2020
Authors
Bessa, D; Rodrigues, NF; Oliveira, E; Kolbenschag, J; Prahm, C;
Publication
2020 IEEE 8th International Conference on Serious Games and Applications for Health, SeGAH 2020
Abstract
As an amputee, learning how to control a myoelectric prosthesis is a difficult task. One of the main issues with conventional, highly repetitive, rehabilitation methods is the lack of engagement and motivation of the patients that often leads to high rejection rates of the prosthetic device. This work proposes and implements a novel serious game design, improving previous work, as music-based app. The prototype was evaluated by seven able-bodied participants with regard system usability and engagement. Results suggest positive outcomes in motivation, but room for improvement in system usability. © 2020 IEEE.
2020
Authors
Pacheco, P; Santos, F; Coimbra, J; Oliveira, E; Rodrigues, NF;
Publication
2020 IEEE 8th International Conference on Serious Games and Applications for Health, SeGAH 2020
Abstract
Emergency department crowding has been steadily increasing, with a significant part due to non-emergent pathologies. We developed a self-service kiosk to be used by patients while waiting from triage to treatment room allocation, which collects clinical history, usual medication, main complaint and, also collects vital signs. This information is processed and presented in a comprehensive way to the medical staff in order to accelerate diagnostics and treatment selection. This work describes and analyzes the results of the usability evaluation of this kiosk, taking into account the average time per screen, the average time of a complete kiosk session, the application design and the user interaction with devices and the system. The kiosk was tested in several environments with different types of users, allowing the identification of causes of problems and difficulties experienced, as well as solutions to improve the solution. © 2020 IEEE.
2020
Authors
Pacheco, P; Santos, F; Coimbra, J; Oliveira, E; Rodrigues, NF;
Publication
2020 IEEE 8TH INTERNATIONAL CONFERENCE ON SERIOUS GAMES AND APPLICATIONS FOR HEALTH (SEGAH 20)
Abstract
Emergency department crowding has been steadily increasing, with a significant part due to non-emergent pathologies. We developed a self-service kiosk to be used by patients while waiting from triage to treatment room allocation, which collects clinical history, usual medication, main complaint and, also collects vital signs. This information is processed and presented in a comprehensive way to the medical staff in order to accelerate diagnostics and treatment selection. This work describes and analyzes the results of the usability evaluation of this kiosk, taking into account the average time per screen, the average time of a complete kiosk session, the application design and the user interaction with devices and the system. The kiosk was tested in several environments with different types of users, allowing the identification of causes of problems and difficulties experienced, as well as solutions to improve the solution.
2020
Authors
Madureira, AM; Abraham, A; Gandhi, N; Silva, C; Antunes, M;
Publication
SoCPaR
Abstract
2020
Authors
Reis, P; Santos, AS; Bastos, JA; Madureira, AM; Varela, LR;
Publication
Intelligent Systems Design and Applications - 20th International Conference on Intelligent Systems Design and Applications (ISDA 2020) held December 12-15, 2020
Abstract
2020
Authors
Braga, D; Madureira, A;
Publication
International Journal of Computer Information Systems and Industrial Management Applications
Abstract
The rapid expansion of Asian hornets poses a high threat for the honey bee survival, as these invaders pray on them. Furthermore, they also pose a threat to people who are allergic, whose sting can lead to death. This study proposes a Decision Support System that uses Computer Vision techniques to automatically detect signs of Vespa velutina through images from GPS equipped camera. The goal of the system is to provide timely information about the presence of these invaders, allowing park managers and beekeepers to act quickly in removing the Vespidae. The proposed methodology obtained an 85% accuracy in the detection of V. velutina using the Mask RCNN architecture, enabling the system to perform detection at 3 FPS. © 2020 MIR Labs.
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.