negative half axis of the horizontal axis, and therefore, the sampling number of the horizontal axis of the preprocessed initial photoplethysmographic pulse wave signal needs to be converted, and the sampling index value is used for marking in the present application. Optionally, if the number of samples N is even, the value of the sample index value may be [ - (N-1)/2, (N-1)/2], and if the number of samples N is odd, the value of the sample index value may be [ - (N-1)/2], but not limited thereto.
Among these, baseline drift may be a noise signal caused by respiratory rate, muscle tremor, and physiological changes in the body to various stimuli, often appearing as a slowly varying curve. According to the sampling index value corresponding to the preprocessed initial photoplethysmographic signal, baseline wandering can be removed from the preprocessed initial photoplethysmographic signal, so that baseline wandering interference can be removed from the processed photoplethysmographic signal.
And S104, calculating and obtaining the blood oxygen saturation of the person to be tested according to the processed photoplethysmogram signals.
Based on the embodiment, because baseline drift removal operation is performed on the initial photoplethysmographic signal, more accurate blood oxygen saturation can be obtained when calculating and obtaining the blood oxygen saturation of the person to be tested according to the processed photoplethysmographic signal.
To sum up, the calculation method of blood oxygen saturation provided by the embodiment of the present application obtains an initial photoplethysmographic signal of a person to be tested within a preset time period by acquiring, where the initial photoplethysmographic signal includes: an initial photoplethysmography signal corresponding to the red light and an initial photoplethysmography signal corresponding to the infrared light; adjusting the curve gravity center of the initial photoplethysmography signal to coincide with the origin of coordinates, and acquiring the preprocessed initial photoplethysmography signal; according to the sampling index value, baseline drift removal is carried out on the initial photoplethysmogram signal after preprocessing, and the processed photoplethysmogram signal is obtained.
Fig. 2 is a schematic flowchart of another method for calculating blood oxygen saturation according to an embodiment of the present disclosure. Optionally, as shown in fig. 2, the performing baseline wandering on the preprocessed initial photoplethysmographic signal according to the sampling index value to obtain the processed photoplethysmographic signal includes:
s201, acquiring the average slope of the initial photoplethysmographic signal after preprocessing according to the plurality of sampling index values.
S202, performing baseline wandering operation on the preprocessed initial photoplethysmographic signal according to the average slope, and obtaining the processed photoplethysmographic signal.
In some embodiments, when performing the baseline wandering operation, the average slope of the preprocessed initial photoplethysmographic signal may be obtained according to the sampling index values and the signal values corresponding to the sampling index values, and the average slope may be represented by a straight line equation, where the straight line corresponding to the straight line equation may be a straight line passing through the origin of coordinates. Based on the obtained average slope, the baseline wandering operation may be performed on the preprocessed initial photoplethysmographic signal, wherein the average slope value corresponding to each sampling index value may be subtracted from the processed photoplethysmographic signal value corresponding to each sampling index value, so that the processed photoplethysmographic signal value corresponding to each sampling index value may be obtained, that is, the processed photoplethysmographic signal may be obtained.
By applying the embodiment of the application, the baseline wandering operation of the initial photoplethysmography signal can be realized without improving the hardware of the processing equipment, and based on the content, the processing process of the application has the characteristic of simple calculation.
Optionally, the obtaining the average slope of the preprocessed initial photoplethysmographic signal according to the plurality of sampling index values may include:
using a formula
Acquiring the average slope of the preprocessed initial photoplethysmography signals, wherein t represents a sampling index value y'tDenotes the average slope, ytAnd the initial photoplethysmographic signal after preprocessing is shown, wherein if the total number of samples N is an even number, x is equal to N/2, and if the total number of samples N is an odd number, x is equal to (N-1)/2. Through the formula, a corresponding average slope can be calculated for each sampling index value, and then baseline wander removing operation can be performed on the preprocessed initial photoplethysmographic pulse wave signal according to the average slope.
Fig. 3 is a schematic diagram of a photoplethysmographic signal according to an embodiment of the present disclosure. As shown in fig. 3, the curve S3 represents the initial photoplethysmographic signal after preprocessing, the straight line S4 represents the straight line corresponding to the average slope equation, and the curve S5 represents the processed photoplethysmographic signal.
