TWM574469U - QRS wave instant detection device - Google Patents

Abstract

The new QRS wave real-time detection device receives a ECG signal to be detected through a receiving unit, and captures the ECG signal through an acquisition unit through an acquisition unit, and cooperates with a processing unit to eliminate baseline drift and conversion. The high-frequency signal and low-frequency signal of all scales, then the calculation unit selects the analysis scale, calculates the positive and negative threshold values, and calculates the corresponding coordinates of the ECG signal. Finally, the recording unit judges the distance between the coordinates and the previous one. It can be recorded or deleted to effectively and accurately determine the position of the QRS wave, which not only reduces the misjudgment caused by noise, but also greatly improves the accuracy of judgment, reduces the calculation amount, and improves the analysis speed, thereby effectively reducing the consumption of human resources and more economically. benefit.

Description

QRS wave instant detection device

The present invention relates to a detection device, particularly a QRS wave instant detection device.

With the improvement of living standards and quality, the prevention and detection of major diseases have gradually been valued by modern people. At the same time, the type of disease has also changed from acute to chronic, such as cancer, heart disease, and cerebrovascular disease. With the development of science and technology, by measuring and analyzing relevant physiological signals, early signs of major diseases can be detected, so that patients can be treated early, and it can help control the disease and improve the cure rate.

It is commonly used to track, analyze, and diagnose heart disease in cardiac diseases. It uses non-invasive measurement methods and provides good information, so that medical personnel or researchers can use the electrocardiogram signal to show the overall potential of the heart. Changes to further understand the patient ’s heart condition and detect potentially dangerous patients, or to help monitor patients with heart defects in order to reduce the risk of heart attacks in patients, before judging and classifying ECG signals Medical personnel or researchers must find out the QRS wave shape in a large number of ECG signals, and then use the position, size, and shape of P, Q, R, S, and T waves as the basis for diagnosing heart disease.

However, in order to improve the accuracy of ECG signal analysis and judgment, it usually takes a considerable time to measure, so as to collect enough signals for analysis, and at the same time improve the success rate of records to the onset of the disease, so a large number of ECG signals cause analysis The interpretation operation takes a long time, and it needs to be interpreted by professional medical personnel or researchers, so the consumption of human resources is quite huge. Therefore, how to quickly and accurately determine the QRS in the ECG signal Wave, so that professional medical personnel or researchers can quickly evaluate and diagnose the patient's disease, thereby effectively reducing the consumption of human resources and improving the speed of overall analysis, is still one of the goals of those skilled in the art.

Therefore, the purpose of the present invention is to provide a QRS wave real-time detection device, which can greatly improve the accuracy of judgment, reduce the amount of calculation, and increase the speed of analysis, so as to achieve rapid assessment and diagnosis of diseases, and thereby effectively reduce the consumption of human resources.

Therefore, the new QRS wave real-time detection device includes a receiving unit, a capturing unit, a processing unit, a calculation unit, and a recording unit; wherein the processing unit includes a filter and a converter, and the recording unit includes a judgment Group and record group, the heartbeat signal to be detected is received by the receiving unit, then the acquisition unit overlaps two acquisition panes and acquires the ECG signal through the acquisition pane, and cooperates with the filter to eliminate the The baseline drift signal of the ECG signal, and the ECG signal is converted by the converter to obtain high-frequency signals and low-frequency signals of all scales, and the waveform is converted into positive and negative characteristic extreme points, and then the calculation unit selects it. Calculate the positive and negative threshold values on a scale, mark the characteristic extreme value pairs according to the positive and negative threshold values, and then calculate the coordinates of the ECG signal in the time domain. Finally, cooperate with the judgment group to further rely on the characteristic poles. The distance between value pairs is judged, and the matching characteristic extreme value pairs are transmitted to the record group for recording, which not only improves the accuracy of judgment, reduces the calculation amount, and improves the analysis. Degree in order to achieve rapid assessment and diagnosis of disease, while effectively reducing the consumption of human resources, more cost-effective.

The foregoing and other technical contents, features, and effects of the present invention will be clearly understood in the following detailed description of the preferred embodiments with reference to the drawings.

