• DocumentCode
    74465
  • Title

    Smartphone-Based Wound Assessment System for Patients With Diabetes

  • Author

    Lei Wang ; Pedersen, Peder C. ; Strong, Diane M. ; Tulu, Bengisu ; Agu, Emmanuel ; Ignotz, Ronald

  • Author_Institution
    Electr. & Comput. Eng. Dept., Worcester Polytech. Inst., Worcester, MA, USA
  • Volume
    62
  • Issue
    2
  • fYear
    2015
  • fDate
    Feb. 2015
  • Firstpage
    477
  • Lastpage
    488
  • Abstract
    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 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.
  • Keywords
    biomedical communication; biomedical optical imaging; diseases; health care; image colour analysis; image segmentation; medical image processing; patient care; skin; smart phones; wounds; Android smartphone; Institutional Review Board approved protocol; UMASS-Memorial Health Center Wound Clinic; accelerated mean-shift algorithm; caregivers; chronic foot ulcers; cost-effective examination method; daily wound care; diabetic foot ulcers; foot outline; health issue; healthcare expense reduction; high-resolution digital camera; image capture box; patient; quantitative examination method; red-yellow-black color evaluation model; simple connected region detection method; skin color; smartphone-based wound assessment system; trend analysis; visual examination; wound boundary; wound healing status; wound image analysis system; wound segmentation; wound size; Algorithm design and analysis; Diabetes; Foot; Image color analysis; Image segmentation; Vectors; Wounds; Android-based smartphone; mean shift; patients with diabetes; wound analysis;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2014.2358632
  • Filename
    6901243