An Experimental Study of Personalized Mobile Assistance Service in Healthcare Emergency Situations

Chronic diseases currently account for most deaths in the world. Despite the fact that these illnesses are generally incurable, they are often preventable and manageable, and concomitant risks are reducible. In particular, acute out-of-hospital complications of the chronic conditions can pose a threat to health and life. Nevertheless, in the case of early detection and timely treatment the remote patient has a good chance to survive. The success of the early management and resuscitation is directly related to the arrival time of the emergency medical services. In our approach, a mobile health (m-Health) service is introduced to healthcare. The service supports involvement of trained volunteers to first aid and resuscitation, dispatching them depending on the proximity to the patient, and provide a guidance. Our design concept of this service is heavily relies upon the smart spaces paradigm, namely, the personalized assistance in medical emergencies is delivered to mobile participants operated in networked environment as a result of knowledge reasoning over the shared information. In this paper, we study the architecture and key features of the service and its smart m-Health space. We experimentally evaluate the Smart-M3 based implementation to analyze the feasibility and applicability of such mobile information services for the case of medical emergencies. Keywords–healthcare; medical emergency; m-Health; personalized assistance service; smart spaces; Internet of Things; Smart-M3; performance evaluation

[1]  Ivan Timofeev,et al.  Design and implementation of the first aid assistance service based on Smart-M3 platform , 2016, 2016 18th Conference of Open Innovations Association and Seminar on Information Security and Protection of Information Technology (FRUCT-ISPIT).

[2]  J. Ornato,et al.  Improving survival from sudden cardiac arrest: the "chain of survival" concept. A statement for health professionals from the Advanced Cardiac Life Support Subcommittee and the Emergency Cardiac Care Committee, American Heart Association. , 1991, Circulation.

[3]  Jethro B. de Guzman,et al.  Mobile Emergency Response Application Using Geolocation for Command Centers , 2014 .

[4]  Luca Roffia,et al.  An Integrated Framework to Achieve Interoperability in Person-Centric Health Management , 2011, International journal of telemedicine and applications.

[5]  Hugh Tunstall-Pedoe,et al.  Preventing Chronic Diseases. A Vital Investment: WHO Global Report. Geneva: World Health Organization, 2005. pp 200. CHF 30.00. ISBN 92 4 1563001. Also published on http://www.who.int/chp/chronic_disease_report/en/ , 2006 .

[6]  Ilya Paramonov,et al.  Communication between emergency medical system equipped with panic buttons and hospital information systems: Use case and interfaces , 2015, 2015 Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference (AINL-ISMW FRUCT).

[7]  Pedro Castillejo,et al.  An Internet of Things Approach for Managing Smart Services Provided by Wearable Devices , 2013, Int. J. Distributed Sens. Networks.

[8]  Yevgeni Koucheryavy,et al.  IoT Use Cases in Healthcare and Tourism , 2015, 2015 IEEE 17th Conference on Business Informatics.

[9]  Dmitry G. Korzun,et al.  Digital assistance services for emergency situations in personalized mobile healthcare: Smart space based approach , 2015, 2015 International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON).

[10]  Ronald Brown,et al.  Smart-M3 information sharing platform , 2010, The IEEE symposium on Computers and Communications.

[11]  Haluk Demirkan,et al.  A Smart Healthcare Systems Framework , 2013, IT Professional.

[12]  Björn Sund Effect of response times on survival from out-of-hospital cardiac arrest: using geographic information systems , 2012 .

[13]  Alexander V. Smirnov,et al.  The Smart-M3 Platform: Experience of Smart Space Application Development for Internet of Things , 2015, NEW2AN.

[14]  Alexander V. Borodin,et al.  The cross-platform application for arrhythmia detection , 2012, 2012 12th Conference of Open Innovations Association (FRUCT).

[15]  M. Goldacre,et al.  Determinants of the decline in mortality from acute myocardial infarction in England between 2002 and 2010: linked national database study , 2012, BMJ : British Medical Journal.

[16]  Sergey Balandin,et al.  Smart Spaces Enabled Mobile Healthcare Services in Internet of Things Environments , 2015, Int. J. Embed. Real Time Commun. Syst..

[17]  M. Schalij,et al.  High survival rate of 43% in out-of-hospital cardiac arrest patients in an optimised chain of survival , 2014, Netherlands Heart Journal.

[18]  Reinhard Busse,et al.  Tackling Chronic Disease in Europe: Strategies, Interventions and Challenges , 2010 .

[19]  D. Mozaffarian,et al.  Executive Summary: Heart Disease and Stroke Statistics—2015 Update A Report From the American Heart Association , 2011, Circulation.

[20]  J. Ornato,et al.  Prehospital and emergency department care to preserve neurologic function during and following cardiopulmonary resuscitation. , 2006, Neurologic clinics.

[21]  Alexander V. Borodin,et al.  Architectural approach to the multisource health monitoring application design , 2015, 2015 17th Conference of Open Innovations Association (FRUCT).