Referring to FIG. 1, a first preferred embodiment of the present invention. The QRS wave real-time detection device 3 includes a receiving unit 31 connected to an external ECG signal measuring device 4 or an ECG signal database 5, and a receiving unit connected to the receiving unit 31. An extraction unit 32 of 31, a processing unit 33 connected to the extraction unit 32, a calculation unit 34 connected to the processing unit 33, and a recording unit 35 connected to the calculation unit 34; wherein the processing unit 33 includes a The filter 331 and a converter 332 connected to the filter 331. In addition, the recording unit 35 includes a judgment group 351 and a recording group 352 connected to the judgment group 351.

Referring to FIG. 1 and FIG. 2, when performing a QRS wave detection operation, first, the receiving unit 31 receives an ECG signal S to be detected by the ECG signal measuring device 4 or the ECG signal database 5, and the ECG signal The measurement device 4 can be directly worn on the patient, so as to directly receive the patient's ECG signal S and perform subsequent analysis and processing. Then, the acquisition unit 32 uses the wavelet conversion formula as follows:

The coefficient a in the mother wavelet Ψ (tb / a) can be used to expand and contract the mother wavelet, and the coefficient b can be used to translate the mother wavelet. The acquisition unit 32 further adjusts the mother wavelet to expand and contract according to the input parameters through the coefficients a and b. Panning can obtain similar acquisition panes that can be adjusted freely, see Figure 3, and make multiple sampling points overlap between any two acquisition panes. The overlapping of different numbers of sampling points will also affect the subsequent detection accuracy. In the embodiment, an example is described in which 150 sampling points overlap between any two acquisition panes and each acquisition pane has 4096 sampling points. The acquisition unit 32 then acquires the acquisition panes through the acquisition panes. ECG signal S to be detected.

With reference to FIG. 4, the processing unit 33 then filters the captured ECG signal S through the filter 331. In this embodiment, the 200 ms median filter 331 and the 600 ms median filter 331 are used for filtering. Processing, the 200ms median filter 331 first performs preliminary filtering processing on the captured ECG signal S, thereby filtering out QRS waves and P waves, then the 600ms median filter 331 and then the 200ms median filter 331 The filtered ECG signal S is filtered to remove the T wave and obtain a baseline drift signal that does not include QRS, P and T waves, and the processing unit 33 subtracts the baseline drift signal from the ECG signal S. That is, the corrected ECG signal S is obtained, as shown in FIG. 5-2. In this embodiment, the filter 331 does not include the action of eliminating high frequency noise, so as to avoid the ECG signal S from eliminating high frequency. In the process of noise, the high frequency QRS waveform is affected to reduce the eigenvalue, and then the converter 332 performs the conversion operation of the modified ECG signal S. The mother of the bi-orthogonal spline wavelet is used. The wavelet is the following formula:

The converter 332 converts the modified ECG signal S by the above formula, and obtains the high-frequency signal D and low-frequency signal A of all scales, and the number of scales converted by the converter 332 can be adjusted according to actual needs and conditions, and In this embodiment, the converter 332 is used to obtain high-frequency signals D1, D2, D3, and D4 and low-frequency signals A1, A2, A3, and A4 through wavelet transformation, as shown in FIGS. 6 to 9. The converter 332 converts the waveforms of the high-frequency signals D1, D2, D3, and D4 into positive and negative characteristic extreme points, as shown in FIG. 10. In the embodiment, the converter 332 is The first 50 sampling points and the last 50 sampling points of the acquisition pane of these high-frequency signals D1, D2, D3, and D4 are removed, and they are not included in the detection calculation.

Continuing from the foregoing, the calculation unit 34 selects one of the scales for calculation. In this embodiment, the calculation unit 34 selects the third scale for calculation. For example, the calculation unit 34 first selects the high frequency of the third scale. The signal D3 is divided into four segments, and the positive maximum value and the negative minimum value are respectively taken in the four segment signals, and then the four maximum values are averaged to obtain the average maximum value, and the four minimum values are averaged to obtain the average value. The minimum value, then a quarter of the average maximum value, to obtain the positive threshold value, and another quarter value of the average minimum value, to obtain the negative threshold value, see Figure 11 and Figure 12, the calculation Unit 34 further marks a positive characteristic extreme point that exceeds the positive threshold value, and a negative characteristic extreme point that has the opposite polarity to the positive characteristic extreme point and exceeds the negative threshold value to form a characteristic extreme value pair. And the distance between the positive and negative characteristic extreme points does not exceed a preset value. In this embodiment, the preset value is 45 sampling points. When the distance exceeds 45 sampling points, it means that the waveform is smoother. Too high QRS wave shape Then, the calculation unit 34 sets the positive characteristic extreme point coordinates (X2, Y2), the negative characteristic extreme point coordinates (X1, Y1), and performs wavelet transformation of the ECG signal S to lead or lag the time domain. The magnitude of is brought into an estimation formula, and in this embodiment, the value is brought in according to different usage scales, which is 5 in the second scale, 10 in the third scale, 25 in the fourth scale, and the calculation The formula is as follows:

The calculation unit 34 further calculates the coordinates P (n) of the ECG signal S in the time domain by using the above-mentioned estimation formula.

