Tuesday, 20 October 2015

Smartphone-Based Wound Assessment System For Patients With Diabetes

Diabetic foot ulcers represent a significant health issue. 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 patients and their caregivers 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 smart phones 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 smart phone. The wound image is captured by the camera on the smart phone with the assistance of an image capture box. After that, the smart phone 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.
The aim of this paper is propose a novel wound image analysis system implemented solely on the Android smart phone.
The scope of this paper is tends to show that our system can be efficiently used to analyze the wound healing status with promising accuracy
There are several problems with current practices for treating diabetic foot ulcers. First, patients must go to their wound clinic on a regular basis to have their wounds checked by their clinicians. This need for frequent clinical evaluation is not only inconvenient and time consuming for patients and clinicians, but also represents a significant health care cost because patients may require special transportation, e.g., ambulances. Second, a clinician’s wound assessment process is based on visual examination. He/she describes the wound by its physical dimensions and the color of its tissues, providing important indications of the wound type and the stage of healing. Because 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; specifically the distance regularized level set evolution The principal disadvantage of the level set algorithm is that the iteration of global level set function is too computationally intensive to be implemented on smart phones, even with the narrow band confined implementation based on GPUs. In addition, the level set evolution completely depends on the initial curve which has to be pre-delineated either manually or by a well-designed algorithm. Finally, false edges may interfere with the evolution when the skin color is not uniform enough and when missing boundaries, as frequently occurring in medical images, results in evolution leakage (the level set evolution does not stop properly on the actual wound boundary). Hence, a better method was required to solve these problems.

  1. Patient has to travel with foot ulcers to their clinics to report about the ulcers. This may increase the seriousness of the ulcers instead of curing it.
  2. Patient travel exposure may cause a serious problem for them.

In this paper, replaced the level set algorithms with the efficient mean-shift segmentation algorithm. While it addresses the previous problems, it also creates additional challenges, such as over-segmentation, which we solved using the region adjacency graph (RAG)-based region merge algorithm. Present the entire process of recording and analyzing a wound image, using algorithms that are executable on a smart phone, and provide evidence of the efficiency and accuracy of these algorithms for analyzing diabetic foot ulcers.
  • Patient’s travel exposure is considerably reduced. Also it will reduce the patients stress.
  • Doctor can easily analyze the problem through images and its segmentation. So the proper report can be given to the patient on time



·                Processor          -   Pentium –III

·                Speed                -    1.1 Ghz
·                RAM                 -    256 MB(min)
·                Hard Disk         -   20 GB
·                Floppy Drive    -    1.44 MB
·                Key Board                 -    Standard Windows Keyboard
·                Mouse               -    Two or Three Button Mouse
·                Monitor             -    SVGA


·                Operating System      :Android OS             
·                Front End                  : JAVA
·                Database                  : SqLite
·                Tool                           :Eclipse


Pedersen, P.C. Strong, D.M.  Tulu, B.,Lei Wang ,"SMARTPHONE-BASED WOUND ASSESSMENT SYSTEM FOR PATIENTS WITH DIABETES" , IEEE Transactions on  Biomedical Engineering Volume 62 ,  Issue 2  Feb. 2015

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