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Tools and Components of Wound Healing Assessment

[+] Author Affiliations
Jessica Chin, Ibrahim Zeid, Sagar Kamarthi

Northeastern University, Boston, MA

Paper No. DETC2013-13270, pp. V004T05A027; 9 pages
  • ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 4: 18th Design for Manufacturing and the Life Cycle Conference; 2013 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications
  • Portland, Oregon, USA, August 4–7, 2013
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5591-1
  • Copyright © 2013 by ASME


Chronic wound assessment and analysis has long been a major healthcare issue. Chronic wound management and treatment cost billions of dollars each year. The research to alleviate the burden of non-healing wounds and predicting when they will heal is progressing at incremental pace. Characteristics of a chronic wound are unique to both the patient and wound itself. Like a fingerprint, each wound has a unique set of properties that tell a story about its health and viability. Although each person’s wound is individual, there are a few underlying pathologies that are common amongst all wounds. For example, all wounds have a definite surface area, depth, and temperature at any given time. By knowing these common characteristics across all wounds, we can use both historical data and collected data to determine wound healing patterns and wound healing rates. The purpose of this study is to develop an algorithm that uses photography and statistical modeling to predict an approximate wound healing rate for lower appendage wounds. We focus on lower appendage wounds with a depth of 1–2 mm because lower appendage wounds account for approximately 70% of wounds seen at wound clinics.

Copyright © 2013 by ASME



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