Based on the above embodiment, in consideration of the practical application scenario, there may be a case where the movement amplitude of the person to be tested is large (motion artifact may be introduced), or a case where external light interference is large, which causes the correlation between the photoplethysmographic signal corresponding to red light and the photoplethysmographic signal corresponding to infrared light to be poor, that is, the quality of the acquired initial photoplethysmographic pulse signal is poor, and a relatively accurate blood oxygen saturation level cannot be obtained.
Fig. 4 is a schematic flowchart of another method for calculating blood oxygen saturation according to an embodiment of the present application. Alternatively, as shown in fig. 4, the calculating and obtaining the blood oxygen saturation of the person to be tested according to the processed photoplethysmographic signal may include:
s301, calculating a correlation coefficient between the photoplethysmography signals corresponding to the processed red light and the photoplethysmography signals corresponding to the processed infrared light according to the processed photoplethysmography signals.
The correlation coefficient between the two signals can be calculated according to the photoplethysmography signal corresponding to the processed red light and the photoplethysmography signal corresponding to the infrared light, so as to further judge the signal quality of the processed photoplethysmography signal. Alternatively, the correlation coefficient between the two signals may be calculated based on a calculation formula of pearson correlation coefficient, the pearson correlation coefficient value is between-1 and 1, and represents a negative correlation and a positive correlation, respectively, although it should be noted that the actual calculation formula is not limited thereto.
For example, formulas may be employed
And calculating, where β denotes a correlation coefficient, t denotes a sampling index value, x denotes N/2 if the total number of samples N is an even number, x denotes (N-1)/2 if the total number of samples N is an odd number, x (t) denotes a photoplethysmographic signal corresponding to red light, and y (t) denotes a photoplethysmographic signal corresponding to infrared light.
S302, screening the processed photoplethysmogram signals according to the correlation coefficient and a preset threshold value, and obtaining the screened photoplethysmogram signals.
Optionally, the preset threshold, that is, the correlation coefficient threshold, may be set according to an empirical value or an actual application scenario, and a value may be 0.2, 0.3, 0.4, and is not limited herein.
After the correlation coefficient is obtained, a period of the photoplethysmography signal may be taken as a unit, the correlation coefficient of the photoplethysmography signal corresponding to the red light and the correlation coefficient of the photoplethysmography signal corresponding to the infrared light in each period are sequentially compared with the preset threshold, and optionally, if the correlation coefficient of the two signals in a certain period is smaller than the preset threshold, which indicates that the correlation of the two signals in the period is poor, the photoplethysmography signal in the period may be filtered, and the filtered photoplethysmography signal may be obtained.
And S303, calculating and obtaining the blood oxygen saturation of the person to be tested according to the screened photoplethysmogram signals.
It can be understood that, based on the above operations, in the filtered photoplethysmography signals, the correlation between the photoplethysmography signal corresponding to the red light and the photoplethysmography signal corresponding to the infrared light is strong, and then, based on the filtered photoplethysmography signals, the obtained blood oxygen saturation of the person to be tested is calculated more accurately.
Fig. 5 is a schematic flowchart of another method for calculating blood oxygen saturation according to an embodiment of the present application. Optionally, as shown in fig. 5, the calculating and obtaining the blood oxygen saturation of the person to be tested according to the screened photoplethysmographic pulse wave signals includes:
s401, calculating and obtaining a relative change measurement value of red light and infrared light absorbance according to the screened photoplethysmography signals.
Wherein, when acquiring the filtered photoplethysmography signals, the method can be implemented according to a preset formula:
calculating to obtain a relative change measurement value of the absorbance of the red light and the infrared light, wherein R represents the relative change measurement value of the absorbance of the red light and the infrared light, ACRedRepresenting the AC component, DC, in the photoplethysmographic signal corresponding to the screened red lightRedRepresenting the DC component, AC, in the photoplethysmographic signal corresponding to the screened red lightIRRepresenting the AC component, DC, in the photoplethysmographic signal corresponding to the filtered infrared lightIRAnd the direct current component in the photoplethysmography signals corresponding to the filtered infrared light is represented. Of course, the actual calculation formula is not limited to this, and may be flexibly set according to the actual application scenario.
