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Title: Towards non-invasive patient monitoring through iris tracking and pain detection
Authors: Michael, Georges 
Tsaparellas, K. 
Panis, Gabriel 
Loizou,  Christos P. 
Lanitis, Andreas 
Keywords: Iris tracking;Pain detection;Patient monitoring;Texture video analysis
Category: Electrical Engineering - Electronic Engineering - Information Engineering;Medical Engineering;Clinical Medicine;Health Sciences
Field: Engineering and Technology;Medical and Health Sciences
Issue Date: 1-Jan-2016
Publisher: Springer-Verlag
Source: 14th Mediterranean Conference on Medical and Biological Engineering and Computing, MEDICON 2016, Paphos, Cyprus, 31 March 2016 through 2 April 2016
Conference: Mediterranean Conference on Medical and Biological Engineering and Computing 
Abstract: Patient monitoring is an important operation taking place in hospitals. It usually involves the use of dedicated invasive equipment that requires the co-operation of patients and also involves remarkable purchase and maintenance costs. In this paper we describe a feasibility study of using image analysis techniques for implementing a low-cost noninvasive patient monitoring system based on iris tracking and pain detection in image sequences captured with ordinary video cameras. Within this context iris tracking can be used for activity monitoring and also as a means for communication in cases where body movement is disabled. Automatic pain detection can be used for detecting increasing pain levels and automatically request help for the patient. As part of our preliminary investigation pain detection is achieved based on a number of texture features extracted from the shape normalized facial regions in image sequences. Iris tracking is carried out by a method based on circular edge detection and isophote curves. The initial results of our study prove the feasibility of the approach as the basis of implementing a complete non-invasive patient monitoring system. Further validation and work in a larger sample of videos is required for further validating the proposed method.
ISBN: 978-331932701-3
DOI: 10.1007/978-3-319-32703-7_71
Rights: © Springer International Publishing Switzerland 2016.
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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