Continuing the foregoing, the judging group 351 of the recording unit 35 compares the distance between the aforementioned coordinate P (n) and the calculated coordinate P (n-1) of the previous characteristic extreme value pair, due to differences in age, gender, living habits, etc. The judgment standard value of the distance will also be different due to factors, and should not be limited to this. When the distance is smaller than the first value, and the first value is 100 sampling points in this embodiment, the judgment group 351 Take the coordinates P (n) and P (n-1) with sharper waveforms, that is, the judgment group 351 sets the individual positive characteristic extreme point coordinates of the P (n) and P (n-1) coordinates (X2, Y2) and negative characteristic extreme point coordinates (X1, Y1) are brought into a judgment formula, which is as follows:

The judging group 351 further calculates the P (n) and P (n-1) by using the judging formula, and then takes the one with the larger result value (α) (that is, the R wave peak), and sets the characteristic pole with the larger result value. The value pair is transmitted to the record group 352 for recording. With reference to FIG. 13, two characteristic extreme value pairs appear at the frame. The judgment group 351 calculates through the judgment formula and takes the larger value, that is, the R wave. The wave peak is transmitted to the record group 352 for recording; when the distance is less than the second value and greater than the first value, it means that the subject's heart rate is faster, or the ECG signal S contains a steeper T wave or P It is necessary to further judge the wave. In this embodiment, the second value is 130 sampling points. Therefore, the judging group 351 adds a high-frequency signal D of another scale to assist in judging. In this embodiment, the judging group 351 The high-frequency signal D2 of the second scale is added for judgment. When the characteristic extreme value pair of the third scale also appears in the high-frequency signal D2 of the second scale and has the same position, the judgment group 351 sets the P (n ) The coordinate position is transmitted to the record group 352 for recording, that is, when the coordinates P (n-1) and P (n) both appear Among the high-frequency signals D3 and D2 of the third scale and the second scale, it means that the two coordinates P (n-1) and P (n) are both R wave peaks, so the two coordinates P (n-1 ), P (n) must be transmitted to the record group 352 record. Conversely, if the coordinates that do not appear in the third scale and the second scale high frequency signals D3 and D2 are not R wave peaks, they are not transmitted to The record group 352 records, refer to FIG. 14. The characteristic extreme pair at the beginning of the frame of the third-scale high-frequency signal D3 also appears in the second-scale high-frequency signal D2, and then the judgment group 351 transmits it to the record. Group 352 is added to the record, and referring to FIG. 15, the frame shown in FIG. 15 has characteristic extreme value pairs at the high-frequency signal D3 at the third scale, but the high-frequency signal D2 at the second scale does not have the characteristic pole. Value pair, the judgment group 351 does not transmit it to the recording group 352, that is, it does not record it; when the distance is greater than the second value, that is, greater than 130 sampling points, the judgment group 351 directly transmits it Go to the record group 352 for recording. In this way, the positions of all QRS waves can be obtained, which not only reduces interference during detection, but also effectively increases Measurement accuracy, and then quickly and accurately locate the QRS complex to do, while greatly enhance the accuracy of judgment, reducing the overall amount of calculation, and effectively enhance the speed of analysis, and help reduce the consumption of human resources, as well as cost-effective.

The new model uses 48 ECG records of the MIT-BIH arrhythmia database, a total of 109,488 QRS waves, to further test the QRS wave real-time detection device 3 proposed in this case, and uses the following formula to calculate the QRS wave real-time detection device 3 proposed in this case Sensitivity (Se), positive predictive value (+ P), and error rate (Der):

TP: Total number of correct QRS waves

FP: Total number of non-QRS waves detected

FN: The total number of QRS waves that were not detected

FP + FN: Total number of errors

See Table 1 below. The experimental results show that the QRS wave detection accuracy can reach 99.84% sensitivity and 99.91% positive predictive value, and the error rate is only 0.2471%. Therefore, the QRS wave real-time detection device 3 proposed in this case has comparable The accuracy is also of practical value.

