Park, Soojin

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2010 - 20123
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  • Publication
    GSA: A Framework for Rapid Prototyping of Smart Alarm Systems
    (2010-11-11) King, Andrew; Roederer, Alex; Arney, David; Chen, Sanjian; Fortino-Mullen, Margaret; Giannareas, Ana; Hanson III, C. William; Kern, Vanessa; Stevens, Nicholas; Viesca Trevino, Adrian; Park, Soojin; Sokolsky, Oleg; Lee, Insup; Tannen, Jonathan
    We describe the Generic Smart Alarm, an architectural framework for the development of decision support modules for a variety of clinical applications. The need to quickly process patient vital signs and detect patient health events arises in many clinical scenarios, from clinical decision support to tele-health systems to home-care applications. The events detected during monitoring can be used as caregiver alarms, as triggers for further downstream processing or logging, or as discrete inputs to decision support systems or physiological closed-loop applications. We believe that all of these scenarios are similar, and share a common framework of design. In attempting to solve a particular instance of the problem, that of device alarm fatigue due to numerous false alarms, we devised a modular system based around this framework. This modular design allows us to easily customize the framework to address the specific needs of the various applications, and at the same time enables us to perform checking of consistency of the system. In the paper we discuss potential specific clinical applications of a generic smart alarm framework, present the proposed architecture of such a framework, and motivate the benefits of a generic framework for the development of new smart alarm or clinical decision support systems.
  • Publication
    Clinical Decision Support for Integrated Cyber-Physical Systems: A Mixed Methods Approach
    (2012-01-01) Roederer, Alex; Hicks, Andrew R.; Oyeniran, Enny; Lee, Insup; Park, Soojin
    We describe the design and implementation of a clinical decision support system for assessing risk of cerebral vasospasm in patients who have been treated for aneurysmal subarachnoid hemorrhage. We illustrate the need for such clinical decision support systems in the intensive care environment, and propose a three pronged approach to constructing them, which we believe presents a balanced approach to patient modeling. We illustrate the data collection process, choice and development of models, system architecture, and methodology for user interface design. We close with a description of future work, a proposed evaluation mechanism, and a description of the demo to be presented.
  • Publication
    Challenges and Research Directions in Medical Cyber-Physical Systems
    (2012-01-01) Lee, Insup; Sokolsky, Oleg; Chen, Sanjian; Hatcliff, John; Jee, Eunkyoung; Kim, BaekGyu; King, Andrew; Mullen-Fortino, Margaret; Park, Soojin; Roederer, Alexander; Venkatasubramanian, Krishna
    Medical cyber-physical systems (MCPS) are lifecritical, context-aware, networked systems of medical devices. These systems are increasingly used in hospitals to provide highquality continuous care for patients. The need to design complex MCPS that are both safe and effective has presented numerous challenges, including achieving high assurance in system software, intoperability, context-aware intelligence, autonomy, security and privacy, and device certifiability. In this paper, we discuss these challenges in developing MCPS, some of our work in addressing them, and several open research issues