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Mobile Healthcare System for Personalized Emergency Management

사용자 맞춤형 응급 관리를 위한 모바일 헬스케어 시스템

  • Received : 2014.04.22
  • Accepted : 2014.06.05
  • Published : 2014.06.25

Abstract

In mobile healthcare service, the accurate detection and the notification of the emergency situation are important to chronic patients' life. In the existing healthcare service, the medical staff or medical service provider always judges patients' health status by monitoring from the measured from bio-data. However, it is difficult to monitor many patients in real-time simultaneously, because the medical staff should monitor the health status continuously. Furthermore, an emergency condition diagnosis based solely on the statistical level of the bio-data may be difficult, since the emergency judgment of the bio-data might differ depending on the health characteristics of each person such as age, history of disease, gender, etc. In order to solve this problem, this article presents an mobile healthcare system for emergency bio-data management using a personalized emergency policy. The salient feature of the proposed mobile healthcare system is that the characteristics of the health status of an unique patient is defined to the policy, which is used to judge the emergency condition of the bio-data measured from the patient. The prototype of proposed mobile healthcare system has been built to demonstrate the design concept.

모바일 헬스케어 서비스에서 환자의 응급 상태를 정확하게 응급 감지하고 신속히 알리는 것이 매우 중요하다. 기존의 헬스케어 서비스에서는 전달된 생체 정보를 의료진 또는 의료 서비스 공급자가 항시 모니터링을 하여 환자의 상태를 판단하게 된다. 하지만 의료진이 항시 모니터링을 해야 하기 때문에 다수 환자를 실시간으로 동시에 모니터링하기에는 어렵다. 더구나, 환자마다의 고유한 환자의 건강 상태의 특징 (나이, 성별, 병력 기록 등)들이 있기 때문에 통계적인 의료 지식으로 환자의 상태를 진단하는 것은 더욱 힘든 일이다. 이러한 기존의 문제점을 해결하기 위해서 본 논문에서는 사용자 맞춤형 응급관리를 위한 모바일 헬스케어 시스템을 제시한다. 제안된 모바일 헬스케어 시스템의 특징은 환자의 고유한 건강 상태의 특징을 정책으로 정의하고 이를 기반으로 환자로부터 측정된 생체 정보에 대해 응급 상태를 판단하는 것이다. 제안된 모바일 헬스케어 시스템의 개념을 입증하기 위해 프로토타입을 구현하였다.

Keywords

References

  1. ISO/IEEE 11073-20601 Standard for "Health Infor matics - Personalized health device communication"- Application profile - Optimized exchange protocol-ISO/IEEE 11073-20601, The Institute of Electrical and Electronics Engineers, 2008.
  2. HL7 Clinical Document Architecture (CDA), Release 2.0, Health Level 7, Apr. 2005.
  3. X. Shen, "Emerging Technologies for e-healthcare," IEEE Network, Vol. 26, No. 5, pp. 2-3, 2012. https://doi.org/10.1109/MNET.2012.6375885
  4. S. Franklin, et al., "Does the Relation of Blood Pressure to Coronary Heart Disease Risk Change W ith Aging?: The Framingham Heart Study," American Heart Association, Vol. 103, pp. 1245 -1249, 2001.
  5. J. Wei and G. Kong, "Block-Based Neural Networks for Personalized ECG Signal Classification," IEEE Transactions on Neural Networks, Vol. 18, No. 6, pp. 1750-1761, Nov. 2007. https://doi.org/10.1109/TNN.2007.900239
  6. J. Yao and S. Warren, "Applying the ISO/IEEE 1107 3 Standards to Wearable home Health Monitoring Systems,"Journal of Clinical Monitoring and Comp uting, Vol. 19, No. 6, pp. 427-436, Jan. 2006.
  7. A. Mense, et al., "Healthy interoperability: A st andard based framework for integrating personal monitoring and personal health device data into medical information systems," Journal on Inform ation Technology in Healthcare, Vol. 7, pp. 214-221, 2009.
  8. M. Yang, et al.,"Guideline-driven telemonitoring and follow-up of cardiovascular implantable electronic devices using IEEE 11073, HL7 & IHE profiles," Proc. of IEEE Engineering Medical Biology Society pp. 3192-6, 2011.
  9. ISO/IEEE 11073-10404, 10406: 2010 Health Informatics-Personal Health Device Communication - Device Specialization - Pulse Oximeter, The Institute of Electrical and Electronics Engineers, New York, USA, pp. 1-61, Apr. 2008.