S402, calculating and acquiring the blood oxygen saturation of the person to be tested according to the relative change measurement value of the red light and the infrared light absorbance and a preset calculation formula.
After the relative change measurement value of the absorbance of the red light and the infrared light is obtained, the relative change measurement value of the absorbance of the red light and the infrared light can be substituted into a preset calculation formula, and the blood oxygen saturation of the person to be tested is obtained through calculation. Alternatively, the preset calculation formula may be: the SpO2 is 104-17R, where SpO2 represents the blood oxygen saturation, and R represents the relative change measurement of the absorbance of red light and infrared light, but the preset calculation formula is not limited thereto.
Fig. 6 is a schematic flowchart of another method for calculating blood oxygen saturation according to an embodiment of the present application. Based on the above embodiment, in some application scenarios, the pulse rate of the person to be tested may need to be measured, and considering that the change of the photoplethysmographic pulse wave signal is irregular, if the pulse rate of the person to be tested is directly obtained according to the photoplethysmographic pulse wave signal corresponding to the filtered red light or the photoplethysmographic pulse wave signal corresponding to the filtered infrared light, it is difficult to determine the period of the photoplethysmographic pulse wave signal, and further the calculated pulse rate is inaccurate. In view of the above, optionally, as shown in fig. 6, the method further includes:
s501, according to the filtered photoplethysmography signals, calculating and obtaining autocorrelation coefficients of the photoplethysmography signals corresponding to the filtered red light, or autocorrelation coefficients of the photoplethysmography signals corresponding to the filtered infrared light.
S502, generating a red light autocorrelation waveform or an infrared light autocorrelation waveform according to the autocorrelation coefficient of the photoplethysmographic signal corresponding to the screened red light or the autocorrelation coefficient of the photoplethysmographic signal corresponding to the screened infrared light.
The pulse rate of the person to be tested can be obtained by calculation according to the photoplethysmography signals corresponding to the screened red light, or can be obtained by calculation according to the photoplethysmography signals corresponding to the screened infrared light, which is not limited herein.
The embodiment of the application describes that the pulse rate of the person to be tested is calculated and obtained according to the photoplethysmography signals corresponding to the screened red light as an example, the autocorrelation coefficients of the photoplethysmography signals corresponding to the screened red light can be calculated and obtained in a cyclic left-shift or cyclic right-shift manner, and a series of autocorrelation coefficients are linked to generate a red light autocorrelation waveform, so that the period parameters of the photoplethysmography signals corresponding to the red light can be more clearly reflected through the red light autocorrelation waveform. For the generation process of the infrared light autocorrelation waveform, reference may be made to the generation process of the infrared light autocorrelation waveform, which is not described herein again.
S503, calculating and obtaining the pulse rate of the person to be tested according to the red light autocorrelation waveform or the infrared light autocorrelation waveform.
Based on the above description, the pulse rate of the person to be tested can be further calculated and obtained according to the relationship between the cycle parameter and the pulse rate, by obtaining the cycle parameter of the photoplethysmographic signal corresponding to the red light according to the red light autocorrelation waveform, or the infrared light autocorrelation waveform, or obtaining the cycle parameter of the photoplethysmographic signal corresponding to the infrared light according to the cycle parameter and the pulse rate.
By applying the embodiment of the application, on the basis of the embodiment, the pulse rate of the person to be tested can be calculated and obtained, and the applicability of the calculation method of the application is improved.
Optionally, the calculating and obtaining the pulse rate of the person to be tested according to the red light autocorrelation waveform or the infrared light autocorrelation waveform may include:
and calculating and acquiring the pulse rate of the person to be tested according to the red light autocorrelation waveform or the first period waveform in the infrared light autocorrelation waveform.
In some embodiments, the calculated autocorrelation coefficient is more accurate as the distance that the user can move is less, and therefore, the pulse rate of the person to be tested can be obtained by calculation according to the first periodic waveform in the red light autocorrelation waveform. Of course, the actual calculation method is not limited to this, and the pulse rate of the person to be tested may also be calculated by selecting the periodic waveform at the middle position of the red light autocorrelation waveform, or the average period of the red light autocorrelation waveform may be calculated, and the pulse rate of the person to be tested may be calculated according to the average period.
