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Publicações

Publicações por HumanISE

2014

Designing Players' Emotional Reaction Models: A Generic Method Towards Adaptive Affective Gaming

Autores
Nogueira, PA; Aguiar, R; Rodrigues, R; Oliveira, E;

Publicação
PROCEEDINGS OF THE 2014 9TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI 2014)

Abstract
Current approaches to game design improvements rely on gameplay testing, an iterative process following the test, try and fix pattern, relying on target audience feedback via standard questionnaires. Besides being a very time consuming phase, it is also highly subjective. In this paper, we demonstrate a generalizable approach for building predictive models of players' affective reactions across games and genres. Our aim is two-fold: 1) That game developers can use these models to more easily and accurately tune game parameters, allowing improved gaming experiences, and 2) That these models can be used as the basis for parameterisable and adaptive affective gaming. This paper describes our preliminary results regarding a novel, physiological-based method for emotional player profiling, which consists on the following three phases: (i) monitoring players' emotional states and game events, (ii) identifying player's emotional reactions to game events and (iii) individual and cluster-based modelling of players emotional reactions.

2014

Fuzzy Affective Player Models: A Physiology-Based Hierarchical Clustering Method

Autores
Nogueira, PA; Aguiar, R; Rodrigues, R; Oliveira, EC; Nacke, LE;

Publicação
AIIDE

Abstract
Current approaches to game design improvements rely on time-consuming gameplay testing processes, which rely on highly subjective feedback from a target audience. In this paper, we propose a generalizable approach for building predictive models of players' emotional reactions across different games and game genres, as well as other forms of digital stimuli. Our input agnostic approach relies on the following steps: (a) collecting players' physiologically-inferred emotional states during actual gameplay sessions, (b) extrapolating the causal relations between changes in players' emotional states and recorded game events, and (c) building hierarchical cluster models of players' emotional reactions that can later be used to infer individual player models via fuzzy cluster membership vectors. We expect this work to benefit game designers by accelerating the affective playtesting process through the offline simulation of players' reactions to game design adaptations, as well as to contribute towards individually-tailored affective gaming.

2014

Testing Advanced Driver Assistance Systems with a serious-game-based human factors analysis suite

Autores
Gonçalves, JSV; Rossetti, RJF; Neto Jacob, JTP; Gonçalves, J; Monreal, CO; Coelho, A; Rodrigues, R;

Publicação
Intelligent Vehicles Symposium

Abstract

2014

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Autores
Rodrigues, PL; Moreire, AHJ; Rodrigues, NF; Pinho, ACM; Fonseca, JC; Correia Pinto, J; Vilaca, JL;

Publicação
MEDICAL IMAGING 2014: COMPUTER-AIDED DIAGNOSIS

Abstract
Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82 +/- 5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7 +/- 4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.

2014

An electromagnetic tracker system for the design of a dental superstructure

Autores
Moreira, AHJ; Queiros, S; Rodrigues, NF; Pinho, ACM; Fonseca, JC; Vilaca, JL;

Publicação
Biodental Engineering III - Proceedings of the 3rd International Conference on Biodental Engineering, BIODENTAL 2014

Abstract
Nowadays, different techniques are available for manufacturing full-arch implantsupported prosthesis, many of them based on an impression procedure. Nevertheless, the long-term success of the prosthesis is highly influenced by the accuracy during such process, being affected by factors such as the impression material, implant position, angulation and depth. This paper investigates the feasibility of a 3D electromagnetic motion tracking system as an acquisition method for modeling such prosthesis. To this extent, we propose an implant acquisition method at the patient mouth, using a specific prototyped tool coupled with a tracker sensor, and a set of calibration procedures (for distortion correction and tool calibration), that ultimately obtains combined measurements of the implant's position and angulation, and eliminating the use of any impression material. However, in the particular case of the evaluated tracking system, the order of magnitude of the obtained errors invalidates its use for this specific application. © 2014 Taylor & Francis Group.

2014

Preliminary clinical trial in percutaneous nephrolithotomy using a real-time navigation system for percutaneous kidney access

Autores
Rodrigues, PL; Moreira, AHJ; Rodrigues, NF; Pinho, ACM; Fonseca, JC; Lima, E; Vilaca, JL;

Publicação
MEDICAL IMAGING 2014: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING

Abstract
Background: Precise needle puncture of renal calyces is a challenging and essential step for successful percutaneous nephrolithotomy. This work tests and evaluates, through a clinical trial, a real-time navigation system to plan and guide percutaneous kidney puncture. Methods: A novel system, entitled i3DPuncture, was developed to aid surgeons in establishing the desired puncture site and the best virtual puncture trajectory, by gathering and processing data from a tracked needle with optical passive markers. In order to navigate and superimpose the needle to a preoperative volume, the patient, 3D image data and tracker system were previously registered intraoperatively using seven points that were strategically chosen based on rigid bone structures and nearby kidney area. In addition, relevant anatomical structures for surgical navigation were automatically segmented using a multi-organ segmentation algorithm that clusters volumes based on statistical properties and minimum description length criterion. For each cluster, a rendering transfer function enhanced the visualization of different organs and surrounding tissues. Results: One puncture attempt was sufficient to achieve a successful kidney puncture. The puncture took 265 seconds, and 32 seconds were necessary to plan the puncture trajectory. The virtual puncture path was followed correctively until the needle tip reached the desired kidney calyceal. Conclusions: This new solution provided spatial information regarding the needle inside the body and the possibility to visualize surrounding organs. It may offer a promising and innovative solution for percutaneous punctures.

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