CN110840434A - Low-power consumption bluetooth electrocardio monitoring system based on discrete component and microprocessor - Google Patents

Abstract

The invention discloses a low-power-consumption Bluetooth electrocardiogram monitoring system based on discrete components and a microprocessor. The invention is realized by adopting discrete components and a microprocessor, and realizes low power consumption, low cost and high-precision processing of electrocardiosignals through high-precision circuit design; a power supply circuit with high efficiency and low ripple is designed to supply power to the system, so that the interference of a power supply part on the electrocardiosignal is further reduced; a trap circuit is designed, and the 50Hz power frequency interference is specially removed; performing signal processing on the interference noise remained in the analog circuit by adopting a digital filter algorithm; the QRS electrocardio-wave complex is accurately locked in real time by adopting an improved dynamic difference threshold algorithm, so that the QRS electrocardio-wave complex has better adaptability.

Description

Low-power consumption bluetooth electrocardio monitoring system based on discrete component and microprocessor

Technical Field

The invention relates to a low-power-consumption Bluetooth electrocardio monitoring system based on discrete components and a microprocessor.

Background

Electrocardiosignals (ECG) are important criteria for reflecting the health condition of the heart. The electrocardiogram is an important means for diagnosing and analyzing cardiovascular diseases, and is widely applied to clinical treatment centers. However, the conventional electrocardiograph generally needs to acquire data through an electrocardiograph in a large medical place, such as a hospital or a nursing home, and the further application of the electrocardiograph is hindered due to the defects of difficult acquisition way, high price, long time consumption and the like. Clinical medicine shows that patients with cardiovascular diseases can show abnormal electrocardiograms in early stage, and most of the cardiovascular patients are critically ill or die because the patients are not cured in time. Therefore, the portable monitoring system for monitoring the electrocardiosignals of the patient has important significance for relieving the resource tension medical industry and reducing the sudden death probability of cardiovascular diseases.

At present, the Android mobile phone occupies most of the share of the Chinese mobile phone market, so that the development speed and the portability of mobile application are greatly improved. Since 2011, various kinds of mobile medical APPs have emerged like bamboo shoots in the spring after rain, and about 30% of Android users have installed such APPs. Once the physiological signal acquisition front end and the wireless transmission network system are mature, the contradiction between Chinese doctors and patients can be relieved, the increasingly tense medical resource shortage trend of the domestic medical industry is relieved, the probability of cardiovascular disease paroxysmal death is reduced, and the development of Internet medical treatment is promoted.

Although many embedded biological information acquisition systems for mobile platforms exist at home and abroad, the electrocardiogram can be accurately obtained and displayed under the requirements of low power consumption and low cost. Therefore, a set of portable electrocardio monitoring system with low power consumption, low cost and high precision has the significance of industrial prospection.

Disclosure of Invention

The invention aims to design a set of portable electrocardio monitoring system which can accurately obtain the electrocardiogram of the human body and display the electrocardiogram of the human body in real time, and has low power consumption and low cost.

In order to accurately obtain and display an electrocardiogram in real time under the requirements of low power consumption and low cost, the electrocardiosignal processing circuit part adopts a well-selected discrete high-performance analog device, and realizes the low-power consumption, low-cost and high-precision processing of the electrocardiosignals through the design of a high-efficiency and low-ripple power supply circuit (comprising a voltage reduction circuit and a voltage stabilizing circuit) and the design of a high-precision analog signal processing circuit (comprising a pre-amplification circuit, a trap circuit, a high-low pass filter, a post-amplification circuit and a level lifting circuit); the digital processing and display circuit part adopts a microprocessor (the system takes STM32F4 as an example) as a processing core, further reduces the power consumption of the system, and is matched with a real-time operating system and an improved low-complexity signal processing algorithm, thereby accurately displaying the electrocardiogram in real time; an Android mobile phone APP capable of carrying out Bluetooth communication with a microprocessor is designed, so that electrocardiogram data processed by an analog system and a digital system are transmitted to a mobile terminal of the mobile phone to be displayed and stored synchronously in real time.