Table 1 Numbering TP FP FN FP + FN Numbering TP FP FN FP + FN 100 2,273 0 0 0 201 1,963 6 2 8 101 1,865 0 0 0 202 2,136 0 3 3 102 2,187 0 0 0 203 2,980 13 33 46 103 2,084 0 0 0 205 2,656 0 6 6 104 2,229 1 1 2 207 1,860 1 18 19 105 2,572 27 4 31 208 2,955 2 16 18 106 2,027 0 5 5 209 3,005 0 2 2 107 2,137 0 1 1 210 2,650 4 8 12 108 1,763 10 13 twenty three 212 2,748 0 0 0 109 2,532 0 0 0 213 3,251 0 0 0 111 2,124 0 1 1 214 2,262 1 3 4 112 2,539 0 0 0 215 3,363 0 1 1 113 1,789 6 0 6 217 2,208 3 7 10 114 1,879 1 8 9 219 2,154 0 0 0 115 1,953 0 0 0 220 2,048 0 0 0 116 2,412 0 20 20 221 2,427 0 2 2 117 1,535 0 0 0 222 2,483 1 2 3 118 2,278 0 0 0 223 2,605 0 3 3 119 1,987 0 0 0 228 2,053 8 13 twenty one 121 1,863 0 1 1 230 2,256 1 0 1 122 2,476 0 0 0 231 1,571 0 0 0 123 1,518 0 0 0 232 1,780 4 0 4 124 1,619 0 0 0 233 3,079 0 2 2 200 2,601 2 5 7 234 2,753 0 0 0

Referring to FIG. 16 and FIG. 17, the second preferred embodiment of the present invention still includes the components described in the previous embodiment, and its purpose and effect are the same as those in the previous embodiment, and will not be repeated here. This embodiment is particularly that the recording unit 35 is further connected with an exclusion unit 36, and the result unit (α) of each characteristic extreme value pair is calculated by the exclusion unit 36 through the foregoing judgment formula. When the result value is less than all results One-fifth of the average value of the value, the exclusion unit 36 deletes the point from the record, thereby effectively improving the accuracy of detection.

In summary, the new QRS wave real-time detection device receives the ECG signal to be detected by the receiving unit, further adjusts the acquisition pane by the acquisition unit, and acquires the ECG signal through the acquisition pane. , Together with the filter to eliminate baseline drift, and the converter converts high-frequency signals and low-frequency signals of all scales, then the calculation unit selects the analysis scale, calculates the positive and negative thresholds, and calculates the ECG signal. Corresponds to the coordinates. Finally, the judgment group judges whether it is transmitted to the record group for recording according to the distance between the coordinate and the previous point. In this way, the QRS wave detection is completed, which not only reduces the noise and the large amplitude of P waves and T waves. At the same time, it greatly improves the accuracy of judgment, reduces the amount of calculation, and increases the speed of analysis, which effectively reduces the consumption of human resources and is more in line with economic benefits.

However, the above are only for explaining the preferred embodiments of the present invention. When the scope of the implementation of the present invention cannot be limited by this, that is, the simple equivalent changes and modifications made according to the scope of the patent application of the new application and the content of the new specification , All should still fall within the scope of this new patent.

(This creation)