Fig. 7 is a schematic diagram of a red light autocorrelation waveform according to an embodiment of the present disclosure. As shown in fig. 7, S5 represents the photoplethysmographic signal corresponding to the screened red light, and S6 represents the red light autocorrelation waveform, which shows that it is difficult to determine when determining the signal period directly according to the photoplethysmographic signal corresponding to the screened red light, but it is easier to determine when determining the signal period according to the red light autocorrelation waveform, so that the pulse rate of the person to be tested can be obtained by calculation with improved accuracy by applying the embodiment of the present application.
In summary, the calculation method of the blood oxygen saturation provided by the embodiment of the application has the characteristic of simple calculation, can quickly remove baseline drift, dynamically adapt to different testees, can also filter out measurement interference caused by slight movement of the testees, and obtains more accurate blood oxygen saturation and pulse rate through measurement.
Fig. 8 is a functional block diagram of a device for calculating blood oxygen saturation level according to an embodiment of the present application, the basic principle and the technical effect of the device are the same as those of the corresponding method embodiment, and for a brief description, the corresponding contents in the method embodiment may be referred to for parts not mentioned in this embodiment. As shown in fig. 8, the measuring apparatus 100 may include:
the collecting module 110 is configured to collect and obtain an initial photoplethysmogram signal of a to-be-tested person within a preset time period, where the initial photoplethysmogram signal includes: an initial photoplethysmography signal corresponding to the red light and an initial photoplethysmography signal corresponding to the infrared light;
the adjusting module 120 is configured to adjust a curve center of gravity of the initial photoplethysmographic signal to coincide with the origin of coordinates, and obtain a preprocessed initial photoplethysmographic signal;
the processing module 130 is configured to perform baseline wandering on the preprocessed initial photoplethysmographic signal according to the sampling index value, and obtain a processed photoplethysmographic signal;
and the calculating module 140 is used for calculating and acquiring the blood oxygen saturation of the person to be tested according to the processed photoplethysmogram signals.
In an optional embodiment, the processing module 130 is specifically configured to obtain an average slope of the preprocessed initial photoplethysmographic signal according to a plurality of sampling index values; and performing baseline wandering removal operation on the initial photoplethysmographic signal after the preprocessing according to the average slope to obtain the processed photoplethysmographic signal.
In an alternative embodiment, the processing module 130 is specifically configured to use a formula
Acquiring the average slope of the preprocessed initial photoplethysmography signals, wherein t represents a sampling index value y'tDenotes the average slope, ytAnd the initial photoplethysmographic signal after preprocessing is shown, wherein if the total number of samples N is an even number, x is equal to N/2, and if the total number of samples N is an odd number, x is equal to (N-1)/2.
In an optional embodiment, the calculating module 140 is specifically configured to calculate, according to the processed photoplethysmography pulse wave signal, a correlation coefficient between the photoplethysmography pulse wave signal corresponding to the processed red light and the photoplethysmography pulse wave signal corresponding to the infrared light; screening the processed photoplethysmography signals according to the correlation coefficient and a preset threshold value to obtain screened photoplethysmography signals; and calculating and obtaining the blood oxygen saturation of the person to be tested according to the screened photoplethysmogram signals.
In an optional embodiment, the calculating module 140 is specifically configured to calculate and obtain a measurement value of relative change of absorbance of red light and infrared light according to the filtered photoplethysmographic pulse wave signal; and calculating and acquiring the blood oxygen saturation of the person to be tested according to the relative change measurement value of the red light and the infrared light absorbance and a preset calculation formula.
In an optional embodiment, the calculating module 140 is further configured to calculate and obtain an autocorrelation coefficient of a photoplethysmographic signal corresponding to the filtered red light or an autocorrelation coefficient of a photoplethysmographic signal corresponding to the filtered infrared light according to the filtered photoplethysmographic pulse signal; generating a red light autocorrelation waveform or an infrared light autocorrelation waveform according to the autocorrelation coefficient of the photoplethysmogram signal corresponding to the screened red light or the autocorrelation coefficient of the photoplethysmogram signal corresponding to the screened infrared light; and calculating and acquiring the pulse rate of the person to be tested according to the red light autocorrelation waveform or the infrared light autocorrelation waveform.