In order to achieve the technical purpose, the technical scheme of the invention is that,

a low-power consumption Bluetooth electrocardio monitoring system based on discrete components and a microprocessor comprises an electrocardio signal processing circuit, a digital processing and displaying circuit and a Bluetooth module, wherein the digital processing and displaying circuit is respectively in communication connection with the electrocardio signal processing circuit and the Bluetooth module;

the electrocardiosignal processing circuit comprises an analog signal processing circuit and a power supply circuit, the power supply circuit supplies power to the whole system, the input end of the analog signal processing circuit is connected with an electrode for collecting electrocardiosignals of a human body, and the collected electrocardiosignals are processed and then output to a digital processing and display circuit;

the analog signal processing circuit comprises a pre-amplification circuit, a trap circuit, a high-low pass filter and a post-amplification and level-lifting circuit, wherein the pre-amplification circuit, the trap circuit, the high-low pass filter and the post-amplification and level-lifting circuit are sequentially connected, and the processed electrocardiosignals are sent to a digital processing and display circuit.

The low-power-consumption Bluetooth electrocardio monitoring system based on the discrete component and the microprocessor is characterized in that the digital processing and displaying circuit comprises the microprocessor and a micro display screen, the microprocessor is in communication connection with the electrocardiosignal processing circuit and processes received electrocardiosignals, and the micro display screen is in communication connection with the microprocessor and displays an electrocardiogram formed by the processed electrocardiosignals.

The low-power consumption Bluetooth electrocardio monitoring system based on the discrete component and the microprocessor is characterized in that the power supply circuit comprises a battery, a DC-DC voltage reduction circuit, an LDO linear voltage regulator, a negative power supply and a digital LDO linear voltage regulator, wherein the battery, the DC-DC voltage reduction circuit and the LDO linear voltage regulator are sequentially connected, the LDO linear voltage regulator outputs positive voltage to the analog signal processing circuit and converts the negative voltage into negative voltage to provide a bipolar power supply for the analog signal processing circuit, and the digital LDO linear voltage regulator is connected with the LDO linear voltage regulator, reduces the voltage of the power supply and outputs the voltage to the digital processing and display circuit.

The low-power-consumption Bluetooth electrocardio monitoring system based on the discrete component and the microprocessor comprises an analog signal processing circuit and a right leg driving circuit, wherein the output end of the right leg driving circuit is connected to the input end of a pre-amplification circuit.

The low-power-consumption Bluetooth electrocardio monitoring system based on the discrete component and the microprocessor is characterized in that the micro display screen is a touch display screen realized by adopting an LCD.

A bluetooth low energy electrocardio monitoring system based on discrete component and microprocessor, bluetooth module and APP on the smart machine carry out bluetooth communication and send electrocardiosignal data.

The low-power-consumption Bluetooth electrocardio monitoring system based on the discrete component and the microprocessor is characterized in that a digital processing and display circuit draws an electrocardiogram, calculates and displays a heart rate value through a QRS electrocardio wave group locking algorithm based on a dynamic differential threshold algorithm, and the QRS electrocardio wave group locking algorithm comprises the following steps:

firstly, extracting an inflection point serving as a characteristic point on an electrocardiogram waveform curve, namely calculating a slope value K (n) of the electrocardiogram waveform corresponding to an nth sampling point:

wherein the initial step value Δ n is 1, and x (n) is a height value of the electrocardiographic waveform corresponding to the nth sampling point; n is the nth sample point on the electrocardiographic waveform. The actual electrocardiographic waveform is continuous, with the horizontal axis of the waveform representing time t. To store in a computer, the electrocardiographic waveform must be discretized through processes such as sampling, and the horizontal axis of the waveform becomes n, namely the nth sampling point.

