Implementation of post-operative wound analytics

Wound infection care after clinical surgery is mostly done by human observation. This type of work not only adds extra work to clinical physician and/or nurses, but is also subjective in nature. Doctors are relying on off-premise post-surgery monitoring mechanism to track the progress of their patients. This paper introduces our scheme to assist doctor in post-operative wound analytics based on smart mobile device, which combines automatic wound detection and infectious status recognition of wound. We integrate color normalization, robust edge detection, and skin color detection for wound detection. Subsequently, wound image is divided into overlapped blocks for infectious status recognition, which employs feature extraction and machine learning. The experiment results demonstrate the proposed scheme has high accuracies in post-operative wound analytics.