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- Blueeyes : easing the navigation and orientation of blind peoplePublication . Silva, Marta; Gomes, Anabela; Teixeira, Ana; Orvalho, JoaoAs reported by the World Health Organization (WHO), of the 7 billion people alive today, an estimated 253 million live with visual impairment that cannot be corrected with glasses or contact lenses. From these, 30 million blind or partially sighted persons live in Europe. Over the past years, blindness that is caused by diseases has decreased due to the success of public health actions. However, the number of blind people that are over 60 years old is increasing by 2 million per decade. Unfortunately, all these numbers are estimated to be doubled by 2020. With these facts, is necessary to bring awareness and understanding of the challenges blind people face and help to motivate research into new technology to answer those questions. This document starts to identify the challenges people with visual disabilities face in their life. The problem of navigation and orientation as well the different possibilities to deal with the locomotion situation is also addressed in this paper. It describes the traditional navigational solutions as well other which involves more sophisticated technological devices and their multimodal interfaces. The paper ends with the description of the BlueEyes project (Orvalho, 2016), consisting in a solution to help blind people moving in a city. The first phases of the project are described, and the actual research situations is also slightly explained.
- KPCA denoising and the pre-image problem revisitedPublication . Teixeira, Ana; Tomé, A.M.; Stadlthanner, K.; Lang, E.W.Kernel principal component analysis (KPCA) is widely used in classification, feature extraction and denoising applications. In the latter it is unavoidable to deal with the pre-image problem which constitutes the most complex step in the whole processing chain. One of the methods to tackle this problem is an iterative solution based on a fixed-point algorithm. An alternative strategy considers an algebraic approach that relies on the solution of an under-determined system of equations. In this work we present a method that uses this algebraic approach to estimate a good starting point to the fixed-point iteration. We will demonstrate that this hybrid solution for the pre-image shows better performance than the other two methods. Further we extend the applicability of KPCA to one-dimensional signals which occur in many signal processing applications. We show that artefact removal from such data can be treated on the same footing as denoising. We finally apply the algorithm to denoise the famous USPS data set and to extract EOG interferences from single channel EEG recordings.
- Usability evaluation of playstation move motion controlerPublication . Teixeira, Ana; Assena, André; Santos, André; Moura, Mariana; Gomes, Nuno; Orvalho, JoaoThe several known studies of usability in videogames describe the elements contributing to the immersion and satisfaction in the videogame playing experience, as well as the importance of tests that secure the good performance of elements such as interface, graphics, sound, history, gameplay and replayability. This paper demonstrates an evaluation of the user´s interaction with the Playstation Move motion controller through usability tests. The goal is to understand the overall usability, the influence of environmental conditions and the use of two controllers simultaneously. This study will also contribute to the understanding of how important it is to use simultaneous but different methodologies, namely questionnaires, heuristic evaluations and direct observation of the users. It was concluded that different light conditions do not affect the use of the controllers, the accuracy and ergonomics are very good, but the button layout is not ideal. The controller´s calibration is time consuming but afterwards the acquisition is almost immediate.
- Age and gender effects in european portuguese spontaneous speechPublication . Albuquerque, Luciana; Valente, Ana Rita; Teixeira, Ana; Oliveira, Catarina; Figueiredo, DanielaAging is part of the normal evolution of human beings. However, the knowledge about speech in the older ages is still dispersed and incomplete. Considering conflicting findings reported in prior research, this study aims to contribute to increase our knowledge about age effects on the spontaneous speech of Portuguese adults. In order to analyze the effects of age on rhythmic, intonation and voice quality domains, several parameters were extracted from spontaneous speech produced by 112 adults, aged between 35 and 97. Data were obtained through a picture description task. The results showed that the most consistent age-related effects are an increase in speech pauses, mainly in men, and a Harmonics-to-Noise Ratio (HNR) decrease in women. Speaking fundamental fre-quency (f0) tends to decrease in women and to slightly increase in men with age. These findings for Portuguese are in line with previous research suggesting that suprasegmental characteristics of speech change with age, with some gender differences.
- Clustering evoked potential signals using subspace methodsPublication . Tomé, A. M.; Teixeira, Ana; Figueiredo, N.; Georgieva, P.; Santos, I.M.; Lang, E.This work proposes a clustering technique to analyze evoked potential signals. The proposed method uses an orthogonal subspace model to enhance the single-trial signals of a session and simultaneously a subspace measure to group the trials into clusters. The ensemble averages of the signals of the different clusters are compared with ensemble averages of visually selected trials which are free of any artifact. Preliminary results consider recordings from an occipital channel where evoked response P100 wave is most pronounced.