And (3) compensating errors caused by noise by adopting step length accumulation, wherein the conditions of judging a maximum value and a minimum value, namely an inflection point are as follows:

[x(n)＞x(n-2)]∩[x(n)＞x(n-1)]∩[x(n)＞x(n+1)]∩[x(n)＞x(n+2)]

[x(n)＜x(n-2)]∩[x(n)＜x(n-1)]∩[x(n)＜x(n+1)]∩[x(n)＜x(n+2)]

then there are:

by calculating a slope value, taking a point of which the slope value changes from positive to negative or from negative to positive as the position of each inflection point of the electrocardiosignal, extracting the time period of occurrence of the QRS wave in the electrocardio waveform by a threshold method, and determining an R point in the QRS wave, namely a peak point, by combining the inflection points:

the point at which the QRS wave occurs satisfies the following equation:

wherein

For the threshold, it is calculated as follows:

wherein K_maxIs the maximum slope value, K_maxA new threshold value calculated according to the new electrocardiographic waveform;

judging QRS waves according to the calculated threshold, and when the threshold is larger than 0, if 4 continuous groups of slope data are larger than the threshold, judging that a QR section in the QRS waves is a rising section; when the threshold is less than 0, if the slope data of 4 continuous groups are less than the threshold, judging that the RS section in the QRS wave is a descending section, and finding out an inflection point after locking the QRS wave, wherein the inflection point is an R point;

after the R wave is determined, after 2s, recalculating the threshold value, and judging to lock a new R wave;

and finally, calculating the human heart rate value by calculating the time between the R waves and displaying.

The system has the following advantages: the whole set of electrocardio monitoring system is realized by adopting discrete components and a microprocessor, and low-power consumption, low-cost and high-precision processing of electrocardiosignals is realized through high-precision circuit design; a power supply circuit with high efficiency and low ripple is designed to supply power to the system, so that the interference of a power supply part on the electrocardiosignal is further reduced; a trap circuit is designed, and the 50Hz power frequency interference is specially removed; performing signal processing on the interference noise remained in the analog circuit by adopting a digital filter algorithm; an improved dynamic difference threshold algorithm is adopted, and the QRS electrocardio wave group is accurately locked in real time, so that the QRS electrocardio wave group has better adaptability; a matched Android mobile phone APP is developed, and processed electrocardio data can be received through Bluetooth and displayed and stored in real time and synchronously.

Drawings

FIG. 1 is a block diagram of the system of the present invention;

FIG. 2 is a diagram of a system hardware architecture;

FIG. 3 is a diagram of a power system architecture;

FIG. 4 is a schematic diagram of an active dual T trap circuit;

FIG. 5 is a diagram of an example of an ECG signal processing circuit PCB;

FIG. 6 is a diagram of a system software architecture;

FIG. 7 is a diagram of an EMWIN based graphical user interface;

FIG. 8 is a flow chart of a QRS electrocardiograph complex locking algorithm;

FIG. 9 is a diagram of an APP Bluetooth pairing interface;

fig. 10 is an APP physiological data receiving and displaying interface diagram;

FIG. 11 is an APP physiological data preservation interface diagram;

fig. 12 is a diagram of an electrocardiographic waveform, in which the central peak is the QRS wave.

Detailed Description

The invention is described in further detail below with reference to the figures and examples.

The invention designs a low-power consumption Bluetooth electrocardiogram monitoring system based on discrete components and a microprocessor, and a system block diagram of the system is shown in figure 1.

The hardware structure of the system is shown in figure 2, electrocardiosignals are collected from 3 electrodes respectively attached to the left arm, the right arm and the right leg of a human body, the 3 electrodes are respectively connected with an analog signal processing circuit, and the function of the system is to collect the electrocardiosignals of the human body and input the electrocardiosignals into the circuit. The whole system adopts 7.4V lithium battery power supply, obtains 5.4V voltage through DC-DC step-down topology, contains more ripples in the power this moment, needs to obtain stable 5V voltage through LDO linear voltage regulator. The bipolar power supply required by the integrated operational amplifier is obtained through the negative power supply, and the digital part supplies power to the microprocessor through the 3.3V linear voltage stabilizer. The combined modulation mode of the DC-DC and the LDO forms a high-efficiency and low-ripple power supply system, and the structure diagram is shown in fig. 3.

