Design of intelligent electronic blood pressure meter based on programmable system on chip

In view of the shortcomings of previous electronic blood pressure monitors, this paper introduces the design of an intelligent electronic blood pressure monitor based on a programmable system on chip (SOPC). The blood pressure measurement method adopts the oscillometric method based on the inflation process. The system uses the Cyclone II series low-cost FPGA and embeds the NNIOS II soft core as the core processor. It can complete the functions of automatic blood pressure measurement, information display, data storage, viewing and deleting historical data. The use of FPGA simplifies the circuit design, improves the reliability and stability of the system, and makes the system have strong scalability, which is conducive to the upgrade of the system.

Blood pressure is an important physiological parameter that reflects the state of the cardiovascular system. Appropriate blood pressure is a necessary condition for maintaining normal human metabolism. With the continuous improvement of people's living standards and the increase in the degree of urban aging, people's awareness of self-care has gradually increased. Electronic blood pressure monitors have the advantages of low cost, miniaturization, and high degree of automation. Now they have become a necessary health care product for families and are very popular. SOPC (System on Programmable Chip) is a flexible and efficient SOC solution proposed by Altera. Putting the entire system on a silicon chip using programmable logic technology is called SOPC. It can perfectly combine MCU, DSP and FPGA, and has very good development prospects.

1 Principle of human blood pressure measurement

1.1 Blood pressure measurement

There are many methods for measuring blood pressure. The most commonly used non-invasive blood pressure measurement methods are Korotkoff sound method and oscillometric method. The design of this paper adopts the oscillometric method based on inflation. The inflation measurement based on the oscillometric method is just the reverse process of the deflation measurement. As shown in Figure 1, during the pressure increase (inflation) process, the static pressure and the oscillation wave of the gas in the cuff are detected. The oscillation wave originates from the pulsation of the blood vessel wall. When the pressure is low, before the static pressure of the cuff is less than the diastolic pressure Pd, the arterial wall has been fully expanded during the diastolic period, and the rigidity of the wall has increased, so the amplitude is maintained at a small level. With the increase of pressure, when the cuff pressure is higher than the systolic pressure Ps, the artery is compressed and closed. At this time, due to the impact of the proximal pulse, a small oscillation wave appears; when the static pressure of the cuff is equal to the mean pressure, the amplitude reaches the maximum value; the static pressure of the cuff corresponding to the envelope of the oscillation wave indirectly reflects the arterial blood pressure.

1.2 Heart rate calculation

Heart rate refers to the number of times the heart beats per minute. Since the heart beats at the same time as the pulse, the heart rate can be measured at the same time as the blood pressure. The key to measuring heart rate is to determine the peak value of the pulse wave, and then calculate the heart rate based on how many pulse waves are measured within a certain period of time.

2 Hardware Design of SOPC System

The hardware design block diagram of the SOPC system is shown in Figure 2.

2.1 SOPC system circuit

This circuit consists of FPGA chip, memory and other peripheral components, and is the core part of signal processing. The embedded microprocessor system including CPU, memory interface and I/O peripherals is built by SOPC Builder hardware development environment. After completing the system design, SOPC Builder can be used to generate the system. The figure below shows the system content configuration built in SOPC Builder.

The EPCS device controller core is added to the SOPC system to make full use of system resources, fix the FPGA configuration data and Nios II software program into the EPCS chip, and save more space for the Flash chip to store measurement results. At this time, the reset address of the Nios II processor should be set to the base address of the EPCS controller. When the system is reset, the program fixed into the EPCS chip will be automatically downloaded to SDRAM for execution.

Figure 4 is a top-level module diagram of the SOPC system generated by the SOPC Builder hardware development environment.

2.2 Pressure measurement circuit

2.2.1 Pressure sensor selection

The pressure sensor selected for this design is the MPXV5050GP pressure sensor produced by Motorola. It contains a signal amplifier, has a signal conditioning function, has good linearity, and can directly convert the pressure of arterial blood on the blood vessel wall into an electrical signal of 0.2-4.7V. The corresponding blood pressure value is 0-375mmHg, which is very consistent with the design requirements of the sphygmomanometer.

2.2.2 Design of driving circuit

The signal to control the operation of the air pump and the solenoid valve is sent by the FPGA. The air pump requires a working drive current of 450mA and the solenoid valve requires 75mA, but the digital I/O output current of the FPGA cannot meet the requirements. Therefore, in order to provide the air pump and the solenoid valve with a suitable drive current, the Darlington tube array ULN2803 drive circuit is used to drive the air pump and the solenoid valve. The ULN2803 can output a current of 500mA. The first and second channels of the ULN2803 are used to drive the solenoid valve and the air pump respectively, and the third channel drives an LED to indicate the pulse wave signal. As shown in Figure 5.

