A Method and System for Efficient Continuous Mobile Health Data Processing

Publication Summary

Existing mobile healthcare system will use mobile phone as a Hub and let it relay all the datas to the backend server, the article showes a method and system to optimize the data flow from mobile phone to backend server so that the energy cost and traffic fee is reduced to a reasonable level.

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Language	English (United States)

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A Method and System for Efficient Continuous MobileHealth Data Processing

For telecom service provider, Mobile healthcare wasconsidered as one of killer applications in 3G agesince mobile phone can be used as person health assistant. High efficient and low cost emergency medical service, remote healthcare service, personalhealth management system is required by aging populations, chronic patients etc.

Today, in the world there are 1 billion adults overweight,860 million chronic disease patients,600 million elders age 60 or older,75-85% of healthcare spending is on chronic disease management.

Mobile enabled healthcare service can provide low cost chronic disease management and continual monitoring service. In General speaking, Mobile healthcare solution is combination of sensor technique, mobile technique and event processing technique.

However, existing mobile healthcare system will usemobile phone as a Hub and let it relay all the datas to the backend server,

while it works, the existing

solution has some problems.

To mobile device there are some challenge problems in this scenario, including 1)High communication cost due to high GRRS/EDGE traffic fee. 2) Great Energy Consumption, Reduce Battery Usage Time, since the phone needs to keep transmitting over long time unacceptable network.

So far, there are some methods to reduce traffic such as data compress. Mobile phone also can reduce energy consumption through shutdown external interface, cut down screen light. There is not whole system optimization method.

The article showes a method and system to optimize the data flow from mobile phone to backend server so that the energy cost and traffic fee is reduced to a reasonable level.

   Figure 1 shows a typical deployment model of mobilehealthcare. Sensors can collect health data and send to event processing system through wireless network, and then event platform will route relateddata and event to background system.

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In-hom e D e vices

 D e vice M an a g er

 R em ote M on ito ring

S erve r

E xa m ple

P ro vid er

A pplicatio ns

P H R

E M R

  D ise as e
M a na gem ent

W ire d G luc o se M e te r

M e dica tion P ack

W ire d W eighing

S cale

 D e vice s to collec t pe rsonal health data

• C ollect device da ta
• R e liable M essag ing
• Id entification

IB M W ebs ph e re S e ns or
E ve nts

• A ggrega te da ta from la rg e n um ber of de vices

• P erform even t proc essin g
• M ap in to P rovide r ap plication

Figure 1 typical mobile healthcare system.

the center of existing mobile healthcare system is a rule engine

Most of rule engine now will compile rules into Rete network by Rete algorithm, The compilation algorithm describes how the Rules in the Production Memory to generate an efficient discrimination network. Innon-technical terms, a discrimination network is used to filter data. The idea is to fil...

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