Performance analysis of multiple Indoor Positioning Systems in a healthcare environment. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Haute, Tom; Poorter, Eli; Crombez, Pieter; Lemic, Filip; Handziski, Vlado; Wirström, Niklas; Wolisz, Adam; Voigt, Thiemo; Moerman, Ingrid
• Is Part Of: International journal of health geographics. Volume 15:Issue 1(2016)
• Page Start: 1
• Page End: 15
• Publication Date: 2016-12
• Subjects: Indoor localization -- Healthcare -- Hospital -- RSSI -- ToA -- Fingerprinting; Geographic information systems -- Health aspects -- Periodicals; Geography -- Health aspects -- Periodicals; 614.40285
• DOI: 10.1186/s12942-016-0034-z
• Languages: English
• ISSNs: 1476-072X

Abstract

Abstract Background The combination of an aging population and nursing staff shortages implies the need for more advanced systems in the healthcare industry. Many key enablers for the optimization of healthcare systems require provisioning of location awareness for patients (e.g. with dementia), nurses, doctors, assets, etc. Therefore, many Indoor Positioning Systems (IPSs) will be indispensable in healthcare systems. However, although many IPSs have been proposed in literature, most of these have been evaluated in non-representative environments such as office buildings rather than in a hospital. Methods To remedy this, the paper evaluates the performance of existing IPSs in an operational modern healthcare environment: the "Sint-Jozefs kliniek Izegem" hospital in Belgium. The evaluation (data-collecting and data-processing) is executed using a standardized methodology and evaluates the point accuracy, room accuracy and latency of multiple IPSs. To evaluate the solutions, the position of a stationary device was requested at 73 evaluation locations. By using the same evaluation locations for all IPSs the performance of all systems could objectively be compared. Results Several trends can be identified such as the fact that Wi-Fi based fingerprinting solutions have the best accuracy result (point accuracy of 1.21 m and room accuracy of 98 %) however it requires calibration before use and needs 5.43 s to estimate the location. On the other hand, proximity based solutions (based on sensor nodes) are significantly cheaper to install, do not require calibration and still obtain acceptable room accuracy results. Conclusion As a conclusion of this paper, Wi-Fi based solutions have the most potential for an indoor positioning service in case when accuracy is the most important metric. Applying the fingerprinting approach with an anchor installed in every two rooms is the preferred solution for a hospital environment.