Experimental Study on Wound Area Measurement with Mobile Devices
Journal
Sensors
Date Issued
2021-08-26
Author(s)
Ferreira, Filipe
Pires, Ivan Miguel
Ponciano, Vasco
Costa, Mónica
Villasana, María Vanessa
Garcia, Nuno M
Abstract
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.
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.
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