In an optional embodiment, the calculating module 140 is specifically configured to calculate and obtain a pulse rate of the person to be tested according to the red light autocorrelation waveform or a first periodic waveform in the infrared light autocorrelation waveform.
The above-mentioned apparatus is used for executing the method provided by the foregoing embodiment, and the implementation principle and technical effect are similar, which are not described herein again.
These above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when one of the above modules is implemented in the form of a Processing element scheduler code, the Processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
Fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 9, the electronic device may include: a processor 210, a storage medium 220, and a bus 230, wherein the storage medium 220 stores machine-readable instructions executable by the processor 210, and when the electronic device is operated, the processor 210 communicates with the storage medium 220 via the bus 230, and the processor 210 executes the machine-readable instructions to perform the steps of the above-mentioned method embodiments. The specific implementation and technical effects are similar, and are not described herein again.
Optionally, the present application further provides a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the computer program performs the steps of the above method embodiments. The specific implementation and technical effects are similar, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A method for calculating blood oxygen saturation, comprising:
acquiring an initial photoplethysmography signal of a person to be tested within a preset time period, wherein the initial photoplethysmography signal comprises: an initial photoplethysmography signal corresponding to the red light and an initial photoplethysmography signal corresponding to the infrared light;
adjusting the curve gravity center of the initial photoplethysmography signal to coincide with the origin of coordinates, and acquiring a preprocessed initial photoplethysmography signal;
according to the sampling index value, baseline drift removal is carried out on the preprocessed initial photoplethysmographic signal, and the processed photoplethysmographic signal is obtained;
and calculating and obtaining the blood oxygen saturation of the person to be tested according to the processed photoplethysmogram signal.
2. The method according to claim 1, wherein the performing baseline wandering on the preprocessed initial photoplethysmographic signal according to the sampling index value to obtain a processed photoplethysmographic signal comprises:
acquiring the average slope of the initial photoplethysmographic signal after the preprocessing according to a plurality of sampling index values;
and performing baseline-removing drift operation on the preprocessed initial photoplethysmographic signal according to the average slope to obtain the processed photoplethysmographic signal.
3. The method according to claim 2, wherein said obtaining an average slope of said preprocessed initial photoplethysmographic signal according to said plurality of sampling index values comprises:
using a formula
Obtaining the preprocessed initial photoelectric volume pulseAverage slope of the beat wave signal, where t represents the sample index value, y'tDenotes the average slope, ytAnd the initial photoplethysmographic signal after preprocessing is shown, wherein if the total number of samples N is an even number, x is equal to N/2, and if the total number of samples N is an odd number, x is equal to (N-1)/2.
4. The method according to claim 1, wherein said calculating and obtaining the blood oxygen saturation of the person to be tested according to the processed photoplethysmographic signals comprises:
calculating a correlation coefficient between the photoplethysmography signals corresponding to the red light and the infrared light according to the processed photoplethysmography signals;
screening the processed photoplethysmography signals according to the correlation coefficient and a preset threshold value to obtain screened photoplethysmography signals;
and calculating and obtaining the blood oxygen saturation of the person to be tested according to the screened photoplethysmogram signals.
5. The method according to claim 4, wherein said calculating and obtaining the blood oxygen saturation of the person to be tested according to the screened photoplethysmographic signals comprises:
calculating and obtaining a relative change measurement value of the absorbance of the red light and the infrared light according to the screened photoplethysmographic signals;
and calculating and obtaining the blood oxygen saturation of the person to be tested according to the relative change measurement value of the red light and the infrared light absorbance and a preset calculation formula.
6. The method of claim 4, further comprising:
according to the screened photoplethysmography signals, calculating and obtaining autocorrelation coefficients of the photoplethysmography signals corresponding to the screened red light, or autocorrelation coefficients of the photoplethysmography signals corresponding to the screened infrared light;
generating a red light autocorrelation waveform or an infrared light autocorrelation waveform according to the autocorrelation coefficient of the photoplethysmographic signal corresponding to the screened red light or the autocorrelation coefficient of the photoplethysmographic signal corresponding to the screened infrared light;
and calculating and obtaining the pulse rate of the person to be tested according to the red light autocorrelation waveform or the infrared light autocorrelation waveform.
