Research And Implementation Of The Measurement Technology For Vital Signs Parameters Based On Smart Terminal

The vital signs of the human body includes the heart rate, respiration, blood pressure, the blood oxygen saturation and the body temperature, and they are very closely related to the health of human body. Cardiovascular disease is one of the common chronic disease in middle-aged and old people and it has a close relationship with vital signs index. Recently years, an aging population has become a worldwide problem, more and more the elderly health is under threat from cardiovascular disease. As health consciousness to improve, many people want to find the abnormal state of health as early as possible, so they start to choose the medical equipment like sleeve type and wrist strap type to measure the vital signs, and before the onset of monitor the abnormal state of health helps to take measures to reduce the cost of treatment. There are some problems on this kind of measurement equipment at present, such as expensive, difficult to use, etc. In the other hand, the significance of measurement is reduced due to the lack of professional doctors to interpret the measurement data. According to the current situation, this paper studies the measurement method of the human vital signs by the smart phone terminal. This method not only can measure the vital signs, but also can send the measured value to the remote and get the analysis from the server. The contribution of this paper is shown as below.1. In order to ensure that equipment measured value calculation is based on the effective signal. This paper mainly analyzes the signal mechanism, and puts forward adaptive algorithm for the ROI selection. In the other hand, this paper designed a kalman filter to reduce the jitter of the system noise and introduced the modified mealy finite state machine to detect the signal quality.2. This paper puts forward an adaptive algorithm of difference quotient and threshold value based on the characteristics of the falling edge curve steep to construct a new signal of color change speed. The method improved the detection accuracy of the signal peaks and valleys, so it is helpful to improve the measurement accuracy, and an adaptive algorithm is given for the calculation of the threshold.3. We designed a detection algorithm based on maximum likelihood estimation to detect the singular signal due to finger involuntary sliding and this method have solved the problem of singular signal detection from the angle of statistical, and this step is prepared for the next analysis of the system.4. Empirical mode decomposition algorithm is introduced to the original signal into multiple single band modal component, and combining with the frequency range of the human body respiration to choose some of the low frequency component refactoring respiratory signals, and Raise the proportion of breathing component in the signal.This paper realize the measurement applications based on the Android and Apple smart phone platform. We set up a control experiment using the mobile phone with the standard medical measuring equipment to do the comparison and analysis. Measurement results on mobile phone, heart rate and breathing and inosculation of measurement value of standard equipment is very good, the blood pressure of low pressure in the type of measurement results is also better, and this verify the feasibility of this measuring method and accuracy from the Angle of the experiment. Finally from the perspective of heart rate variability introduced 3 d discrete scatterplot qualitative analysis of cardiac autonomic regulation ability, and this way of the fusion method based on the health status of vital signs index analysis provides a new train of thought.