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Information × Registration Number 0223U002725, 0121U110623 , R & D reports Title Intelligent service for diagnosing the human respiratory system condition to reduce risks in a pandemic COVID-19 popup.stage_title Head Petrenko Anatolii I., д.т.н. Registration Date 02-03-2023 Organization Educational and Scientific Complex "Institute for Applied System Analysis" of National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" popup.description2 Information-analytical means of improving the wireless sensor network (WSN) efficiency, which use mobile devices and specialized software to collect data on the state of health of patients, allowing remote diagnosis of various diseases and receiving preliminary diagnosis and treatment recommendations, were studied. A service-oriented WSN architecture for medicine with a service depository is proposed, allowing solving the problem of WSN compatibility of different developers when they are combined into a global network. There is a well-founded possibility of compensating certain shortcomings of using simple portable body sensors due to deep learning methods, in particular, the use of convolutional neural networks for setting up the necessary diagnostic procedures. The software for the medical platform was developed based on the principles of microservice architecture and micro-frontends. A number of REST services have been implemented to meet the needs of patients: for creating and monitoring the implementation of treatment plans, for the output of current information on an information indicator panel, for diagnosing defects in human respiratory activity, such as sleep apnea. The transfer of medical services to the cloud leads to a decrease in capital costs for the use of existing assets, an increase in the speed and flexibility of developing new ones, an effective management of communication with patients. The developed diagnosis services for defects in human respiratory activity, using the example of sleep apnea, are based on the use of both electrocardiogram data and PPG (blood oxygen saturation) signals, so their complex application increases the remote diagnostics result reliability, and the wide spread of relevant sensors simplifies the production of diagnostic devices. A software-hardware module was developed as part of a physical device based on the PPG sensor MAX30102 and the corresponding cloud service using the paradigm of serverless lambda calculations. Product Description popup.authors Beznosyk Oleksandr Yuriyovych Boloban Oleg Anatoliyovych Bulakh Bogdan Victorovych Kyslyi Roman Volodymyrovych Pysmennyi Ihor Oleksandrovych Kharchenko Kostyantyn Vasyliovych popup.nrat_date 2023-03-02 Close