Team for Research in
Ubiquitous Secure Technology

Citation
Yuan Xue, Posu Yan. "Body Sensors for In-Home Patient Monitoring". Talk or presentation, 30, November, 2009.

Abstract
The cost of health care has become a national concern. Recent advances in wireless communication, networking and information technology have made it possible to monitor rehabilitation outcomes across diverse health care environments (such as hospital, rehabilitation facility, nursing facilities, or home care). This provides a unique opportunity for evidence-based medical practice where a large amount of medical information can be collected to help determine the most effective strategies for treating chronic illness, reducing disability and secondary conditions, improving health outcomes, and reducing the healthcare expenses by more efficient use of clinical resources. To facilitate this process, existing technologies on wireless communication, sensor platform, networking, and database have to be fully integrated with the existing clinical enterprise practice to become part of the overall chronic disease management process. This talk presents our work on supporting remote congestive heart failure (CHF) patient monitoring and management via an integration of biosensor technology, mobile wireless communication platform and clinical enterprise system. In the remote patient monitoring and management, a sensor-based networking system captures and analyzes the medical data of a patient and securely transmits in real time the relevant information to the clinical patient management system. It is built on top of open-source software and readily available hardware. The system is designed to be generic -- it not only monitors CHF patients but supports mobile health applications in general. The design of the remote patient monitoring and management system employs a Model-Integrated Computing (MIC) approach, where the formal models of treatment protocols is built to manage the overall medical processes. Using a model-based approach, security becomes an integral part of the overall system design, where formal models of the security policies are integrated into the clinical workflow models. This talk will present our system design, its end-to-end security support, and the experiments on the monitoring and treatment of congestive heart failure (CHF) patients. We will also present a second BSN system, WAVE and Berkeley Fit, which aims to leverage social networking to promote physical fitness.

Electronic downloads

• 19%20-%20Xue-Yan.ppt · application/vnd.ms-powerpoint · 1328 kbytes

• HTML

  Yuan Xue, Posu Yan. <a
  href="http://www.truststc.org/pubs/649.html"
  ><i>Body Sensors for In-Home Patient
  Monitoring</i></a>, Talk or presentation,  30,
  November, 2009.

• Plain text

  Yuan Xue, Posu Yan. "Body Sensors for In-Home Patient
  Monitoring". Talk or presentation,  30, November, 2009.

• BibTeX

  @presentation{XueYan09_BodySensorsForInHomePatientMonitoring,
      author = {Yuan Xue and Posu Yan},
      title = {Body Sensors for In-Home Patient Monitoring},
      day = {30},
      month = {November},
      year = {2009},
      abstract = {The cost of health care has become a national
                concern. Recent advances in wireless
                communication, networking and information
                technology have made it possible to monitor
                rehabilitation outcomes across diverse health care
                environments (such as hospital, rehabilitation
                facility, nursing facilities, or home care). This
                provides a unique opportunity for evidence-based
                medical practice where a large amount of medical
                information can be collected to help determine the
                most effective strategies for treating chronic
                illness, reducing disability and secondary
                conditions, improving health outcomes, and
                reducing the healthcare expenses by more efficient
                use of clinical resources. To facilitate this
                process, existing technologies on wireless
                communication, sensor platform, networking, and
                database have to be fully integrated with the
                existing clinical enterprise practice to become
                part of the overall chronic disease management
                process. This talk presents our work on supporting
                remote congestive heart failure (CHF) patient
                monitoring and management via an integration of
                biosensor technology, mobile wireless
                communication platform and clinical enterprise
                system. In the remote patient monitoring and
                management, a sensor-based networking system
                captures and analyzes the medical data of a
                patient and securely transmits in real time the
                relevant information to the clinical patient
                management system. It is built on top of
                open-source software and readily available
                hardware. The system is designed to be generic --
                it not only monitors CHF patients but supports
                mobile health applications in general. The design
                of the remote patient monitoring and management
                system employs a Model-Integrated Computing (MIC)
                approach, where the formal models of treatment
                protocols is built to manage the overall medical
                processes. Using a model-based approach, security
                becomes an integral part of the overall system
                design, where formal models of the security
                policies are integrated into the clinical workflow
                models. This talk will present our system design,
                its end-to-end security support, and the
                experiments on the monitoring and treatment of
                congestive heart failure (CHF) patients. We will
                also present a second BSN system, WAVE and
                Berkeley Fit, which aims to leverage social
                networking to promote physical fitness. },
      URL = {http://www.truststc.org/pubs/649.html}
  }
  

Posted by Larry Rohrbough on 5 Nov 2009.
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