The invention designs a preposed differential amplifying circuit by selecting a precise low-power consumption instrument amplifier according to a formula

G＝1+49.4/R

The required signal gain is calculated. Because the preamplification is not suitable to be too large, otherwise the electrocardiosignal saturation distortion is easily caused, the gain is generally controlled to be between 10 and 30, the amplification factor selected by the system is 11 times, the common mode rejection ratio is about 100dB, and 80dB of the common medical requirement can be achieved.

The main purpose of the right leg driving circuit is to reduce signal interference and suppress common mode signals, especially electrocardio signals. The human body can be used as a power frequency interference receiving source, the effect similar to that of an antenna is realized, the patient is in a mains supply system for a long time, and electrocardiosignals are easy to couple with 50Hz interference signals. At this time, the right leg driving circuit can ensure the integrity of the signal.

The frequency distribution of the electrocardiosignals is between 0.05Hz and 100 Hz. Because common mode interference in the circuit is serious, particularly, the mains supply at the body and 50Hz power frequency noise can be mixed into electrocardiosignals, and the electrocardiosignals need to be filtered. Therefore, the output signal of the preamplification circuit is connected into the double-T wave trap to specially remove power frequency interference, so that the electrocardiosignal is smoother. The circuit schematic of this section is shown in fig. 4. Assuming that R1, R2, C1, C2, R3, C3, and R4 are R, the transfer function of the dual T trap is derived as follows

The standard transfer function of the wave trap is

It can be known that

Wherein sigma is used for adjusting the slide rheostat, adjusting the Q value and changing the bandwidth. The value of RC is determined according to the notch frequency of 50 Hz. Here, C is 0.1 μ F, and R is 45.016K Ω. The specific resistor is combined according to the actual resistance value to reach the required resistance value.

Because the frequency of the electrocardiosignal is 0.05-100 Hz, a reasonable filter needs to be designed in the bandwidth. The output signal of the wave trap is connected to a band-pass filter consisting of a high-pass filter with low cut-off frequency (0.05Hz) and a low-pass filter with high cut-off frequency (100Hz) to obtain a precise pass band. The transfer function of the low-pass filter is

The high-pass filter has a transfer function of

The following is a subsequent stage amplification and level raising circuit. Because the preposed amplifying circuit amplifies the electrocardiosignals by 11 times, the electrocardiosignals need to be further amplified to reach the degree that a digital system can collect the electrocardiosignals, namely the total amplifying time can reach 2000 times to carry out A/D conversion. Therefore, the electrocardiographic signal needs to be amplified by about 200 times, and finally, the signal is amplified by 100dB and output. Because the analog part adopts the bipolar integrated operational amplifier, the electrical level of the electrocardiosignal needs to be raised to enable the microprocessor to collect the electrocardiosignal in consideration of the positive and negative electrical level characteristics of the electrocardiosignal (the collection voltage range of the microprocessor is 0-3.3V).

An example of the ecg signal processing circuit PCB is shown in fig. 5.

The system software structure diagram is shown in fig. 6. We have scheduled two tasks on the real-time operating system μ C/OS III. The first is an oscilloscope task EMWINDemo _ task designed based on an EMWIN graphical user interface, which comprises an infinite-length unit impulse response digital filter (IIR) algorithm and a QRS electrocardio complex locking algorithm based on an improved dynamic differential threshold algorithm, and the task has the functions of drawing an electrocardiogram, calculating and displaying a heart rate value; the second is a Bluetooth data transmission task Bluetooth _ task, which has the function of transmitting the electrocardio and heart rate data obtained by calculation to an Android mobile phone APP for displaying and storing at the mobile terminal in real time through the task. An EMWIN based graphical user interface diagram is shown in FIG. 7.

