Author:

Keywords:

Science & Technology, Technology, Life Sciences & Biomedicine, Computer Science, Information Systems, Computer Science, Interdisciplinary Applications, Mathematical & Computational Biology, Medical Informatics, Computer Science, Distributed indoor localization, low resources, received signal strength (RSS), scalability, LOCATION, Humans, Medical Informatics Applications, Monitoring, Physiologic, Patient Identification Systems, Signal Processing, Computer-Assisted, Support Vector Machine, Wireless Technology

Abstract:

In current healthcare environments, a trend towards mobile and personalized interactions between people and nurse call systems is strongly noticeable. Therefore it should be possible to locate patients at all times and in all places throughout the care facility. The present article aims at describing a method by which a mobile node can locate itself indoors, based on signal strength measurements and a minimal amount of yes/no decisions. The algorithm has been developed specifically for use in a healthcare environment. With extensive testing and statistical support, we prove our algorithm can be used in a healthcare setting with an envisioned level of localization accuracy up to room revel (or region level in a corridor), while avoiding heavy investments since the hardware of an existing nurse call network can be reused. The approach opted for leads to very high scalability, since thousands of mobile nodes can locate themselves. Network timing issues and localization update delays are avoided, which ensures a patient can receive the needed care in a time and resources efficient way