2.3 Extraction of sensor output signal

The signal from the pressure sensor is a mixed signal of the pulse wave oscillation signal and the static pressure signal, and is also mixed with high-frequency interference, DC or low-frequency components from the outside world. We divide the mixed signal into two parts. One part is A/D converted after passing through a low-pass filter to extract the cuff pressure signal, and the other part is sent to the A/D conversion module after passing through a band-pass filter and an amplifying circuit to obtain the amplified pulse wave data. The specific circuit of the signal extraction part is shown in Figure 6.

Here, a second-order low-pass Butterworth filter with a cutoff frequency of 0.48Hz is used, and the gain of the low-pass filter is set to 1, which can minimize the amplification of errors. An active filter with signal amplification capability is used to extract the pulse wave signal, and the passband frequency range is designed to be 0.48~4.8Hz. After the pulse wave signal is amplified and filtered, its maximum amplitude should be as close to the upper limit allowed by the A/D conversion module as possible, which helps to improve the accuracy of the collected data.

Since the static pressure signal and pulse wave signal need to be A/D converted separately, two sampling channels are required. The systolic pressure of the human brachial artery blood pressure is generally in the range of 95-140 mmHg, with an average value of 110-120 mmHg, and the diastolic pressure is 60-90 mmHg, with an average value of 80 mmHg. Considering the conditions of hypertension and other diseases, the measurement range of the sphygmomanometer should be within 0-250 mmHg, so the requirement for the A/D converter is at least 8 bits (28=256).

2.4 Keyboard circuit and display circuit

This system uses 1 button as the system reset switch and 5 buttons as the system operation keyboard to complete the functions of measuring blood pressure, viewing records, flipping up records, flipping down records and deleting records. The display part uses a 128×64 dot matrix LCD display, which is easy to operate and has a friendly interface. System software flow design

The software workflow diagram of this system is shown in Figure 7. The signal processing algorithm part mainly processes the sampled pulse signal, including using digital filtering algorithm to identify and remove various interference noise signals, improve the envelope of the pulse wave, etc., so as to improve the anti-interference ability and measurement accuracy of the electronic sphygmomanometer when measuring blood pressure.

When the user measures blood pressure, press the "measure" button, and the SOPC system sends a control signal to the air pump to start pressurizing and inflating. During the inflation process, the blood pressure signal from the pressure sensor is amplified and filtered and then sent to the A/D conversion module. After the signal is converted by A/D, it is sent to the SOPC system to execute the corresponding signal processing algorithm to calculate the heart rate, systolic pressure and diastolic pressure. After SOPC calculates the measurement value, it saves the test result to the Flash chip (write Flash). If the measurement result is normal, the LCD displays the measured data and performs a fast deflation operation; if the measured result exceeds the normal range, the corresponding prompt information is displayed, and an alarm sound and deflation control signal are issued at the same time. If an error occurs during the measurement process, the system will stop inflation and start the solenoid valve for deflation. The buzzer will also sound an alarm and display a prompt message of measurement error.

The user can press the corresponding button to complete the functions of "view" (read the Flash chip), "delete" (erase the contents of the current storage area in the Flash chip), etc. If the user wants to exit the current operation or an error occurs during the measurement process, simply press the reset button and the system will return to the initialization state and wait for new operation information.

4 Comparison and analysis of measurement results

In order to verify the measurement results of this design, we used this electronic blood pressure monitor and the Omron HEM-7012 electronic blood pressure monitor with good market evaluation to measure different individuals. The results are shown in Table 1:

From the comparison of multiple groups of measurement results, it can be seen that although there are certain errors in the measurement results, this sphygmomanometer has good individual adaptability to different measurers. Compared with the Omron electronic sphygmomanometer, the blood pressure results measured by this sphygmomanometer are slightly larger. This is because the electronic sphygmomanometer uses an oscillometric method based on the inflation process. The determination of characteristic points can only rely on the statistical induction of the collected samples, which has a certain degree of discreteness. In addition, during the measurement process, the output signal of the pressure sensor and the output signals of the amplification, filtering and other circuits may have some small differences from the true value, so there will be certain errors.

5 Conclusion

The electronic sphygmomanometer design proposed in this paper adopts the method based on inflation measurement. It has the advantages of simple and convenient operation, friendly interface, high measurement accuracy, strong individual adaptability, etc. Moreover, since it adopts the inflation process measurement, the deflation speed is very fast, thus shortening the measurement time and improving the measurement comfort of the user.