7. The method of claim 6, wherein said calculating the pulse rate of the subject according to the red light autocorrelation waveform or the infrared light autocorrelation waveform comprises:
and calculating and obtaining the pulse rate of the person to be tested according to the red light autocorrelation waveform or the first period waveform in the infrared light autocorrelation waveform.
8. A device for measuring blood oxygen saturation, comprising:
the acquisition module is used for acquiring and acquiring an initial photoplethysmogram signal of a person to be tested in a preset time period, wherein the initial photoplethysmogram signal comprises: an initial photoplethysmography signal corresponding to the red light and an initial photoplethysmography signal corresponding to the infrared light;
the adjusting module is used for adjusting the curve gravity center of the initial photoplethysmographic signal to coincide with the origin of coordinates, and acquiring the preprocessed initial photoplethysmographic signal;
the processing module is used for carrying out baseline wandering on the preprocessed initial photoplethysmography signals according to the sampling index value to obtain the processed photoplethysmography signals;
and the calculation module is used for calculating and acquiring the blood oxygen saturation of the person to be tested according to the processed photoplethysmogram signals.
9. An electronic device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the electronic device is running, the processor executing the machine-readable instructions to perform the steps of the method for calculating blood oxygen saturation according to any one of claims 1 to 7.
10. A storage medium having stored thereon a computer program for performing the steps of the method of calculating blood oxygen saturation according to any one of claims 1 to 7 when executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110139634.5A CN112932475B (en) | 2021-02-01 | 2021-02-01 | Method and device for calculating blood oxygen saturation, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110139634.5A CN112932475B (en) | 2021-02-01 | 2021-02-01 | Method and device for calculating blood oxygen saturation, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112932475A true CN112932475A (en) | 2021-06-11 |
| CN112932475B CN112932475B (en) | 2023-02-21 |
Family
ID=76241218
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110139634.5A Active CN112932475B (en) | 2021-02-01 | 2021-02-01 | Method and device for calculating blood oxygen saturation, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112932475B (en) |
Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0395555A1 (en) * | 1989-03-07 | 1990-10-31 | Eerl Sarl | Signal analysis method, in particular for digestive manometry |
| US5792069A (en) * | 1996-12-24 | 1998-08-11 | Aspect Medical Systems, Inc. | Method and system for the extraction of cardiac artifacts from EEG signals |
| JP2000139863A (en) * | 1998-11-05 | 2000-05-23 | Nec Corp | F wave starting point and finishing point detector and method for detecting starting point and finishing point |
| CN1334709A (en) * | 1998-12-22 | 2002-02-06 | 内文塔医药公司 | Device for reducing signal noise in fetal ECG signal |
| US20050025382A1 (en) * | 2003-08-01 | 2005-02-03 | Munenori Oizumi | Image filter method |
| CN102216749A (en) * | 2008-11-19 | 2011-10-12 | 法国欧陆汽车公司 | Method for correcting the drift of a pressure sensor signal |
| CN103027690A (en) * | 2012-11-28 | 2013-04-10 | 华中科技大学 | Hypoperfusion oxyhemoglobin saturation measuring method based on self-correlation modeling method |
| CN103364644A (en) * | 2013-07-25 | 2013-10-23 | 北京无线电计量测试研究所 | Method for eliminating baseline drift of probe output voltage signal |
| US20140073865A1 (en) * | 2012-09-11 | 2014-03-13 | Nellcor Puritan Bennett Llc | Methods and systems for qualifying calculated values based on a statistical metric |
| CN103961089A (en) * | 2014-05-27 | 2014-08-06 | 山东师范大学 | Sinus heart rate turbulence tendency detecting method based on segmented straight line fitting |