The system adopts a mode of combining the slope and the threshold value to judge the condition of each wave band in the electrocardiosignal. First, a feature point on the heart rate waveform, i.e. an inflection point on the curve, needs to be extracted. Mathematically, it is the point at which maxima and minima occur that is calculated. This inflection point can be found by calculating the form of the differential, i.e. calculating the slope value. Mathematically defining the slope as

The initial step value Δ n is 1, x (n) is the height value of the electrocardiographic waveform corresponding to the nth sampling point; n is the nth sample point on the electrocardiographic waveform. However, because the electrocardiosignal can generate noise interference, the error caused by the noise is compensated by adopting step length accumulation, wherein the maximum value and the minimum value, namely the inflection point, are judged in the case of

[x(n)＞x(n-2)]∩[x(n)＞x(n-1)]∩[x(n)＞x(n+1)]∩[x(n)＞x(n+2)]

[x(n)＜x(n-2)]∩[x(n)＜x(n-1)]∩[x(n)＜x(n+1)]∩[x(n)＜x(n+2)]

From the above two equations, the slope can be calculated

By calculating the slope value, and taking the point where the slope value changes from positive to negative or from negative to positive as the position of each inflection point of the electrocardiosignal, the position of each inflection point of the electrocardiosignal can be determined. Because the data of the R wave needs to be extracted, the time period of the occurrence of the R wave needs to be judged, and then the R point is determined by matching with the extreme point. Here the time at which the locking QRS wave occurs needs to be determined using a thresholding method.

The following equation must be satisfied at the point where the R wave appears

WhereinIs the threshold value to be processed, and this value can be calculated as follows

Wherein K_maxIs the value of the maximum slope that is,

is a new threshold calculated from the new electrocardiographic waveform.

From the above principles, the slope conditions in the QR and RS segments can be determined, see fig. 12, where with the QRs wave starting point as Q, the vertex as R, and the end point as S, the QRs complex is further locked by confirming a positive threshold in the QR segment and a negative threshold in the RS segment. When the threshold value is larger than 0, if the slope data of 4 continuous groups are larger than the threshold value, judging that the QR section in the QRS wave is a rising section; when the threshold is less than 0, if the slope data of 4 continuous groups are smaller than the threshold, the RS section in the QRS wave is judged to be a descending section, and after the QRS wave is locked, an inflection point is found out, namely an R point.

After the R wave is determined, after 2s, the threshold value is updated again, and the locking of the R wave is judged.

And finally, calculating the human heart rate value by calculating the time between the R waves and displaying. A flow chart of the QRS electrocardiographic complex locking algorithm is shown in fig. 8.

In order to display the processed electrocardiogram data at the mobile terminal of the mobile phone, the data needs to be sent to the client terminal of the mobile phone through bluetooth. The invention develops an Android client APP (application), namely real-time health monitoring, which realizes pairing and communication with a front-end Bluetooth module by calling a Bluetooth API (application program interface) provided by Android by utilizing classes closely related to Bluetooth, such as Bluetooth socket classes and Bluetooth adapters. The APP has the functions of receiving and displaying the electrocardio data in real time, the data can be stored in a mobile phone in a file form, and a user can open the previously stored data by using any text (. txt) reading software. The APP bluetooth pairing interface diagram, the APP physiological data receiving and displaying interface diagram, and the APP physiological data storing interface diagram are respectively shown in fig. 9, 10, and 11.

Claims (7)

1. A low-power consumption Bluetooth electrocardio monitoring system based on discrete components and a microprocessor is characterized by comprising an electrocardio signal processing circuit, a digital processing and displaying circuit and a Bluetooth module, wherein the digital processing and displaying circuit is respectively in communication connection with the electrocardio signal processing circuit and the Bluetooth module;

the electrocardiosignal processing circuit comprises an analog signal processing circuit and a power supply circuit, the power supply circuit supplies power to the whole system, the input end of the analog signal processing circuit is connected with an electrode for collecting electrocardiosignals of a human body, and the collected electrocardiosignals are processed and then output to a digital processing and display circuit;

the analog signal processing circuit comprises a pre-amplification circuit, a trap circuit, a high-low pass filter and a post-amplification and level-lifting circuit, wherein the pre-amplification circuit, the trap circuit, the high-low pass filter and the post-amplification and level-lifting circuit are sequentially connected, and the processed electrocardiosignals are sent to a digital processing and display circuit.

