Towards Non-invasive Patient Monitoring Through Iris Tracking and Pain Detection

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 non-invasive 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.