2022
Authors
Caruso, BC; Stenstkie, C; van Duivenboden, D; Starosta, J; Hoernschemeyer, J; Peytard, S; Malheiro, B; Ribeiro, C; Justo, J; Silva, MF; Ferreira, P; Guedes, P;
Publication
MOBILITY FOR SMART CITIES AND REGIONAL DEVELOPMENT - CHALLENGES FOR HIGHER EDUCATION, VOL 1
Abstract
This paper reports the development of WalkSafe, a Smart Pedestrian Crossing solution, by a multinational and multidisciplinary team of students during the spring semester of 2020. The team was enrolled in the European Project Semester (EPS), a project-based capstone programme offered by Instituto Superior de Engenharia do Porto (ISEP). Motivated by the idea to reduce the number of pedestrians hit by cars at road crossings, and associated injuries and deaths, the team surveyed pedestrian behaviour to conclude that people often ignore pedestrian crossings. Thus, this project intended to motivate people to use pedestrian crossings, increasing the safety of both pedestrians and drivers. The proposed solution can be implemented on any pedestrian crossing and involves up to three components: (i) a box to be fixed on each side of pedestrian crossings with a radio-frequency identification reader as well as Bluetooth and Wi-Fi interfaces; (ii) a smartphone mobile app; and (iii) a personal bracelet for children and elderly, with a passive radio-frequency identification tag.
2022
Authors
Costa, T; Coelho, L; Silva, MF;
Publication
BIOENGINEERING-BASEL
Abstract
Diabetic peripheral neuropathy is a major complication of diabetes mellitus, and it is the leading cause of foot ulceration and amputations. The Semmes-Weinstein monofilament examination (SWME) is a widely used, low-cost, evidence-based tool for predicting the prognosis of diabetic foot patients. The examination can be quick, but due to the high prevalence of the disease, many healthcare professionals can be assigned to this task several days per month. In an ongoing project, it is our objective to minimize the intervention of humans in the SWME by using an automated testing system relying on computer vision. In this paper we present the project's first part, constituting a system for automatically identifying the SWME testing sites from digital images. For this, we have created a database of plantar images and developed a segmentation system, based on image processing and deep learning-both of which are novelties. From the 9 testing sites, the system was able to correctly identify most 8 in more than 80% of the images, and 3 of the testing sites were correctly identified in more than 97.8% of the images.
2022
Authors
Duarte, AJ; Malheiro, B; Silva, MF; Ferreira, PD; Guedes, PB;
Publication
Handbook of Research on Improving Engineering Education with the European Project Semester - Advances in Higher Education and Professional Development
Abstract
2022
Authors
Silva, MF; Duarte, AJ; Ferreira, PD; Guedes, PB;
Publication
Handbook of Research on Improving Engineering Education with the European Project Semester - Advances in Higher Education and Professional Development
Abstract
2022
Authors
Chugo, D; Tokhi, MO; Silva, MF; Nakamura, T; Goher, K;
Publication
Lecture Notes in Networks and Systems
Abstract
2022
Authors
Ferreira, P; Malheiro, B; Silva, M; Borges Guedes, P; Justo, J; Ribeiro, C; Duarte, A;
Publication
EDULEARN Proceedings - EDULEARN22 Proceedings
Abstract
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