A health monitoring system

Abstract

The invention provides a health monitoring system, which is composed of a health monitoring device, a 3G network and a Web server. The health monitoring device is connected to the Web server through a 3G network. The embedded device of the GPS module, the web server is a virtual host built using cloud computing services, the health monitoring equipment collects data and transmits the data to the web server through the 3G network, and the web server processes the data and feeds back to the health monitoring equipment .

Description

technical field [0001] The invention relates to a wireless health monitoring system, in particular to a system for collecting various physiological indicators of a human body and transmitting them to a server through a wireless 3G network for health monitoring. [0002] Background technique [0003] my country has a large population, insufficient medical resources per capita, and high medical expenses; the aging population is gradually increasing, and daily life cannot receive sufficient care; chronic patients and sub-health groups lack normalized medical diagnosis. In view of these situations, it is very necessary to develop a low-cost, portable, and scalable health monitoring system. [0004] Currently developed wireless health monitoring systems have the following problems: [0005] (1) Limitations of data transmission methods [0006] At present, the data transmission technologies used in the health monitoring system mainly include Zigbee, Bluetooth, serial port, GPRS...

AI Technical Summary

Problems solved by technology

These technologies have certain limitations in the application of health monitoring: serial port transmission is only suitable for fixed data acquisition equipment; Zigbee technology needs to form a network by itself, and can only carry out short-distance transmission, and needs to define its own routing protocol, which is relatively difficult. Complex and costly, the user's range of activities can only be limited to the community; the Bluetooth transmission distance is short, and the transmission effect is interfered by the environment, and the user's range of activities is limited; GPRS has a wide coverage, which can effectively overcome Zigbee and Bluetooth. Shortcomings, but the bandwidth of GPRS is limited, unable to make full use of mobile Internet resources

[0007] (2) Poor expansion performance

[0008] Existing health monitoring system designs have poor scalability and rely too much on improving the performance of monitoring equipment to obtain better monitoring results, such as selecting high-performance chips to implement complex digital filtering algorithms, etc.

Considering the limited resources of embedded devices, the inability to store a large amount of data and the limited computing power, this approach is not economical, and will increase the cost of the device and increase the burden on users

[0009] (3) Based on the C / S architecture, equipment upgrades are complex

[0010] Most of the current monitoring systems adopt the C / S (Client / Server) architecture. The C / S architecture requires users to install specific software. The software upgrade is more troublesome, and the cross-platform performance is poor. For specific platforms, software design needs to be redesigned. The advantage is that the computing tasks can be reasonably allocated to the client and server, which is mainly suitable for fat clients

For resource-constrained applications such as embedded, it is obviously not suitable for the fat client model

[0011] (4) User privacy is easily leaked

[0012] Since the transmitted data involves privacy information such as user accounts and physical health status, current wireless health monitoring systems, especially systems that use the Internet for data transmission, seldom encrypt data, and user data is easily leaked during transmission.

[0013] (5) The battery life of monitoring equipment is short

Ignoring the existence of this problem, it will not be possible to realize the round-the-clock monitoring of users

[0015] (6) Lack of personalized management for different users

This approach causes a large amount of redundancy in each user's health data, which is very unfavorable to user information retrieval and user diagnosis.

Images