Please use this identifier to cite or link to this item:
Title: Excluding Indecisive Decisions by Bringing Machine Learning and Sensor Fusion Together in Wound Management
Authors: LEMMENS, Marijn 
THOELEN, Ronald 
De Raedt, Walter
Issue Date: 2017
Source: Med-e-Tel, International Society for Telemedicine & eHealth (ISfTeH), Luxembourg City, Luxembourg, 05-07/04/2017
Abstract: Monitoring and analysing of chronic woundsis still primarily based on visual inspections and interpretations of medical professionals. By maintaining this method, there is a chance of misinterpretation due to diverse ways of examining the wound. Further, for each assessment thewound dressing needs to be removed, which results into an intermission of the healing process. The Bioelectrical Impedance Spectroscopy (BIS)technique is tested to observe differences in the wound itself over time. By using Electrical Impedance Tomography (EIT) it is possible to detect variations in conductivity solely based on impedance measurements. Features from this digital image are extracted and fed into a machine learningalgorithm.The output from this gives a detailed feedback of the healing state of a wound and this information in turn can be used to alter the conditions in which a wound is healing so an optimal state of healing can be realized.
Document URI:
Category: C2
Type: Conference Material
Appears in Collections:Research publications

Files in This Item:
File Description SizeFormat 
  Restricted Access
N/A3.82 MBMicrosoft PowerpointView/Open    Request a copy
Show full item record

Page view(s)

checked on May 27, 2022

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.