3‧‧‧QRS wave real-time detection device

31‧‧‧Receiving unit

32‧‧‧Capture unit

33‧‧‧Processing unit

34‧‧‧ Computing Unit

35‧‧‧Record Unit

36‧‧‧Excluded units

331‧‧‧Filter

332‧‧‧ converter

351‧‧‧Judgment Team

352‧‧‧Record Team

4‧‧‧ ECG signal measuring device

5‧‧‧ ECG Signal Database

S‧‧‧heart signal

A1‧‧‧First-level low-frequency signal

A2‧‧‧The second low frequency signal

A3‧‧‧ Third-frequency low-frequency signal

A4‧‧‧Fourth scale low frequency signal

D1‧‧‧The first high-frequency signal

D2‧‧‧Second-scale high-frequency signal

D3‧‧‧ Third-frequency high-frequency signal

D4‧‧‧Four-scale high-frequency signal

FIG. 1 is a schematic diagram of a first preferred embodiment of the present invention. FIG. 2 is a detection flowchart of the first preferred embodiment. FIG. 3 is a schematic diagram of adjusting the capture pane. FIG. 4 is a partial flowchart of the first preferred embodiment. Figure 5-1 is the baseline ECG signal. Figure 5-2 is the ECG signal corrected for baseline drift. FIG. 6 is a schematic diagram of wavelet multiple decomposition. Fig. 7 is a wavelet first-order conversion pattern. Figure 8 shows the low-frequency signal of the ECG signal after fourth-order wavelet conversion. Figure 9 shows the high-frequency signal of the ECG signal after fourth-order wavelet conversion. Figure 10 shows the extreme points of high-frequency signals showing positive and negative characteristics. FIG. 11 is a schematic diagram of characteristic extreme value pairs. FIG. 12 is a partial flowchart of the first preferred embodiment. Figure 13 shows the sharper waveforms when two pairs of characteristic extreme pairs appear. Figure 14-15 shows the high-frequency component judgment added to the second scale. FIG. 16 is a schematic diagram of a second preferred embodiment of the present invention. FIG. 17 is a detection flowchart of the second preferred embodiment.

Claims (9)

A QRS wave real-time detection device includes: a receiving unit, which is connected to an external ECG signal database or an ECG signal measurement device, so as to receive an ECG signal to be detected; an acquisition unit, and The receiving unit is connected, and the capturing unit can adjust the position of the capturing pane through a wavelet transformation formula, so that there are several sampling points overlapping between any two capturing panes, and the heart is captured through the capturing panes. Electrical signal; a processing unit connected to the acquisition unit, and the processing unit includes a filter for filtering the captured ECG signal, and a filter connected to the filter for ECG signal filtering A conversion converter; wherein, the filter filters the captured ECG signal and obtains a baseline drift signal, and then subtracts the baseline drift signal from the ECG signal to obtain a modified ECG signal, and the converter The modified ECG signal is converted into high-frequency signals and low-frequency signals of all scales, and the waveforms in the ECG signal are converted into positive and negative characteristic extreme points; a calculation unit, which The processing unit is connected, and the calculation unit may use one of the aforementioned scales to perform calculations to obtain a positive threshold value and a negative threshold value, and based on the positive threshold value and the negative threshold value, mark those that exceed the positive threshold value. Positive characteristic extreme points and negative characteristic extreme points that exceed the negative threshold, and the distance between the positive and negative characteristic extreme points must be less than a preset value to form a characteristic extreme value pair, and calculate the heart The coordinates corresponding to the time signal in the telecommunication signal; and a recording unit, which includes a judgment group and a recording group connected to the judgment group; wherein the judgment group compares the distances between the coordinates calculated by the two characteristic extreme values When the distance is less than the first value, the judgment group calculates the coordinates separately and transmits the larger value to the record group for recording; when the distance is less than the second value and greater than the first value, the judgment group Add a high-frequency signal of another scale for judgment. If the characteristic extreme value pair also appears in the high-frequency signal of the other scale and has the same position, then transmit the characteristic extreme value pair to the record group for recording; Conversely, when the distance is greater than the second value, the judgment group transmits the characteristic extreme value pair to the record group for recording. According to the QRS wave real-time detection device described in item 1 of the scope of the patent application, wherein the two acquisition panes overlap 150 sampling points. According to the QRS wave real-time detection device described in item 1 of the patent application scope, wherein the filter is a median filter. According to the QRS wave real-time detection device described in item 1 of the patent application scope, wherein the converter converts the ECG signal into high-frequency signals and low-frequency signals of four scales, and the converted high-frequency signals are respectively front and rear. Remove 50 sampling points. According to the QRS wave real-time detection device described in item 1 of the scope of the patent application, wherein the calculation unit selects a third-scale high-frequency signal for analysis and calculation. According to the QRS wave real-time detection device described in item 1 of the scope of patent application, the first value is 100 sampling points, and the second value is 130 sampling points. According to the QRS wave real-time detection device described in item 1 of the scope of patent application, the preset value is 45 sampling points. According to the QRS wave real-time detection device described in item 1 or item 6 of the scope of patent application, wherein the judging group adds a high-frequency signal of the second scale for judgment. According to the QRS wave real-time detection device described in item 1 of the scope of the patent application, wherein the recording unit is further connected with an exclusion unit, the exclusion unit calculates the result value of each characteristic extreme value pair, and further excludes the inaccuracies based on the result value. Consistent characteristic extreme pairs.