Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides a noninvasive blood glucose detection method, which specifically comprises the following steps:
and a synchronous monitoring step: collecting a PPG signal and an ECG signal which are synchronously monitored;
the pulse wave transmission time obtaining step: according to the rising point of the PPG signal and the peak value of the ECG signal, pulse wave transmission time is obtained;
and a signal processing step: processing the PPG signal and the ECG signal, removing noise, and obtaining the processed PPG signal and ECG signal;
and a feature extraction step: segmentation processing is carried out according to the processed PPG signal and ECG signal, and signal characteristics are extracted, so that PPG signal characteristics and ECG signal characteristics are obtained;
a step of obtaining blood glucose data: taking pulse wave transmission time, PPG signal characteristics and ECG signal characteristics as blood glucose data to be measured;
and (3) comparing and identifying: comparing the blood glucose data to be detected with the blood glucose data in the database, and identifying the corresponding blood glucose concentration;
the database includes a plurality of sets of blood glucose data having a natural temporal order, the set of blood glucose data including pulse wave transit times, PPG signal characteristics, ECG signal characteristics, and corresponding blood glucose concentrations.
A noninvasive blood glucose testing system, comprising in particular the following units:
synchronization monitoring unit: collecting a PPG signal and an ECG signal which are synchronously monitored;
acquiring a pulse wave transmission time unit: according to the rising point of the PPG signal and the peak value of the ECG signal, pulse wave transmission time is obtained;
a signal processing unit: processing the PPG signal and the ECG signal, removing noise, and obtaining the processed PPG signal and ECG signal;
feature extraction unit: segmentation processing is carried out according to the processed PPG signal and ECG signal, and signal characteristics are extracted, so that PPG signal characteristics and ECG signal characteristics are obtained;
obtaining a blood glucose data unit: taking pulse wave transmission time, PPG signal characteristics and ECG signal characteristics as blood glucose data to be measured;
and a comparison and identification unit: comparing the blood glucose data to be detected with the blood glucose data in the database, and identifying the corresponding blood glucose concentration;
the database includes a plurality of sets of blood glucose data having a natural temporal order, the set of blood glucose data including pulse wave transit times, PPG signal characteristics, ECG signal characteristics, and corresponding blood glucose concentrations.
According to the invention, accurate measurement of blood sugar is realized by taking pulse wave transmission time, PPG signal characteristics and ECG signal characteristics as core parameters, and if a database is accurate enough, the influence of external factors such as skin color, stratum corneum, blood vessel wall thickness and the like can be completely eliminated. Meanwhile, the invention also realizes the update of the database by calculating the first-order or multi-order derivative of the difference, so that the database is more accurate.
The above as well as additional features, aspects, and advantages of the present application will become more readily apparent with reference to the following detailed description.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without creative efforts, based on the described embodiments of the present invention fall within the protection scope of the present invention.
Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs. The terms "first," "second," and the like in the description and in the claims, are not used for any order, quantity, or importance, but are used for distinguishing between different elements. Likewise, the terms "a" or "an" and the like do not denote a limitation of quantity, but rather denote the presence of at least one.
A method for noninvasive blood glucose detection comprising the steps of:
and a synchronous monitoring step: collecting a PPG signal and an ECG signal which are synchronously monitored;
the pulse wave transmission time obtaining step: according to the rising point of the PPG signal and the peak value of the ECG signal, pulse wave transmission time is obtained;
and a signal processing step: processing the PPG signal and the ECG signal, removing noise, and obtaining the processed PPG signal and ECG signal;
the noise removal may be performed by methods commonly known in the art.
And a feature extraction step: segmentation processing is carried out according to the processed PPG signal and ECG signal, and signal characteristics are extracted, so that PPG signal characteristics and ECG signal characteristics are obtained;
the feature extraction step includes:
carrying out feature extraction on the PPG signal and the ECG signal of each single period from two aspects of time domain and frequency domain by adopting a Gaussian fitting algorithm to obtain signal features,
the signal characteristics include: the maximum amplitude of the signal, the rate of rise of a single epoch from start to peak, the rate of fall of a single epoch from peak to end, the average amplitude value of a single cycle, the standard deviation of the amplitude, the average slope from start to peak, the average slope from peak to descending isthmus, the average slope from descending isthmus to diastolic peak, or the average slope from diastolic peak to end.
