Wherein ε is the absorptivity, C is the concentration of light-absorbing substance, I₀And I is the incident light and the detected light intensity, respectively; mu.s_aIs the absorption coefficient, i.e. the probability that a photon is absorbed per unit path.

Obtaining a general photon diffusion equation at the position r of the tissue or the turbid medium and at the time t according to a diffusion transmission theory as follows:

where (r, t) is the optical density at the point (r, t) and is the absorption coefficient, S (r, t) is the amount of light source, c is the speed (constant) at which photons travel, D is the diffusion coefficient, which is a basic characteristic parameter that reflects the diffusion characteristics of biological tissue macroscopically, in m or cm, and for photon migration, the diffusion coefficient is equal to the following formula:

wherein mu_sIs the scattering coefficient, g is the average value of the cosine of the scattering angle, called the scattering anisotropy factor; (1-g) mu_sThe term is referred to as the effective scattering coefficient or equivalent isotropic scattering coefficient. The formula is a general diffusion equation for heat and mass transfer, derived from the radiation transfer equation describing the movement of uncharged particles, and is therefore suitable for the propagation of light in strongly scattering media.

According to the photon diffusion equation and the time-resolved spectroscopy technology, a photon flow distribution formula after one light pulse excitation is given by Patterson et al according to actual boundary conditions, and mainly comprises a transmission formula and a reflection formula, wherein the light intensity formula of the reflection formula is as follows:

in the formula, z₀Equal to [ (1-g) mu_s]^-1(ii) a ρ is the distance between the light source and the detector in the coordinate.

Solving ln for the formula of R (rho, t) and deriving t to obtain the following formula

When the elapsed time is long enough, the left side of the above equation will be close to- μ_ac, namely:

therefore, the derivative can obtain the proportional relation between the change rate of the reflected light intensity and the absorption coefficient, namely:

W＝-μ_ac

w represents the rate of change of the light intensity.

How to determine the absorption coefficient μ is analyzed below_aAnd the concentration C of the light absorbing substance (mainly the concentration of oxygen and hemoglobin and deoxyhemoglobin) to obtain a measurement of the two-wavelength hemoglobin oxygen saturation.

Studies have shown that in the near infrared region, the absorption by water, cytochromes, etc. is much smaller compared to deoxyhemoglobin and oxygen and hemoglobin. Therefore, when two light beams having wavelengths in the near infrared region are selected to probe tissue, only the influence of deoxyhemoglobin and oxygen and hemoglobin are considered, the absorption coefficients at the two wavelengths can be formulated as follows,

combining the two formulas, the following formula is obtained according to the double-beam method

Selecting a wavelength gamma₂For equal absorption points, the formula of blood oxygen saturation can be obtained

In the formula_Hb^γ1,ε_Hb^γ2,

All are constants and can be obtained by adopting a time domain or frequency domain spectral analysis method. Then SpO₂The formula of (a) can be rewritten as:

in the formula A_s，B_sThe empirical constants can be obtained by experimental scaling.

When light passes through tissues and blood vessels, it is divided into non-pulsating components (such as skin, muscle, bone, venous blood, etc.) and pulsating components (such as arterial blood), which are called direct current and alternating current. Thus, the rate of change in tissue of light intensity can be expressed as: w is ═ I_AC/I_DCThus, the blood oxygen saturation formula can be rewritten as:

the above equation is an empirical equation of a linear relationship for measuring blood oxygen saturation, and in practical applications, considering factors such as individual differences of light emitting diodes as light sources and large differences of human physiological tissues, most commercial pulse oximeters use an empirical calculation equation, that is, an empirical equation obtained by statistical analysis of experiments, and an empirical equation that generates a quadratic function relationship by correlation analysis between a variation in light intensity at two wavelengths and blood oxygen saturation can be expressed as:

in the formula, A_s、B_s、C_sThe empirical constants can be obtained by experimental scaling.

Holding breath for three to five times, making the blood oxygen value reach below 90% each time, removing abnormal data from the obtained data, averaging, obtaining the accurate blood oxygen saturation and characteristic value corresponding value through wireless transmission (such as Bluetooth), and re-calibrating the 90-100% blood oxygen saturation data by using the obtained data. The method comprises the following specific steps

And performing Kalman filtering, high-pass filtering and low-pass filtering on the red light and infrared light data to obtain relatively clean data, and acquiring a PPG data peak by using a threshold method. The thresholding threshold update formula is as follows.

In the formula, N is the number of buffered wave crests, peak_iThe height of the buffered peak is denoted as a, which is an empirical coefficient, and is obtained by observing data.

