Abstract
This paper presents the architecture of a medical platform for chronic diseases sufferers that enables specialist physicians to have a permanent overview of the patient’s health. The proposed system, HChecked, integrates the monitoring of vital parameters, reception of notification in case of any exceeding of the pre-defined limits of these parameters and prediction of the evolution of the current disease or of the possibility of occurrence of another disease. The software system follows the idea of trading systems that offers efficient prediction with a high level of security. This concept is based on a particular implementation of finite state-machine algorithms, which enable physicians to run complex rules against particular health information of a certain patient to predict the evolution of the current diseases or the appearance of others. Although the system allows many points of view, this paper is oriented towards the specific way in which complex rules are created.
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Acknowledgement
This work was partially supported by the research grant CHIST-ERA/1/01.10.2012 – “GEMSCLAIM: GreenEr Mobile Systems by Cross LAyer Integrated energy Management”.
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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Fuicu, S., Avramescu, A., Lascu, D., Padurariu, R., Marcu, M. (2015). Real-Time Monitoring Using Finite State-Machine Algorithms. In: Giaffreda, R., et al. Internet of Things. User-Centric IoT. IoT360 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 150. Springer, Cham. https://doi.org/10.1007/978-3-319-19656-5_27
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DOI: https://doi.org/10.1007/978-3-319-19656-5_27
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