Network architecture for global biomedical monitoring service

Abstract

Most of the patients who are in hospitals and, increasingly, patients controlled remotely from their homes, at-home monitoring, are continuously monitored in order to control their evolution. The medical devices used up to now, force the sanitary staff to go to the patients' room to control the biosignals that are being monitored, although in many cases, patients are in perfect conditions. If patient is at home, it is he or she who has to go to the hospital to take the record of the monitored signal. New wireless technologies, such as BlueTooth and WLAN, make possible the deployment of systems that allow the display and storage of those signals in any place where the hospital intranet is accessible. In that way, unnecessary displacements are avoided. This paper presents a network architecture that allows the identification of the biosignal acquisition device as IP network nodes. The system is based on a TCP/IP architecture which is scalable and avoids the deployment of a specific purpose network.

Real-time signal detection and classification algorithms for body-centered systems

“…Body-centered communication systems have many applications in the biomedical, telemedicine and entertainment fields [15], [16], [17], [23], [24] and [25], where obviously wireless technology presents many advantages. Such systems are designed using the so-called Wireless Body Area Networks (WBANs), which are made up of a set of mobile and compact intercommunicating sensors, either wearable or implanted into the human body, which monitor vital body parameters and movements.…”

“…Such systems are designed using the so-called Wireless Body Area Networks (WBANs), which are made up of a set of mobile and compact intercommunicating sensors, either wearable or implanted into the human body, which monitor vital body parameters and movements. In medical applications, these devices, communicating through wireless technologies, transmit data from the body to a central station, from where the data can be forwarded to a hospital, clinic or elsewhere [15]. In Figure 1.…”

“…Additionally, in order to ease the fitting process, the CCDF exp is log-scaled so that Λ can be obtained by means of a linear fit as shown in (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20).…”