Cost-effective vital signs collecting system based on fast biosensors and a flexible Cloud microservices architecture for the prognosis of infectious diseases (Preprint)

Abstract

BACKGROUND Quite often, patients arrive to consultation when the symptoms of an infectious disease are already serious, forcing doctors to divert them to the emergency services. Particularly, the possible anticipation of the diagnosis -prognostic- for institutionalized people would lead to soften the treatment, increasing resident’s wellness and alleviating the degradation of the emergency services. Big data, mobile communications, cloud services or machine learning technologies applied in medicine -e-Health- assist practitioners with efficient tools. OBJECTIVE This article describes a new data collection system for predicting infectious diseases in elderly people, supporting future telecare and medical recommender applications. METHODS The system provides a medical database updated with vital signs that nurses take with medical sensors from residents. The Cloud database is accessible with a flexible microservices software architecture. RESULTS The e-Health system components are cost-effective, leading to massive implementations for servicing disadvantaged areas. The scalable architecture is prepared for big data applications that may extract valuable knowledge patterns for medical research. CONCLUSIONS The innovation relies in the combination of advanced e-Health technologies and procedures that delivers ubiquitously available quality data to provide multifaceted scalable low-cost applications to improve resident’s wealth and release public health care services.