Abstract
‘Lean’ principles are being applied to healthcare to optimize the operating processes. One such tool is the development of ‘spaghetti diagrams’ to track the movement of staff to expose inefficient layouts and identify large distances traveled between key steps in a hospital department or ward. In this paper we report on an automated tool based on smart phone sensors that will record and provide reports on the movement of staff in the emergency room of the Children’s Hospital of The King’s Daughters. Dead Reckoning also known as Deduced Reckoning, is a process of calculating one’s current position by using a previously determined or known position, and advancing that position based upon known or estimated measurements over elapsed time and course. Most smart phones today come equipped with all the necessary sensors that allow us to design such a system. We have built a prototype system that can track a person from a known location indoors and continue to plot the user’s position and can provide the number of strides the user has taken, the approximate length for each stride and direction of the user with each stride. The prototype system also includes a path correction module that considers the physical objects on a floor map and rules out corrects for paths that intersect physical objects. It has been successfully tested on a laboratory floor of the Computer Science Department of Old Dominion University and the emergency floor of the Children’s Hospital.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Krafcik, J.F.: Triumph of the lean production system. Sloan Management Review 30(1), 41–52 (1988)
Toussaint, J.S., Berry, L.L.: The Promise of Lean in Health Care. Mayo Clinic Proceedings 88(1), 74–82 (2013)
Uddin, M., Gupta, A., Maly, K., Nadeem, T., Godambe, S., Zaritsky, A.: SmartSpaghetti: Accurate and Robust Tracking of a Human’s Location. In: 2014 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Valencia, Spain, pp. 129–132 (June 2014)
Lim, Y.P., Brown, I.T., Khoo, J.C.T.: An accurate and robust gyroscope-based pedometer. In: 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2008, Vancouver, BC, pp. 4587–4590 (2008)
Jayalath, S., Abhayasinghe, N., Jayalath, S.: A gyroscope based accurate pedometer algorithm. In: 2013 8th International Conference on Computer Science & Education (ICCSE), pp. 551–555 (April 2013)
Li, F., Zhao, C., Ding, G., Gong, J., Liu, C., Zhao, F.: A reliable and accurate indoor localization method using phone inertial sensors. In: Proceedings of the 2012 ACM Conference on Ubiquitous Computing, UbiComp 2012, pp. 421–430 (2012)
Uddin, M., Gupta, A., Maly, K., Nadeem, T., Godambe, S., Zaritsky, A.: SmartSpaghetti: use of smart devices to solve health care problems. In: International Workshop on Biomedical and Health Informatics, Shanghai, China, pp. 40–45 (December 2013)
Shuster, M.D.: The quaternion in Kalman filtering. In: AAS/AIAA Astrodynamics Conference (1993)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Pitapurapu, R. et al. (2015). Dead Reckoning with Smartphone Sensors for Emergency Rooms. In: Geissbühler, A., Demongeot, J., Mokhtari, M., Abdulrazak, B., Aloulou, H. (eds) Inclusive Smart Cities and e-Health. ICOST 2015. Lecture Notes in Computer Science(), vol 9102. Springer, Cham. https://doi.org/10.1007/978-3-319-19312-0_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-19312-0_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19311-3
Online ISBN: 978-3-319-19312-0
eBook Packages: Computer ScienceComputer Science (R0)