Applications of angiosome classification model for monitoring disease progression in the diabetic feet

Manish Bharara, Erin Boulger, Gurtej Singh Grewal, Jeffrey N. Schoess, David G. Armstrong

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

"Every 20 seconds there is a diabetes related amputation somewhere in the world". Diabetes affects 382 million people in the world today and by 2035, at least 592 million people will have diabetes-approximately 10% of the world's adult population. One of the most sinister complications of diabetes is peripheral neuropathy, where patients loose the gift of pain in their feet. Presently, clinicians assess circulation, neuropathy, and plantar pressures to identify the risk of foot ulceration that when get infected lead to amputations. The key common factor that appears to be present both in dysfunctional healing and in predicting breakdown may be inflammation. Inflammation is a central unifying concept of medicine spanning across the spectrum of pathologies from a simple bruise to cancer. For a diabetic wound, uncontrolled inflammation produces staggering impact for the patients as well as the healthcare system. Currently, there are no objective means of measuring wound inflammation and surprisingly the status quo is 'measurements of temperatures using back of the hand'. This paper presents a conceptual methodology for classification of thermograms based on the angiosomes of the feet.

Original languageEnglish (US)
Pages (from-to)241-245
Number of pages5
JournalSimulation Series
Volume46
Issue number10
StatePublished - Jan 1 2014
EventSummer Computer Simulation Conference, SCSC 2014, Part of the 2014 Summer Simulation Multiconference, SummerSim 2014 - Monterey, United States
Duration: Jul 6 2014Jul 10 2014

Keywords

  • Angiogenesis
  • Angiosomes
  • Diabetic Foot
  • Inflammation
  • Thermography

ASJC Scopus subject areas

  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Applications of angiosome classification model for monitoring disease progression in the diabetic feet'. Together they form a unique fingerprint.

Cite this