A PROFICIENT APPROACH TO DETECT THE THRESHOLD RATE FOR DIABETIC PATIENT USING WOUND HEALING STATUS

“A PROFICIENT APPROACH TO DETECT THE THRESHOLD RATE FOR DIABETIC PATIENT USING WOUND HEALING STATUS” is an approach based on image processing.The physical components of the system consist of an image capture box, a camera for wound image capture and a laptop for analyzing the wound image. The wound image assessment algorithms calculate the overall wound area, color segmented wound areas, and a healing score, to provide a quantitative assessment of the wound healing status both for a single wound image and comparisons of subsequent images to an initial wound image. In the existing work, the visual assessment does not produce objective measurements and quantifiable parameters of the healing status, tracking a wound’s healing process across consecutive visits is a difficult task for both clinicians and patients. The wound boundary determination was done with a particular implementation of the level set algorithm. The entire process of recording and analyzing a wound image, using algorithms that are executable on a camera, and provide evidence of the efficiency and accuracy of these algorithms for analyzing diabetic foot ulcers. Diabetic foot ulcers represent a significant health is- sue. Currently, clinicians and nurses mainly base their wound assessment on visual examination of wound size and healing status, while the patients themselves seldom have an opportunity to play an active role. Hence, a more quantitative and cost-effective examination method that enables the patient and their care givers to take a more active role in daily wound care potentially can accelerate wound healing, save travel cost and reduce healthcare expenses. Considering the prevalence of smartphones with a high-resolution digital camera, assessing wounds by analyzing images of chronic foot ulcers is an attractive option. In this paper, we propose a novel wound image analysis system implemented solely on the Android smartphone. The wound image is captured by the camera on the smartphone with the assistance of an image capture box. After that, the smartphone performs wound segmentation by applying the accelerated mean shift algorithm. Specifically, the outline of the foot is determined based on skin color, and the wound boundary is found using a simple connected region detection method. Within the wound boundary, the healing status is next assessed based on red–yellow–black color evaluation model. Moreover, the healing status is quantitatively assessed, based on trend analysis of time records for a given patient. Experimental results on wound images collected in UMASS—Memorial Health Center Wound Clinic (Worcester, MA) following an Institutional Review Board approved protocol show that our system can be efficiently used to analyze the wound healing status with promising accuracy.