Because of filtering processing, the position of the wave crest of the waveform has certain deviation, the exact position of the wave crest is determined after secondary searching is carried out near the wave crest of the original data, the position of a trough is obtained through the minimum value between two wave crests, and the wave crest and trough data are respectively interpolated by using cubic spline interpolation to obtain the upper envelope and the lower envelope of the original data, wherein the cubic spline interpolation meets the following conditions (the boundary conditions can be defined by self, and the boundary conditions defined by the invention are 0):

interpolation conditions are as follows: s (x)_j)＝y_j,j＝0,1,…,n

Continuity conditions:

first derivative continuous condition:

second derivative continuous condition:

the difference value between the upper envelope and the lower envelope is the data alternating current quantity, the average value of the upper envelope and the lower envelope is the data direct current quantity, the blood oxygen characteristic value is obtained, and the characteristic value formula is as follows

In the formula, Ir_ACFor the quantity of infrared light traffic, Ir_ACFor direct current of infrared light, Rd_ACFor red light traffic, Rd_DCIs the red light direct current quantity.

According to actual data tests, the characteristic value between 94% -99% and 90% -93% of the blood oxygen saturation has an obvious mutation, so that the data are divided into two groups by using a piecewise fitting method to carry out least square polynomial curve fitting to obtain a quadratic polynomial fitting curve, wherein the curve formula is as follows:

SpO₂＝A·R²+B·R+C

in the formula, A, B and C are constant coefficients obtained by data fitting.

This application makes user's blood oxygen drop to below 90 through holding out breath, marks this section of data through transmission-type oxyhemoglobin saturation appearance, uses the algorithm to refit oxyhemoglobin saturation 90 ~ 99's curve, has improved and has directly markd the error that reflection formula oxyhemoglobin algorithm caused through transmission-type oxyhemoglobin simulator, compares clinical blood oxygen and marks also labour saving and time saving more.

The personal data is used for calibration, so that the calculation error of the blood oxygen saturation caused by factors such as individual difference of light emitting diodes of the light source, larger difference of human physiological tissues and the like is reduced, the private customization of each algorithm is realized, and the accuracy of the measurement of the blood oxygen saturation is improved.

In the above embodiments, the specific working process of the reflective oximeter has been illustrated, and the above components can be implemented by using the existing hardware product to implement the corresponding functions, but the improvement of the present invention does not lie in the improvement of the signal processing process in the reflective oximeter, but utilizes the components and their connection relationship to implement the functions of the present invention.

The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only represent some embodiments of the present invention, and the description thereof is specific and detailed, but not to be construed as limiting the scope of the present invention. It should be noted that, for those skilled in the art, without departing from the spirit of the present invention, several variations and modifications can be made, which are within the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. A reflection type oximeter is characterized by comprising an optical reflection probe assembly and a pulse blood oxygen detection module;

the microprocessor controls the light-emitting assembly to emit detection light, and a detection signal is obtained through the optical signal receiving assembly, wherein the detection signal is a signal generated by reflecting the detection light by a tissue part of an object to be detected and converting the detection light;

and the microprocessor receives the blood oxygen saturation detection data of the object to be detected of the transmission oximeter through the signal transmission device.

2. The reflective oximeter of claim 1, wherein the light assembly comprises more than two light tubes, wherein different light tubes emit light of different wavelengths during operation.

3. The reflective oximeter of claim 2, wherein the light assembly comprises a red LED tube and an infrared LED tube.

4. The reflective oximeter of claim 2, wherein the pulse oximetry module further comprises a light intensity modulation circuit;

5. The reflective oximeter of claim 1, wherein the optical signal receiving assembly comprises a photodiode and a transimpedance amplifier connected to each other, the transimpedance amplifier being further connected to the microprocessor;

the photodiode is used for receiving an optical signal and converting the optical signal into an electric signal, wherein the optical signal is generated by reflecting the detection light by the tissue part of the object to be detected; the transimpedance amplifier is used for amplifying the electrical signal.

6. The reflective oximeter of claim 5, wherein the pulse oximetry module further comprises a signal amplifier, a filter and an analog-to-digital converter connected in sequence;

7. The reflective oximeter of any one of claims 1-5, wherein the signal transmission means comprises a wireless transmission means for receiving the oximetry data of the transmissive oximeter via a wireless signal.

8. The reflective oximeter of claim 7, wherein the pulse oximetry module further comprises a low dropout voltage regulator connected between the microprocessor and a power supply.

9. The reflective oximeter of claim 7, wherein the pulse oximetry module further comprises a display screen connected to the microprocessor for displaying blood oxygen data.

10. The reflective oximeter of claim 7, wherein the pulse oximetry module further comprises a memory coupled to the microprocessor for storing blood oxygenation data.