Gaussian Fitting (Gaussian Fitting) uses shapes such as:
Gi(x)＝Ai*exp((x-Bi)^2/Ci^2)
a gaussian function of (c) a fitting method for performing a function approximation to a set of data points. The method can be analogized with polynomial fitting, and is different from polynomial fitting in that the polynomial fitting is performed by a power function system and a Gaussian function, and has the advantage of being simple and quick in integral calculation.
The realization scheme of the mathnet wakeup matrix operation in the c# is as follows:
double[,]a＝new double[fitDatas.Count,3]；
double[]b＝new double[fitDatas.Count]；
double[]X＝new double[3]{0,0,0}；
for(int i＝0；i<fitDatas.Count；i++)
{
b[i]＝Math.Log(fitDatas[i].Intensity)；
a[i,0]＝1；
a[i,1]＝fitDatas[i].WaveLength；
a[i,2]＝a[i,1]*a[i,1]；
}
//Matrix.Equation(datas.Count,3,a,b,X)；
MathNet.Numerics.LinearAlgebra.Matrix matrixA＝new MathNet.Numerics.LinearAlgebra.Matrix(a)；
MathNet.Numerics.LinearAlgebra.Matrix matrixB＝new MathNet.Numerics.LinearAlgebra.Matrix(b,b.Length)；
MathNet.Numerics.LinearAlgebra.Matrix matrixC＝matrixA.Solve(matrixB)；
X＝matrixC.GetColumnVector(0)；
double S＝-1/X[2]；
double xMax＝X[1]*S/2.0；
double yMax＝Math.Exp(X[0]+xMax*xMax/S)；
a step of obtaining blood glucose data: taking pulse wave transmission time, PPG signal characteristics and ECG signal characteristics as blood glucose data to be measured;
and (3) comparing and identifying: comparing the blood glucose data to be detected with the blood glucose data in the database, and identifying the corresponding blood glucose concentration;
the comparison step specifically comprises the following steps:
if the blood glucose data to be measured is the first group of blood glucose data in natural time, comparing the blood glucose data to be measured with the blood glucose data in the database one by one according to the sequence, and calculating the difference between the blood glucose data to be measured and the blood glucose data in the database, wherein the blood glucose data with the smallest difference in the database is used as the matching data;
if the blood glucose data to be measured is not the first group of blood glucose data in natural time, calculating the difference between the blood glucose data to be measured and the blood glucose data in the database; according to the preset difference threshold, a plurality of groups of blood sugar data are found in the database, and according to the natural time of the plurality of groups of blood sugar data, the blood sugar data which is closer to the natural time of the last matching data is selected as the matching data of the blood sugar data to be detected;
the blood glucose concentration in the data is matched as the detected blood glucose concentration.
The database includes a plurality of sets of blood glucose data having a natural temporal sequence, one set of blood glucose data including pulse wave transit time, PPG signal characteristics, ECG signal characteristics, and corresponding blood glucose concentrations.
The difference is calculated by the following formula:
T＝ΔA×α1 +ΔB×α2 +ΔC×α3
wherein T is the difference;
Δa is the pulse wave transit time difference;
Δb is the sum of absolute differences between PPG signal features;
ΔC is the sum of absolute differences between the ECG signal characteristics;
α1, α2, and α3 are weight coefficients. The weighting factor generally gives a greater weight to the pulse wave transit time difference, for example, a factor of 0.8.
The noninvasive blood glucose detection method further comprises a database updating step:
according to the multiple groups of blood glucose data to be tested and the matched blood glucose data obtained in the comparison step, multiple groups of differential values arranged according to natural time are obtained through calculation, first-order or multi-order derivatives of the differential values are calculated, if the first-order or multi-order derivatives are higher than a certain threshold value, the multiple groups of blood glucose data to be tested are placed in a database, and natural time is given to the multiple groups of blood glucose data to be tested according to the sequence.