| CN104622444A (en) * | 2015-01-30 | 2015-05-20 | 中国科学院电子学研究所 | Wrist monitoring system with multiple photoelectric sensor modules |
| CN105637360A (en) * | 2013-10-17 | 2016-06-01 | 株式会社岛津制作所 | Method and device for detecting peak endpoints in waveform |
| CN107137059A (en) * | 2016-03-01 | 2017-09-08 | 上海佑壳尔科技有限公司 | With noisy non-real time physiological data signal-data processing method |
| CN109381179A (en) * | 2018-10-16 | 2019-02-26 | 中山大学 | A kind of diagnosis and therapy system of obstructive sleep apnea syndrome |
| CN109561842A (en) * | 2016-08-09 | 2019-04-02 | 皇家飞利浦有限公司 | Equipment for oxygen saturation measurement |
| CN109700450A (en) * | 2018-12-28 | 2019-05-03 | 联想(北京)有限公司 | A kind of heart rate detection method and electronic equipment |
| CN110477889A (en) * | 2018-10-08 | 2019-11-22 | 合云力健康科技(北京)有限公司 | The method and apparatus for identifying radial artery wave shape reflection point |
| CN110638441A (en) * | 2019-08-29 | 2020-01-03 | 上海询康数字科技有限公司 | Electrocardiogram noise reduction method and device, computer equipment and storage medium |
| CN112244804A (en) * | 2020-11-06 | 2021-01-22 | 深圳市爱都科技有限公司 | Physiological monitoring device and electronic equipment |
-
2021
- 2021-02-01 CN CN202110139634.5A patent/CN112932475B/en active Active
Patent Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0395555A1 (en) * | 1989-03-07 | 1990-10-31 | Eerl Sarl | Signal analysis method, in particular for digestive manometry |
| US5792069A (en) * | 1996-12-24 | 1998-08-11 | Aspect Medical Systems, Inc. | Method and system for the extraction of cardiac artifacts from EEG signals |
| JP2000139863A (en) * | 1998-11-05 | 2000-05-23 | Nec Corp | F wave starting point and finishing point detector and method for detecting starting point and finishing point |
| CN1334709A (en) * | 1998-12-22 | 2002-02-06 | 内文塔医药公司 | Device for reducing signal noise in fetal ECG signal |
| US20050025382A1 (en) * | 2003-08-01 | 2005-02-03 | Munenori Oizumi | Image filter method |
| CN102216749A (en) * | 2008-11-19 | 2011-10-12 | 法国欧陆汽车公司 | Method for correcting the drift of a pressure sensor signal |
| US20140073865A1 (en) * | 2012-09-11 | 2014-03-13 | Nellcor Puritan Bennett Llc | Methods and systems for qualifying calculated values based on a statistical metric |
| CN103027690A (en) * | 2012-11-28 | 2013-04-10 | 华中科技大学 | Hypoperfusion oxyhemoglobin saturation measuring method based on self-correlation modeling method |
| CN103364644A (en) * | 2013-07-25 | 2013-10-23 | 北京无线电计量测试研究所 | Method for eliminating baseline drift of probe output voltage signal |
| CN105637360A (en) * | 2013-10-17 | 2016-06-01 | 株式会社岛津制作所 | Method and device for detecting peak endpoints in waveform |
| CN103961089A (en) * | 2014-05-27 | 2014-08-06 | 山东师范大学 | Sinus heart rate turbulence tendency detecting method based on segmented straight line fitting |
| CN104622444A (en) * | 2015-01-30 | 2015-05-20 | 中国科学院电子学研究所 | Wrist monitoring system with multiple photoelectric sensor modules |
| CN107137059A (en) * | 2016-03-01 | 2017-09-08 | 上海佑壳尔科技有限公司 | With noisy non-real time physiological data signal-data processing method |
| CN109561842A (en) * | 2016-08-09 | 2019-04-02 | 皇家飞利浦有限公司 | Equipment for oxygen saturation measurement |
| CN110477889A (en) * | 2018-10-08 | 2019-11-22 | 合云力健康科技(北京)有限公司 | The method and apparatus for identifying radial artery wave shape reflection point |
| CN109381179A (en) * | 2018-10-16 | 2019-02-26 | 中山大学 | A kind of diagnosis and therapy system of obstructive sleep apnea syndrome |
| CN109700450A (en) * | 2018-12-28 | 2019-05-03 | 联想(北京)有限公司 | A kind of heart rate detection method and electronic equipment |
| CN110638441A (en) * | 2019-08-29 | 2020-01-03 | 上海询康数字科技有限公司 | Electrocardiogram noise reduction method and device, computer equipment and storage medium |
| CN112244804A (en) * | 2020-11-06 | 2021-01-22 | 深圳市爱都科技有限公司 | Physiological monitoring device and electronic equipment |
Non-Patent Citations (8)
| Title |
|---|