2. The bluetooth low energy electrocardiogram monitoring system based on discrete components and microprocessor as claimed in claim 1, wherein the digital processing and display circuit comprises a microprocessor and a micro display screen, the microprocessor is communicatively connected to the electrocardiogram signal processing circuit and processes the received electrocardiogram signal, and the micro display screen is communicatively connected to the microprocessor and displays an electrocardiogram formed by the processed electrocardiogram signal.

3. The discrete component and microprocessor based bluetooth low energy electrocardiograph monitoring system according to claim 1, wherein the power circuit comprises a battery, a DC-DC voltage reduction circuit, an LDO linear regulator, a negative power supply, and a digital LDO linear regulator, the battery, the DC-DC voltage reduction circuit, and the LDO linear regulator are connected in sequence, the LDO linear regulator outputs a positive voltage to the analog signal processing circuit and converts the negative power supply into a negative voltage to provide a bipolar power supply for the analog signal processing circuit, and the digital LDO linear regulator is connected to the LDO linear regulator and reduces the voltage of the power supply and outputs the reduced voltage to the digital processing and display circuit.

4. The discrete component and microprocessor based bluetooth low energy electrocardiographic monitoring system according to claim 1 wherein the analog signal processing circuit further comprises a right leg driver circuit, the output of the right leg driver circuit is connected to the input of the pre-amplifier circuit.

5. The system according to claim 2, wherein the micro display screen is a touch display screen implemented by an LCD.

6. The discrete component and microprocessor based bluetooth low energy electrocardiographic monitoring system according to claim 1 wherein the bluetooth module performs bluetooth communication with the APP on the smart device and sends electrocardiographic signal data.

7. The system according to claim 2, wherein the digital processing and display circuit performs a QRS ecg locking algorithm based on a dynamic differential threshold algorithm to map an electrocardiogram and calculate and display a heart rate value, the QRS ecg locking algorithm comprising the steps of:

firstly, extracting an inflection point serving as a characteristic point on an electrocardiogram waveform curve, namely calculating a slope value K (n) of the electrocardiogram waveform corresponding to an nth sampling point:

wherein the initial step value An is 1, and x (n) is the height value of the electrocardiographic waveform corresponding to the nth sampling point; n is the nth sample point on the electrocardiographic waveform;

and (3) compensating errors caused by noise by adopting step length accumulation, wherein the conditions of judging a maximum value and a minimum value, namely an inflection point are as follows:

[x(n)＞x(n-2)]∩[x(n)＞x(n-1)]∩[x(n)＞x(n+1)]∩[x(n)＞x(n+2)]

[x(n)＜x(n-2)]∩[x(n)＜x(n-1)]∩[x(n)＜x(n+1)]∩[x(n)＜x(n+2)]

then there are:

by calculating a slope value, taking a point of which the slope value changes from positive to negative or from negative to positive as the position of each inflection point of the electrocardiosignal, extracting the time period of occurrence of the QRS wave in the electrocardio waveform by a threshold method, and determining an R point in the QRS wave, namely a peak point, by combining the inflection points:

the point at which the QRS wave occurs satisfies the following equation:

wherein

For the threshold, it is calculated as follows:

wherein K_maxIs the value of the maximum slope that is,

a new threshold value calculated according to the new electrocardiographic waveform;

judging QRS waves according to the calculated threshold, and when the threshold is larger than 0, if 4 continuous groups of slope data are larger than the threshold, judging that a QR section in the QRS waves is a rising section; when the threshold is less than 0, if the slope data of 4 continuous groups are less than the threshold, judging that the RS section in the QRS wave is a descending section, and finding out an inflection point after locking the QRS wave, wherein the inflection point is an R point;

after the R wave is determined, after 2s, recalculating the threshold value according to the new electrocardiographic waveform, and judging to lock the new R wave;

and finally, calculating the human heart rate value by calculating the time between the R waves and displaying.

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