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ECG Monitoring System Based On Wireless Network

Posted on:2016-01-15Degree:MasterType:Thesis
Country:ChinaCandidate:J Y JiaFull Text:PDF
GTID:2284330464959532Subject:Radio Physics
Abstract/Summary:PDF Full Text Request
In recent years, the technology of network has been in rapid development. Especially cloud computing and cloud storage technology mature, which makes mobile healthcare possible. As our country gradually enters the era of an aging population, the state share of GDP spent on medical expenses is increasing year by year, and as young people are prone to cardiovascular and cerebrovascular diseases leading to one highest death rate as a result. Therefore, early detection and treatment have great significance in terms of saving lives and reducing health care costs.As China’s medical resources are relatively concentrated in economically developed areas, medical treatment is difficult and expensive; the status quo is not possible to change greatly in a short time. In order to solve this problem, this paper presents the ECG-based wireless networks system.In this paper, the extraction of human ECG use a five-point threshold slope characteristic parameter method, and then by way of wireless communication upload cloud server, through mobile phones and other terminals can access into the database, which provides the basis for the doctor’s diagnosis. In this paper, the works are mainly concluded as follow: 1. the hardware circuit on getting ECG was designed and PCB board was fabricated. 2. the pretreatment process of ECG signal was investigated, and the digital signal processing technology was used to preprocess ECG. 3.the five-point slope threshold algorithm was designed to detect the QRS wave of ECG. 4.the big T wave suppression algorithms was proposed for solving the inaccuracy of t he heart rate measurement.Clinical data tests show that the system of human ECG peak class features high detection rate and can automatically analyze the type of arrhythmia in humans.
Keywords/Search Tags:electrocardiogram, feature extraction, peak feature
PDF Full Text Request
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