Chronic wound tissue characterization under telemedicine framework

Chronic wound (CW) diagnosis is more demanding to monitor the healing process of the wound. However, the availability of specialist medical help in remote/rural areas in developing countries, like India, is a challenge. Further, visiting specially hospitals in city is both expensive and time consuming. This paper discusses the comprehensive CW diagnostic approach using three important modules, namely, wounds data acquisition (WDA), tele-wound technology network (TWTN), and wound screening and diagnostic (WSD) respectively. We have proposed a CW characterization and diagnosis under telemedicine framework to classify the tissue depending on percentage of wound and based on color variation at regular time intervals. The Bayesian classifier based wound characterization (BWC) method is proposed to identify the percentage of tissue with high accuracy. It has been observed that the BWC method provides overall accuracy of 87.11%.