| MD. ASADUR RAHMAN，等: "Baseline wandering removal from ECG signal by wandering path finding algorithm", 《 2017 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL INFORMATION AND COMMUNICATION TECHNOLOGY (EICT)》 * |
| MD. ASADUR RAHMAN，等: "Baseline wandering removal from ECG signal by wandering path finding algorithm", 《 2017 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL INFORMATION AND COMMUNICATION TECHNOLOGY (EICT)》, 1 February 2018 (2018-02-01), pages 1 - 5 * |
| XIAO TAN, 等: "Real-Time Baseline Wander Removal in ECG Signal", 《2013 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (ICIA)》 * |
| XIAO TAN, 等: "Real-Time Baseline Wander Removal in ECG Signal", 《2013 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (ICIA)》, 27 January 2014 (2014-01-27), pages 453 - 456 * |
| 闫宏伟: "基于DSP的无袖带连续血压测量***研究", 《中国优秀硕士学位论文全文数据库》 * |
| 闫宏伟: "基于DSP的无袖带连续血压测量***研究", 《中国优秀硕士学位论文全文数据库》, 15 February 2010 (2010-02-15), pages 56 * |
| 黄富贵，等: "评定直线度误差的最小二乘法与最小包容区域法精度之比较", 《光学 精密工程》 * |
| 黄富贵，等: "评定直线度误差的最小二乘法与最小包容区域法精度之比较", 《光学 精密工程》, vol. 15, no. 6, 30 June 2007 (2007-06-30), pages 890 - 893 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112932475B (en) | 2023-02-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20210030372A1 (en) | Methods to estimate the blood pressure and the arterial stiffness based on photoplethysmographic (ppg) signals | |
| Schäfer et al. | How accurate is pulse rate variability as an estimate of heart rate variability?: A review on studies comparing photoplethysmographic technology with an electrocardiogram | |
| Lemay et al. | Application of optical heart rate monitoring | |
| CN107920786B (en) | Pulse oximetry | |
| US20060224073A1 (en) | Integrated physiological signal assessing device | |
| WO2011013132A1 (en) | Photoplethysmography device and method | |
| Yang et al. | Estimation and validation of arterial blood pressure using photoplethysmogram morphology features in conjunction with pulse arrival time in large open databases | |
| JPH0549624A (en) | Method and device for monitoring saturation degree of blood oxygen | |
| JP2011521702A (en) | Method and apparatus for CO2 evaluation | |
| Fontaine et al. | Reflectance-based pulse oximeter for the chest and wrist | |
| Manurung et al. | Non-invasive blood glucose monitoring using near-infrared spectroscopy based on Internet of Things using machine learning | |
| US20220412883A1 (en) | Method and Apparatus for Non-Invasively Measuring Blood Circulatory Hemoglobin | |
| Scardulla et al. | Photoplethysmograhic sensors, potential and limitations: Is it time for regulation? A comprehensive review | |
| Wong et al. | Applied machine learning for blood pressure estimation using a small, real-world electrocardiogram and photoplethysmogram dataset | |
| Aarthi et al. | Fingertip based estimation of heart rate using photoplethysmography | |
| Lemay et al. | Applications of optical cardiovascular monitoring | |
| Lee et al. | A Non-Invasive Blood Glucose Estimation System using Dual-channel PPGs and Pulse-Arrival Velocity | |
| CN112932475B (en) | Method and device for calculating blood oxygen saturation, electronic equipment and storage medium | |
| Sannino et al. | Non-invasive estimation of blood pressure through genetic programming-preliminary results | |
| Jamal et al. | Portable health monitoring kit using photolethysmogram signal | |
| RU2805810C1 (en) | Wearable device with function of determining hemoglobin concentration, method and system for determining hemoglobin concentration | |
| Huang et al. | Pulse rate guided oxygen saturation monitoring using a wearable armband sensor | |
| Naguszewski et al. | Determination of oxygen saturation based on distorted photoplethysmography signals by scaling method | |
| Haroon et al. | Design and development of non-invasive prototype to measure pulse rate, blood glucose and oxygen saturation level in arterial blood | |
| Uguz | Design of a multipurpose photoplethysmography sensor to assist cardiovascular and respiratory diagnosis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |