Name
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-19312-0_17 | INCLUSIVE SMART CITIES AND E-HEALTH |
Keywords | Field | DocType |
Indoors positioning, Lean process, Smartphone sensors, Error correction, Spaghetti diagram | STRIDE,Computer science,Computer security,Error detection and correction,Dead reckoning,Smart phone,Emergency rooms,The Intersect | Conference |
Volume | ISSN | Citations |
9102 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 3 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ravi Pitapurapu | 1 | 0 | 0.34 |
| Ajay Gupta | 2 | 0 | 0.34 |
| Kurt Maly | 3 | 567 | 139.93 |
| Tamer Nadeem | 4 | 835 | 80.46 |
| Ramesh Govindarajulu | 5 | 0 | 0.34 |
| Sandip Godambe | 6 | 0 | 0.34 |
| Arno Zaritsky | 7 | 0 | 0.34 |