- Nonlinear projective techniques to extract artifacts in biomedical signalsPublication . Teixeira, Ana; Tomé, A. M.; Stadlthanner, K.; Lang, E. W.Biomedical signals are generally contaminated with artifacts and noise. In case the artifacts dominate, the useful signal can easily be extracted with projective subspace techniques. Then, biomedical signals which often represent one dimensional time series, need to be transformed to multidimensional signal vectors for the latter techniques to be applicable. The transformation can be achieved by embedding an observed signal in its delayed coordinates. Using this embedding we propose to cluster the resulting feature vectors and apply a singular spectrum analysis (SSA) locally in each cluster to recover the undistorted signals. We also compare the reconstructed signals to results obtained with kernel-PCA. Both nonlinear subspace projection techniques are applied to artificial data to demonstrate the suppression of random noise signals as well as to an electroencephalogram (EEG) signal recorded in the frontal channel to extract its prominent electrooculogram (EOG) interference.
- How to apply nonlinear subspace techniques to univariate biomedical tim e seriesPublication . Teixeira, Ana; Tomé, A. M.; Böhm, M.; Puntonet, Carlos G.; Lang, Elmar W.In this paper, we propose an embedding technique for univariate single-channel biomedical signals to apply projective subspace techniques. Biomedical signals are often recorded as 1-D time series; hence, they need to be transformed to multidimensional signal vectors for subspace techniques to be applicable. The transformation can be achieved by embedding an observed signal in its delayed coordinates. We propose the application of two nonlinear subspace techniques to embedded multidimensional signals and discuss their relation. The techniques consist of modified versions of singular-spectrum analysis (SSA) and kernel principal component analysis (KPCA). For illustrative purposes, both nonlinear subspace projection techniques are applied to an electroencephalogram (EEG) signal recorded in the frontal channel to extract its dominant electrooculogram (EOG) interference. Furthermore, to evaluate the performance of the algorithms, an experimental study with artificially mixed signals is presented and discussed.
- Subspace techniques to remove artifacts from EEG: A quantitative analysisPublication . Teixeira, Ana; Tome, A. M.; Lang, E. W.; Martins da Silva, A.In this work we discuss and apply projective subspace techniques to both multichannel as well as single channel recordings. The single-channel approach is based on singular spectrum analysis(SSA) and the multichannel approach uses the extended infomax algorithm which is implemented in the opensource toolbox EEGLAB. Both approaches will be evaluated using artificial mixtures of a set of selected EEG signals. The latter were selected visually to contain as the dominant activity one of the characteristic bands of an electroencephalogram (EEG). The evaluation is performed both in the time and frequency domain by using correlation coefficients and coherence function, respectively.
- On the Use of KPCA to Extract Artifacts in One-Dimensional Biomedical SignalsPublication . Teixeira, Ana; Tome, A.; Lang, E.; Schachtner, R.; Stadlthanner, K.Kernel principal component analysis(KPCA) is a nonlinear projective technique that can be applied to decompose multi-dimensional signals and extract informative features as well as reduce any noise contributions. In this work we extend KPCA to extract and remove artifact-related contributions as well as noise from one-dimensional signal recordings. We introduce an embedding step which transforms the one-dimensional signal into a multi-dimensional vector. The latter is decomposed in feature space to extract artifact related contaminations. We further address the preimage problem and propose an initialization procedure to the fixed-point algorithm which renders it more efficient. Finally we apply KPCA to extract dominant Electrooculogram (EOG) artifacts contaminating Electroencephalogram (EEG) recordings in a frontal channel.
- Scratch on Road Pedagogical Model: Study of learning perceptionPublication . Almeida, Maria Emilia Bigotte de; Almeida, Ricardo; Teixeira, AnaThis paper presents Scratch on Road pedagogical model, that is been used in several 4th grade classes. This model foresees the participation of both the community and higher education institutions, with active roles in classes and consequently in students’ projects – stories, animations or games. This pedagogical model has an investigation component aiming to comprehend students’ perceptions relating their own learnings. The study, conducted in three classes, reveals that students don’t have a clearly perception relating their learnings, with focus on specific Scratch contents.