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A case-based patient identification system using pulseoximeter and a personalized health profile
Örebro University, School of Science and Technology. (Center for Applied Autonomous Sensor Systems)
Örebro University, School of Science and Technology. (Center for Applied Autonomous Sensor Systems)
Örebro University, School of Science and Technology. (Center for Applied Autonomous Sensor Systems)ORCID iD: 0000-0002-3122-693X
2012 (English)Conference paper, Oral presentation only (Refereed)
Abstract [en]

This paper proposes a case-based system framework in order to identify patient using their health parameters taken with physiological sensors. It combines a personalized health profiling protocol with a Case-Based Reasoning (CBR) approach. The personalized health profiling helps to determine a number of individual parameters which are important inputs for a clinician to make the final diagnosis and treatment plan. The proposed system uses a pulse oximeter that measures pulse rate and blood oxygen saturation. The measurements are taken through an android application in a smart phone which is connected with the pulseoximeter and bluetooth communication. The CBR approach helps clinicians to make a diagnosis, classification and treatment plan by retrieving the most similar previous case. The case may also be used to follow the treatment progress. Here, the cases are formulated with person’s contextual information and extracted features from sensor signal measurements. The features are extracted considering three domain analysis:1) time domain features using statistical measurement, 2) frequency domain features applying Fast Fourier Transform (FFT), and 3) time-frequency domain features applying Discrete Wavelet Transform (DWT). The initial result is acceptable that shows the advancement of the system while combining the personalized health profiling together with CBR.

Place, publisher, year, edition, pages
Springer, 2012.
National Category
Signal Processing Computer Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-24086OAI: oai:DiVA.org:oru-24086DiVA: diva2:540932
Conference
workshop on CBR in the Health Sciences at 20th International Conference on Case-Based Reasoning, ICCBR12
Projects
Remote
Available from: 2012-08-24 Created: 2012-07-12 Last updated: 2017-10-17Bibliographically approved

Open Access in DiVA

fulltext(1627 kB)569 downloads
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Other links

http://www.iccbr.org/iccbr12/doku.php?id=start

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Ahmed, Mobyen UddinLoutfi, Amy
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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
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  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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