The Design Of The Portable Multi-parameter Intelligent Medical System

In order to solve the lack of medical resources and meet people’s daily health monitoring, this paper presents a household portable multi-parameter intelligent medical equipment with complete function, safety and low-power. The diagnostic data including the blood pressure, ECG, heart rate and oxygen saturation can be collected, analyzed, displayed and stored by using it, even can be transferred to Android or iOS smart phone through the WIFI.By comparing the advantages and disadvantages of the existing signal acquisition and processing methods for the blood pressure, blood oxygen, ECG,the circuit design and data processing of the system are introduced in detail in this paper.(1) Circuit design. MP3V5050 is selected as the pressure sensor for blood pressure acquisition. Compared with the traditional scheme, the optical coupler is adopted in the control circuits for inflator pump and air release valve, and it can reduce the interference from mechanical devices. And compared with the design that using separation device, AFE4400 and ADS1293 are selected as sensors for oxygen saturation and ECG acquisition in order to increase the system reliability and reduce the power dissipation.(2) Data processing. Blood pressure is calculated by using gauss curve fitting combined with variable amplitude coefficient method. Difference method is put forward for the baseline processing, which can reduce the difficulty of realization and keep the oscillation characteristic of blood pressure pulse waveform. Blood-oxygen saturation is measured based on the frequency domain analysis method, which can ensure the measuring precision and overcome the disadvantages that the amplitude method is not accurate and the hardware implementation of Gauss function method is difficult. The real-time threshold update method was used to detect the R wave of ECG Compared with the matched filtering method and wavelet transform, the method is simple, and easy to implement on the MCU platform. And it can accurately detect the R wave point.The results indicate that the measurement accuracy of the designed system meets the standard requirements and can be connected with smart phone for transferring data. It is suitable for the development of Internet medical. The successful design and implementation of this system provides a reference for the development of intelligence and mobile health, and will be of high commercial value in the future.