Experimental Study on Wound Area Measurement with Mobile Devices

Healthcare treatments might benefit from advances in artificial intelligence and technological equipment such as smartphones and smartwatches. The presence of cameras in these devices with increasingly robust and precise pattern recognition techniques can facilitate the estimation of the wound area...

Full description

Bibliographic Details
Main Authors: Filipe Ferreira, Ivan Miguel Pires, Vasco Ponciano, Mónica Costa, María Vanessa Villasana, Nuno M. Garcia, Eftim Zdravevski, Petre Lameski, Ivan Chorbev, Martin Mihajlov, Vladimir Trajkovik
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/21/17/5762
id doaj-81e335c971ca4f86b88dbdd1e07018d4
record_format Article
spelling doaj-81e335c971ca4f86b88dbdd1e07018d42021-09-09T13:56:07ZengMDPI AGSensors1424-82202021-08-01215762576210.3390/s21175762Experimental Study on Wound Area Measurement with Mobile DevicesFilipe Ferreira0Ivan Miguel Pires1Vasco Ponciano2Mónica Costa3María Vanessa Villasana4Nuno M. Garcia5Eftim Zdravevski6Petre Lameski7Ivan Chorbev8Martin Mihajlov9Vladimir Trajkovik10R&D Unit in Digital Services, Applications, and Content, Polytechnic Institute of Castelo Branco, 6000-767 Castelo Branco, PortugalInstituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, PortugalR&D Unit in Digital Services, Applications, and Content, Polytechnic Institute of Castelo Branco, 6000-767 Castelo Branco, PortugalR&D Unit in Digital Services, Applications, and Content, Polytechnic Institute of Castelo Branco, 6000-767 Castelo Branco, PortugalCentro Hospitalar do Baixo Vouga, 3810-164 Aveiro, PortugalInstituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, PortugalFaculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North MacedoniaFaculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North MacedoniaFaculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North MacedoniaLaboratory for Open Systems and Networks, Jozef Stefan Institute, 1000 Ljubljana, SloveniaFaculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North MacedoniaHealthcare treatments might benefit from advances in artificial intelligence and technological equipment such as smartphones and smartwatches. The presence of cameras in these devices with increasingly robust and precise pattern recognition techniques can facilitate the estimation of the wound area and other telemedicine measurements. Currently, telemedicine is vital to the maintenance of the quality of the treatments remotely. This study proposes a method for measuring the wound area with mobile devices. The proposed approach relies on a multi-step process consisting of image capture, conversion to grayscale, blurring, application of a threshold with segmentation, identification of the wound part, dilation and erosion of the detected wound section, identification of accurate data related to the image, and measurement of the wound area. The proposed method was implemented with the OpenCV framework. Thus, it is a solution for healthcare systems by which to investigate and treat people with skin-related diseases. The proof-of-concept was performed with a static dataset of camera images on a desktop computer. After we validated the approach’s feasibility, we implemented the method in a mobile application that allows for communication between patients, caregivers, and healthcare professionals.https://www.mdpi.com/1424-8220/21/17/5762wound area measurementmobile applicationsegmentationthresholdimage processing techniques
collection DOAJ
language English
format Article
sources DOAJ
author Filipe Ferreira
Ivan Miguel Pires
Vasco Ponciano
Mónica Costa
María Vanessa Villasana
Nuno M. Garcia
Eftim Zdravevski
Petre Lameski
Ivan Chorbev
Martin Mihajlov
Vladimir Trajkovik
spellingShingle Filipe Ferreira
Ivan Miguel Pires
Vasco Ponciano
Mónica Costa
María Vanessa Villasana
Nuno M. Garcia
Eftim Zdravevski
Petre Lameski
Ivan Chorbev
Martin Mihajlov
Vladimir Trajkovik
Experimental Study on Wound Area Measurement with Mobile Devices
Sensors
wound area measurement
mobile application
segmentation
threshold
image processing techniques
author_facet Filipe Ferreira
Ivan Miguel Pires
Vasco Ponciano
Mónica Costa
María Vanessa Villasana
Nuno M. Garcia
Eftim Zdravevski
Petre Lameski
Ivan Chorbev
Martin Mihajlov
Vladimir Trajkovik
author_sort Filipe Ferreira
title Experimental Study on Wound Area Measurement with Mobile Devices
title_short Experimental Study on Wound Area Measurement with Mobile Devices
title_full Experimental Study on Wound Area Measurement with Mobile Devices
title_fullStr Experimental Study on Wound Area Measurement with Mobile Devices
title_full_unstemmed Experimental Study on Wound Area Measurement with Mobile Devices
title_sort experimental study on wound area measurement with mobile devices
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2021-08-01
description Healthcare treatments might benefit from advances in artificial intelligence and technological equipment such as smartphones and smartwatches. The presence of cameras in these devices with increasingly robust and precise pattern recognition techniques can facilitate the estimation of the wound area and other telemedicine measurements. Currently, telemedicine is vital to the maintenance of the quality of the treatments remotely. This study proposes a method for measuring the wound area with mobile devices. The proposed approach relies on a multi-step process consisting of image capture, conversion to grayscale, blurring, application of a threshold with segmentation, identification of the wound part, dilation and erosion of the detected wound section, identification of accurate data related to the image, and measurement of the wound area. The proposed method was implemented with the OpenCV framework. Thus, it is a solution for healthcare systems by which to investigate and treat people with skin-related diseases. The proof-of-concept was performed with a static dataset of camera images on a desktop computer. After we validated the approach’s feasibility, we implemented the method in a mobile application that allows for communication between patients, caregivers, and healthcare professionals.
topic wound area measurement
mobile application
segmentation
threshold
image processing techniques
url https://www.mdpi.com/1424-8220/21/17/5762
work_keys_str_mv AT filipeferreira experimentalstudyonwoundareameasurementwithmobiledevices
AT ivanmiguelpires experimentalstudyonwoundareameasurementwithmobiledevices
AT vascoponciano experimentalstudyonwoundareameasurementwithmobiledevices
AT monicacosta experimentalstudyonwoundareameasurementwithmobiledevices
AT mariavanessavillasana experimentalstudyonwoundareameasurementwithmobiledevices
AT nunomgarcia experimentalstudyonwoundareameasurementwithmobiledevices
AT eftimzdravevski experimentalstudyonwoundareameasurementwithmobiledevices
AT petrelameski experimentalstudyonwoundareameasurementwithmobiledevices
AT ivanchorbev experimentalstudyonwoundareameasurementwithmobiledevices
AT martinmihajlov experimentalstudyonwoundareameasurementwithmobiledevices
AT vladimirtrajkovik experimentalstudyonwoundareameasurementwithmobiledevices
_version_ 1717759421489086464