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A Ubiquitous Approach for Visualizing Back Pain Data.

Authors :
Gervasi, Osvaldo
Gavrilova, Marina L.
Kumar, Vipin
Laganà, Antonio
Lee, Heow Pueh
Mun, Youngsong
Taniar, David
Tan, Chih Jeng Kenneth
Serif, T.
Ghinea, G.
Frank, A.O.
Source :
Computational Science & Its Applications - ICCSA 2005 (9783540258612); 2005, p1018-1027, 10p
Publication Year :
2005

Abstract

We describe a wireless enabled solution for the vizualisation of back pain data. Our approach uses pain drawings to record spatial location and type of pain and enables data collection with appropriate time stamping, thus providing a means for the seldom-recorded (but often attested) time-varying nature of pain, with consequential impact on monitoring the effectiveness of patient treatment regimes. Moreover, since the implementation platform of our solution is that of a Personal Digital Assistant, data collection takes place ubiquitously, providing back pain sufferers with mobility problems (such as wheelchair users) with a convenient means of logging their pain data and of seamlessly uploading it to a hospital server using WiFi technology. Stakeholder results show that our approach is generally perceived to be an easy to use and convenient solution to the challenges of anywhere/anytime data collection. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540258612
Database :
Supplemental Index
Journal :
Computational Science & Its Applications - ICCSA 2005 (9783540258612)
Publication Type :
Book
Accession number :
32901884
Full Text :
https://doi.org/10.1007/11424826_109