| In today’s medical condition, due to the incomplete of patients’continuous health information, doctors often get patients’ past medical history by patients’complains. However, the time when patients go to see a doctor is always after their illness begins, which make it impossible for doctors to understand the cause of major chronic diseases and patients’ personal situation. All these conditions have led to the drop of diagnostic accuracy; Long before the major chronic non-communicable disease appears, it’s hard for patients to adopt pointed measures because organs are just in a stage of functional change and with no obvious physical change; At the same time, it’s difficult to arrange physical examination project according to personal health and genetic condition; When doing indoor and outdoor activities, people with chronic diseases, especially old people, are vulnerable to fall injury. In case a sudden illness or fall happened to them, it will be very dangerous if there’s no effective medical help from their families or doctors.The daily monitoring and health management become particularly important because of the shortcomings of current medical treatment and chronic diseases’ special features, which means long-term monitoring, scientific management and reasonable intervention. We can collect users’physiological parameter, such as ECG, heart rate and SpO2in real time, then upload it to health manage center by using a portable health monitor. In this way, the doctors will be able to estimate the users’ health condition in time according to the physiological information uploaded. As a result, we will realize the chronically ill health promotion, prevention of the complications and improve patients’living quality. Furthermore, the government will be able to reduce health care cost, distribute medical resources reasonably and achieve the shift of chronic diseases’control mode from treatment to prevention.As the main diagnosis basis of the treatment and prevention of cardiovascular disease, ECG has very important reference significance for heart function and pathological research. When there is abnormal state of the activity of the heart, it will follow a faster or slower ECG signal cycle, or even lead to a distortion of ECG waveform; Timely detection of oxygen content in the arteries is very necessary, which is a very important index to judge whether the human respiratory system and circulatory system is normal or the surrounding environment is short of oxygen. Blood oxygen saturation is used to determine the blood oxygen levels clinically in general; The elderly or people with chronic illnesses are always with poor self-care ability and self-protection ability, so it is common for them to fall because of tripping, sprain, or their own disease, such as cardiovascular and cerebrovascular diseases, which may lead to serious consequences without timely help. In conclusion, ECG, SpO2and fall detection are necessary parameters of family daily care and monitoring for chronic diseases.The object of this paper is to design a family used miniature and portable multi-parameter mobile health device which is portable, safe, low consumption and intelligent. The system realizes the collection, processing, displaying and storage of ECG, heart rate and oxygen saturation. Particularly, the monitor designed is able to exchange data with Android or iOS smart device through Bluetooth and sends out alarm signal if abnormal physiological parameter or fall is detected. The Android or iOS smart device are also capable of uploading users’physiological parameters to community health service website through network such as2G/3G/4G or WiFi, which makes it possible for doctors to make detailed patients’health documents according to the information uploaded.The hardware design of the miniature multi-parameter mobile health device should follow the following principles:(1) Use safety, test results are accurate and reliable;(2) Convenient operation, small volume and comprehensive functions;(3) Low power consumption;(4) Networking functions. According to these principles, this paper uses the STM32F103series MCU designed by ST as the core of the control unit, and three-axis acceleration sensor MMA72560is used in fall detection module. An integrated hardware design project is proposed for the monitoring of ECG and SpO2. The project realizes the collection of physiological signals using an integrated analog front end for heart rate monitors and pulse oximeters named AFE4400and an integrated analog front end for ECG named ADS1298respectively, both of whom are launched by TI.The mobile health motoring device uses a polymer lithium ion rechargeable battery and its capacity is800mAh. The voltage regulator circuit exports+3.3V and+3.0V voltage respectively for the digital circuit and analog circuit power supply. The MCU processes the pulse signal, ECG signal and body acceleration signal acquired by the blood oxygen signal acquisition module, ECG signal acquisition module and three-axis acceleration sensor respectively with specific analysis algorithm, then we will get the user’s heart rate, SpO2, pulse wave, ECG wave and body gesture. These parameters will be updated and displayed on the LCD screen. The users can also choose to send their physiological parameters to smart phone through Bluetooth module in real time, in this way, will the display, saving, alarming and up-transmission of motoring data be convenient and intelligent.ECG and pulse wave signal are low frequency signals with frequency band range of0.05-100Hz and0-20Hz respectively, and99%of the acceleration signal energy of human activities is concentrated below15Hz. According to the Nyquist sampling theorem, we set the sampling period of ECG signal to4ms, while the sampling period of photoelectric pulse wave signal and human body acceleration signal is12ms. The system adopts time-sharing scheduling mechanism to realize data acquisition and processing. The monitor designed communicates with smart device through Bluetooth module by means of serial communication and the data transmitted includes module’s self-checking information, response of control command, set up information, system running state, monitoring waveform data and physiological parameters.ECG signal, photoelectric pulse wave signal and the acceleration of human body are very vulnerable to internal and external factors, such as power frequency interference, baseline drift and electronic equipment noise. In this condition, it will cause signal distortion and large error of measuring results, which can seriously affect the normal use of mobile health monitoring device. Only be analyzed and processed furthermore, can we get correct and stable ECG wave, heart rate, pulse wave, SpO2and human gesture information from the signals acquired by hardware circuits. This paper designs FIR filter with the FDAtool provided by MATLAB. To improve its operating efficiency on STM32, we transfer the filter’s coefficient from float to integer when exporting the filter to be C files. At the same time, we adopt the method of sliding smoothing filter to suppress the baseline drift.This study adopts the method of dynamic difference threshold for the recognition of photoelectric volume pulse wave and ECG waveform feature points and experiments show that the algorithm designed can recognize the peaks and troughs of pulse wave and the R wave of ECG correctly. To improve the stability of the result computed, this paper extracts the DC and AC component of pulse wave through spectral analysis and it is better than the feature points recognition algorithm based on time domain. We can carry out FFT on STM32easily by using the DSP library supplied by ST. R value can be computed after the DC and AC component are extracted correctly, then we could use the vital signs simulator Prosim-8from FLUKE to calibrate the SpO2module designed in a range of70%-100%. It is found that the quadratic fitting results may reflect the variation tendency between R value and SpO2clearly, so we generally use the quadratic fitting results to compute SpO2in practical application.The acceleration signal of human body will have a great change compared to activities of daily life when a fall occurred, we can analysis this change with motoring device to detect the fall and call for help.The ECG monitoring module of the mobile health monitor designed has several gain selection and its measuring range of heart rate or pulse rate is30-220bpm. We collect the three lead ECG signal and pulse wave signal of8adults aged22-28at rest state using the mobile health monitor designed, then compare the results with a commercial portable multi-parameter monitor. It turned out that the measuring precision of heart rate or pulse rate is±3bpm, while the SpO2is±2%in the range of90%-99%, both of which is in permeable error limits. Furthermore, the veracity of the fall detection alarm module is more than90%while detecting the three typical falling actions.Practice shows that the multi-parameter mobile health monitoring device designed is of high measuring precision, good man-machine interface and easy to carry. Its wireless connection with smart phone apparently embodies the rise of telemedicine and remote health care service, which provides a reference for the development of domestic intelligent medical or mobile health and has very high use value and development prospects. |
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