A Lightweight App Distribution Strategy to Generate Interest in Complex Commercial Apps: Case Study of an Automated Wound Measurement System

Tang, Min; Gary, Kevin; Güler, Özgür; Cheng, Patrick

doi:10.24251/hicss.2017.418

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…The most similar studies to our work found in the literature are [25,26,31,33]. However, we have made it possible for three types of users to use the mobile application and for patients to provide feedback to healthcare professionals.…”

Section: Discussionmentioning

confidence: 56%

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Experimental Study on Wound Area Measurement with Mobile Devices

Ferreira

Pires

Ponciano

et al. 2021

Sensors

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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.

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Section: Discussionmentioning

confidence: 56%

“…The authors of [33] implemented a scaling method for measuring the wound size by placing a rectangular box in the image with a mobile device.…”

Section: Informed Consent Statement: Not Applicablementioning

confidence: 99%

Experimental Study on Wound Area Measurement with Mobile Devices

Ferreira

Pires

Ponciano

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Tang et al [42] used a scaling method to measure chronic wounds' sizes with a mobile device, reporting reliable results. The scaling method included calculating the approximate size of an injury and inserting and adjusting a rectangular box in the image.…”

Section: Resultsmentioning

confidence: 99%

A Systematic Investigation of Models for Color Image Processing in Wound Size Estimation

et al. 2021

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In recent years, research in tracking and assessing wound severity using computerized image processing has increased. With the emergence of mobile devices, powerful functionalities and processing capabilities have provided multiple non-invasive wound evaluation opportunities in both clinical and non-clinical settings. With current imaging technologies, objective and reliable techniques provide qualitative information that can be further processed to provide quantitative information on the size, structure, and color characteristics of wounds. These efficient image analysis algorithms help determine the injury features and the progress of healing in a short time. This paper presents a systematic investigation of articles that specifically address the measurement of wounds’ sizes with image processing techniques, promoting the connection between computer science and health. Of the 208 studies identified by searching electronic databases, 20 were included in the review. From the perspective of image processing color models, the most dominant model was the hue, saturation, and value (HSV) color space. We proposed that a method for measuring the wound area must implement different stages, including conversion to grayscale for further implementation of the threshold and a segmentation method to measure the wound area as the number of pixels for further conversion to metric units. Regarding devices, mobile technology is shown to have reached the level of reliable accuracy.

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