With the advent of 4G and other long-term evolution
(LTE) wireless networks, the traditional boundaries of patient
record propagation are diminishing as networking technologies extend
the reach of hospital infrastructure and provide on-demand
mobile access to medical multimedia data. However, due to legacy
and proprietary software, storage and decommissioning costs, and
the price of centralization and redevelopment, it remains complex,
expensive, and often unfeasible for hospitals to deploy their
infrastructure for online and mobile use. This paper proposes
the SparkMed data integration framework for mobile healthcare
(m-Health), which significantly benefits from the enhanced network
capabilities of LTE wireless technologies, by enabling a wide
range of heterogeneous medical software and database systems
(such as the picture archiving and communication systems, hospital
information system, and reporting systems) to be dynamically integrated
into a cloud-like peer-to-peer multimedia data store. Our
framework allows medical data applications to share datawithmobile
hosts over a wireless network (such asWiFi and 3G), by binding
to existing software systems and deploying them as m-Health applications.
SparkMed integrates techniques frommultimedia streaming,
rich Internet applications (RIA), and remote procedure call
(RPC) frameworks to construct a Self-managing, Pervasive Automated
netwoRK for Medical Enterprise Data (SparkMed). Further,
it is resilient to failure, and able to use mobile and handheld
devices to maintain its network, even in the absence of dedicated
server devices. We have developed a prototype of the SparkMed
framework for evaluation on a radiological workflow simulation,
which uses SparkMed to deploy a radiological image viewer as an
m-Health application for telemedical use by radiologists and stakeholders.
We have evaluated our prototype using ten devices over
WiFi and 3G, verifying that our framework meets its two main
objectives: 1) interactive delivery of medical multimedia data to
mobile devices; and 2) attaching to non-networked medical software
processes without significantly impacting their performance.
Consistent response times of under 500 ms and graphical frame
rates of over 5 frames per second were observed under intended
usage conditions. Further, overhead measurements displayed linear
scalability and low resource requirements.
With the advent of 4G and other long-term evolution
(LTE) wireless networks, the traditional boundaries of patient
record propagation are diminishing as networking technologies extend
the reach of hospital infrastructure and provide on-demand
mobile access to medical multimedia data. However, due to legacy
and proprietary software, storage and decommissioning costs, and
the price of centralization and redevelopment, it remains complex,
expensive, and often unfeasible for hospitals to deploy their
infrastructure for online and mobile use. This paper proposes
the SparkMed data integration framework for mobile healthcare
(m-Health), which significantly benefits from the enhanced network
capabilities of LTE wireless technologies, by enabling a wide
range of heterogeneous medical software and database systems
(such as the picture archiving and communication systems, hospital
information system, and reporting systems) to be dynamically integrated
into a cloud-like peer-to-peer multimedia data store. Our
framework allows medical data applications to share datawithmobile
hosts over a wireless network (such asWiFi and 3G), by binding
to existing software systems and deploying them as m-Health applications.
SparkMed integrates techniques frommultimedia streaming,
rich Internet applications (RIA), and remote procedure call
(RPC) frameworks to construct a Self-managing, Pervasive Automated
netwoRK for Medical Enterprise Data (SparkMed). Further,
it is resilient to failure, and able to use mobile and handheld
devices to maintain its network, even in the absence of dedicated
server devices. We have developed a prototype of the SparkMed
framework for evaluation on a radiological workflow simulation,
which uses SparkMed to deploy a radiological image viewer as an
m-Health application for telemedical use by radiologists and stakeholders.
We have evaluated our prototype using ten devices over
WiFi and 3G, verifying that our framework meets its two main
objectives: 1) interactive delivery of medical multimedia data to
mobile devices; and 2) attaching to non-networked medical software
processes without significantly impacting their performance.
Consistent response times of under 500 ms and graphical frame
rates of over 5 frames per second were observed under intended
usage conditions. Further, overhead measurements displayed linear
scalability and low resource requirements.
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