Abstract
Psoriasis is a chronic inflammatory skin disease with a high worldwide incidence that in worst cases reaches 4.6%. This dermatosis can be associated with other comorbidities and has a significant negative impact on labor productivity and the quality of life of affected people. During day-to-day lives, psoriasis patients come across several practical clinical difficulties, e.g. to i) easily register a time evolution of affected skin areas (for later analysis by health carers); ii) daily evaluate the size of each affected skin area, to be able to iii) calculate the amount of medication to be applied on those affected body areas. In such a context, this paper proposes the Follow-App mobile system aiming to support people with psoriasis, by alleviating and managing their daily life with the disease. More precisely, the goals of the system are: to allow individual photographic registration of body parts affected by psoriasis; in addition, cataloging each image according to its body segment location and sampling date; then, on those photos, automatically detect and segment the affected skin surface, to posteriorly be able to calculate the area of the lesions; finally, based on the area and prescribed medicine, dynamically accounting the amount of topical medicine to use. These were the requirements addressed by the proposed system prototype. The evaluation tests on the ability to detect and quantify the area of the skin lesions were performed on a data-set with 22 images. The proposed segmentation algorithm for detecting the area of redness lesions reached an IoU rate over 81%. Therefore, the proposed Follow-App mobile system may become an important asset for people with psoriasis since the extent and redness of affected areas are major evaluation factors for the disease severity.
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Acknowledgements
This project was funded by Fundação Ensino e Cultura Fernando Pessoa (FECFP), represented here by its R&D group Intelligent Sensing and Ubiquitous Systems (ISUS: http://isus.ufp.pt).
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Moreira, R.S. et al. (2021). Mobile System for Personal Support to Psoriatic Patients. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies . WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1367. Springer, Cham. https://doi.org/10.1007/978-3-030-72660-7_46
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