Smartphone-Based Wound Assessment System for Patients with Diabetes

Authors

  • Karthik K  Department of MCA, P.E.S. College of Engineering, Mandya, India
  • Prof. K. M Sowmyashree  Department of MCA, P.E.S. College of Engineering, Mandya, India

Keywords:

Android-Based Smartphone, Mean Shift, Patients With Diabetes, Wound Analysis.

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, amore 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 CenterWound Clinic (Worcester,MA)following an InstitutionalReviewBoard approved protocol show that our system can be efficiently used to analyze the wound healing status with promising accuracy.

References

  1. K. M. Buckley, L. K. Adelson, and J. G. Agazio, "Reducing the risks of wound consultation: Adding digital images to verbal reports," Wound Ostomy Continence Nurs., vol. 36, no. 2, pp. 163-170, Mar. 2009.
  2. V. Falanga, "The chronic wound: Impaired healing and solutions in the context of wound bed preparation," Blood Cells Mol. Dis., vol. 32, no. 1, pp. 88-94, Jan. 2004.
  3. C. T. Hess and R. S. Kirsner, "Orchestrating wound healing: Assessing and preparing the wound bed," J. Adv. Skin Wound Care, vol. 16, no. 5, pp. 246-257, Sep. 2006.
  4. R. S. Rees and N. Bashshur, "The effects of tele wound management on use of service and financial outcomes," Telemed. J. E. Health, vol. 13, no. 6, pp. 663-674, Dec. 2007.
  5. NIH’s National Diabetes Information Clearing House, National Institute of Health. (2011). Online]. Available: www.diabetes.niddk.nih.gov
  6. H. Wannous, Y. Lucas, and S. Treuillet, "Combined machine learning with multi-view modeling for robust wound tissue assessment," in Proc. 5th Int. Conf. Comp. Vis. Theory Appl., May 2010, pp. 98-104.
  7. H.Wannous,Y. Lucas, S. Treuillet, andB.Albouy, "A complete 3Dwound assessment tool for accurate tissue classification and measurement," in Proc. IEEE 15th Conf. Image Process., Oct. 2008, pp. 2928-2931.
  8. P. Plassman and T. D. Jones, "MAVIS: A non-invasive instrument to measure area and volume of wounds," Med. Eng. Phys., vol. 20, no. 5, pp. 332-338, Jul. 1998.
  9. A. Malian, A. Azizi, F. A. Van den Heuvel, and M. Zolfaghari, "Development of a robust photogrammetric metrology system for monitoring the healing of bedscores," Photogrammetric Rec., vol. 20, no. 111, pp. 241-273, Jan. 2005.

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Published

2017-06-30

Issue

Section

Research Articles

How to Cite

[1]
Karthik K, Prof. K. M Sowmyashree, " Smartphone-Based Wound Assessment System for Patients with Diabetes, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 3, pp.905-910, May-June-2017.