The invention also relates to a noninvasive blood glucose detection system, which specifically comprises the following units:
synchronization monitoring unit: collecting a PPG signal and an ECG signal which are synchronously monitored;
acquiring a pulse wave transmission time unit: according to the rising point of the PPG signal and the peak value of the ECG signal, pulse wave transmission time is obtained;
a signal processing unit: processing the PPG signal and the ECG signal, removing noise, and obtaining the processed PPG signal and ECG signal;
feature extraction unit: segmentation processing is carried out according to the processed PPG signal and ECG signal, and signal characteristics are extracted, so that PPG signal characteristics and ECG signal characteristics are obtained;
obtaining a blood glucose data unit: taking pulse wave transmission time, PPG signal characteristics and ECG signal characteristics as blood glucose data to be measured;
and a comparison and identification unit: comparing the blood glucose data to be detected with the blood glucose data in the database, and identifying the corresponding blood glucose concentration;
the database includes a plurality of sets of blood glucose data having a natural temporal sequence, one set of blood glucose data including pulse wave transit time, PPG signal characteristics, ECG signal characteristics, and corresponding blood glucose concentrations.
The comparison unit specifically comprises:
if the blood glucose data to be measured is the first group of blood glucose data in natural time, comparing the blood glucose data to be measured with the blood glucose data in the database one by one according to the sequence, and calculating the difference between the blood glucose data to be measured and the blood glucose data in the database, wherein the blood glucose data with the smallest difference in the database is used as the matching data;
if the blood glucose data to be measured is not the first group of blood glucose data in natural time, calculating the difference between the blood glucose data to be measured and the blood glucose data in the database; according to the preset difference threshold, a plurality of groups of blood sugar data are found in the database, and according to the natural time of the plurality of groups of blood sugar data, the blood sugar data which is closer to the natural time of the last matching data is selected as the matching data of the blood sugar data to be detected;
the blood glucose concentration in the data is matched as the detected blood glucose concentration.
The feature extraction unit includes:
and carrying out feature extraction on the PPG signal and the ECG signal of each single period from two aspects of a time domain and a frequency domain by adopting a Gaussian fitting algorithm to obtain signal features, wherein the signal features comprise: the maximum amplitude of the signal, the rate of rise of a single epoch from start to peak, the rate of fall of a single epoch from peak to end, the average amplitude value of a single cycle, the standard deviation of the amplitude, the average slope from start to peak, the average slope from peak to descending isthmus, the average slope from descending isthmus to diastolic peak, or the average slope from diastolic peak to end.
The non-invasive blood glucose test system further comprises a database updating unit:
according to the blood sugar data to be tested and the matched blood sugar data obtained in the comparison unit, a plurality of groups of differential values arranged according to natural time are obtained through calculation, first-order or multi-order derivatives of the differential values are calculated, if the first-order or multi-order derivatives are higher than a certain threshold value, the plurality of groups of blood sugar data to be tested are placed in a database, and natural time is given to the blood sugar data to be tested according to the sequence.
According to the invention, accurate measurement of blood sugar is realized by taking pulse wave transmission time, PPG signal characteristics and ECG signal characteristics as core parameters, and if a database is accurate enough, the influence of external factors such as skin color, stratum corneum, blood vessel wall thickness and the like can be completely eliminated. Meanwhile, the invention also realizes the update of the database by calculating the first-order or multi-order derivative of the difference, so that the database is more accurate.
While the fundamental and principal features of the invention and advantages of the invention have been shown and described, it will be apparent to those skilled in the art that the invention is not limited to the details of the foregoing exemplary embodiments, but may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and the description is provided for clarity only, and those skilled in the art will recognize that the embodiments of the disclosure may be combined appropriately to form other embodiments that will be understood by those skilled in the art.