Sökning: WFRF:(Ahmed Mobyen Uddin)
> (2012) >
A case-based patien...
A case-based patient identification system using pulseoximeter and a personalized health profile
-
- Ahmed, Mobyen Uddin, 1976- (författare)
- Örebro universitet,Institutionen för naturvetenskap och teknik,Center for Applied Autonomous Sensor Systems,Örebro University, Sweden
-
- Islam, Asif Moinul, 1984- (författare)
- Örebro University, Örebro, Sweden,Center for Applied Autonomous Sensor Systems
-
- Loutfi, Amy, 1978- (författare)
- Örebro universitet,Institutionen för naturvetenskap och teknik,Center for Applied Autonomous Sensor Systems,Örebro University, Sweden
-
(creator_code:org_t)
- Lyon, France, 2012
- 2012
- Engelska.
-
Ingår i: Proceedings of the ICCBR 2012 Workshops. - Lyon, France. ; , s. 117-128
- Relaterad länk:
-
https://oru.diva-por... (primary) (Raw object)
-
visa fler...
-
http://www.iccbr.org...
-
https://urn.kb.se/re...
-
https://urn.kb.se/re...
-
visa färre...
Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Nyckelord
- Computer Science
- Datavetenskap
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)