Maternal And Child Care System Based On Internet Of The Design And Implementation

With the one-child policy carrying out, more and more importance is attached topregnant women and fetuses. The antepartum fetal monitor is showed to be a timelymanner to update the growth and development of embryos, avoiding damage fromhypoxia to improve the quality of fetus and reduce perinatal mortality rate.However,pregnant women in the hospital can not be served anytime and anywhere as a result ofmaternal and child-monitoring devices used are totally with huge size and expensivecost. Meanwhile, some portable equipments can neither provide accurate judgment,due to the single index and limiting monitoring scope.And Internet of Things switchthe existing passive mode "go to hospital with sick" to a positive modern medicalmode-"Prevents early and actively treat ahead".Monitoring systems based on theInternet of Things(IOT) are constantly emerging at the moment. The mainachievements of this paper are:1. Aiming at the present situation, an advanced maternal and infant monitoringsystem architecture based on the Internet of Things is proposed in this paper. In thissystem architecture, portable monitoring and hospital care center are organicalcombined over the network, guaranteeing that pregnant women could be under closewatch with the portable equipment and while, deep analysis on physical conditionaccording to latest data can be provided by hospital care center whenever andwherever.2. In this paper, a distill arithmetic on real-time fetal heart rate is designed, with alow complexity and less storage space. The existing portable FHR-collect device getspower from batteries, restricted by low calculates ability, small storage space andlimited energy and so forth. Therefore, the existing FHR distill arithmetic (wavelettransform or autocorrelation algorithm) is not available to collect FHR at actual time. This paper shows an improved median filter algorithm, which can both reduce thecomplexity of calculation and collect FHR in time efficiently. The main idea is toperform binary search instead of data sorting, in order to speed up the median filtering.And self-adaptive extraction algorithm of peaks could be used to get wave data,effective avoiding false detection and residual error.3. Hospital care center with practical value is realized in this paper. Hospital carecenter could have access to collect real-time data and discuss them in great depth,providing the scientific proof for doctor’s official diagnosis to give some quicksuggestions.