The Front End Design of a Health Monitoring System

Abstract. In this paper an efficient e-health platform based on a low-cost sensor controller system is presented, exhibiting enhanced key characteristics able to provide broad coverage of medical scenarios in a reliable and flexible way. The heart of the system is a low-cost sensor controller capable of performing both simple medical tests and more advanced ones communicating with a Gateway and a tablet or smart phone providing instructions to the patient. Equipped with a simple and flexible communication protocol for data and command exchange, the developed platform is capable of readily supporting a variety of sensors with different sampling profiles. Furthermore, first promising results of on-going work pave the way for achieving considerable enhancement of sensors' accuracy (close to high-cost commercial ones) and significant extension of platform's portability through power consumption minimization. These characteristics have been verified by experimenting with various medical scenarios one of which is demonstrated here in detail

Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care

[EN] Health and sociological indicators alert that life expectancy is increasing, hence so are the years that patients have to live with chronic diseases and co-morbidities. With the advancement in ICT, new tools and paradigms are been explored to provide effective and efficient health care. Telemedicine and health sensors stand as indispensable tools for promoting patient engagement, self-management of diseases and assist doctors to remotely follow up patients. In this paper, we evaluate a rapid prototyping solution for information merging based on five health sensors and two low-cost ubiquitous computing components: Arduino and Raspberry Pi. Our study, which is entirely described with the purpose of reproducibility, aimed to evaluate the extent to which portable technologies are capable of integrating wearable sensors by comparing two deployment scenarios: Raspberry Pi 3 and Personal Computer. The integration is implemented using a choreography engine to transmit data from sensors to a display unit using web services and a simple communication protocol with two modes of data retrieval. Performance of the two set-ups is compared by means of the latency in the wearable data transmission and data loss. PC has a delay of 0.051 ± 0.0035 s (max = 0.2504 s), whereas the Raspberry Pi yields a delay of 0.0175 ± 0.149 s (max = 0.294 s) for N = 300. Our analysis confirms that portable devices (p << 0.01) are suitable to support the transmission and analysis of biometric signals into scalable telemedicine systems.Bayo-Monton, JL.; Martinez-Millana, A.; Han, W.; Fernández Llatas, C.; Sun, Y.; Traver Salcedo, V. (2018). Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care. Sensors. 18(6). https://doi.org/10.3390/s18061851S18