2016
Authors
Paiva, JS; Rodrigues, S; Silva Cunha, JPS;
Publication
2016 38TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Abstract
Firefighting is a stressful occupation. The monitoring of psychophysiological measures in those professionals can be a way to prevent and early detect cardiac diseases and other stress-related problems. The current study aimed to assess morphological changes in the ECG signal induced by acute stress. A laboratory protocol was conducted among 6 firefighters, including a laboratory stress-inducer task - the Trier Social Stress Task (TSST) - and a 2-choice reaction time task (CRTT) that was performed before (CRTT1) and after (CRTT2) the stress condition. ECG signals were continuously acquired using the VitalJacket (R), a wearable t-shirt that acts as a medical certified ECG monitor. Results showed that ECG morphological features such as QT and ST intervals are able to differentiate stressful from non stressful events in first responders. Group mean Visual Analogue Scale (VAS) for stress assessment significantly increased after the stress task (TSST), relatively to the end of CRTT2 (after TSST: 4.67 +/- 1.63; after CRTT2: 3.17 +/- 0.75), a change that was accompanied by a significant increase in group mean QT and ST segments corrected for heart rate during TSST. These encouraging results will be followed by larger studies in order to explore those measures and its physiological impact under realistic environments in a higher scalability.
2016
Authors
Sequeira A.F.; Chen L.; Ferryman J.; Alonso-Fernandez F.; Bigun J.; Raja K.B.; Raghavendra R.; Busch C.; Wild P.;
Publication
Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
Abstract
This work presents a novel dual-spectrum database containing both iris and periocular images synchronously captured from a distance and within a realistic indoor environment. This database was used in the 1st Cross-Spectrum Iris/Periocular Recognition Competition (Cross-Eyed 2016). This competition aimed at recording recent advances in cross-spectrum iris and periocular recognition. Six submissions were evaluated for crossspectrum periocular recognition, and three for iris recognition. The submitted algorithms are briefly introduced. Detailed results are reported in this paper, and comparison of the results is discussed.
2016
Authors
Gonçalves, L; Novo, J; Campilho, A;
Publication
24th European Symposium on Artificial Neural Networks, ESANN 2016, Bruges, Belgium, April 27-29, 2016
Abstract
This work presents the results of the characterization of lung nodules in chest Computerized Tomography for benign/malignant classification. A set of image features was used in the Computer-aided Diagnosis system to distinguish benign from malignant nodules and, therefore, diagnose lung cancer. A filter-based feature selection approach was used in order to define an optimal subset with higher accuracy. A large and heterogeneous set of 293 features was defined, including shape, intensity and texture features. We used different KNN and SVM classifiers to evaluate the features subsets. The estimated results were tested in a dataset annotated by radiologists. Promising results were obtained with an area under the Receiver Operating Characteristic curve (AUC value) of 96:2 ± 0:5% using SVM.
2016
Authors
Pereira, T; Paiva, JS; Correia, C; Cardoso, J;
Publication
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
Abstract
The measurement and analysis of the arterial pulse waveform (APW) are the means for cardiovascular risk assessment. Optical sensors represent an attractive instrumental solution to APW assessment due to their truly non-contact nature that makes the measurement of the skin surface displacement possible, especially at the carotid artery site. In this work, an automatic method to extract and classify the acquired data of APW signals and noise segments was proposed. Two classifiers were implemented: k-nearest neighbours and support vector machine (SVM), and a comparative study was made, considering widely used performance metrics. This work represents a wide study in feature creation for APW. A pool of 37 features was extracted and split in different subsets: amplitude features, time domain statistics, wavelet features, cross-correlation features and frequency domain statistics. The support vector machine recursive feature elimination was implemented for feature selection in order to identify the most relevant feature. The best result (0.952 accuracy) in discrimination between signals and noise was obtained for the SVM classifier with an optimal feature subset .
2016
Authors
Achilles, F; Choupina, H; Loesch, A; S. Cunha, J; Remi, J; Vollmar, C; Tombari, F; Navab, N; Noachtar, S;
Publication
Clinical Neurophysiology
Abstract
2016
Authors
Pereira, T; Nogueira Silva, C; Simoes, R;
Publication
INFRARED PHYSICS & TECHNOLOGY
Abstract
Body skin temperature is a useful parameter for diagnosing diseases and infrared thermography can, be a powerful tool in providing important information to detect body temperature changes in a noninvasive way. The aim of this work was to study the pattern of skin temperature during pregnancy, to establish skin temperature reference values and to find correlations between these and the pregnant population characteristics. Sixty-one healthy pregnant women (mean age 30.6 +/- 5.1 years) in the 8th-40th gestational week with normal pregnancies were examined in 31 regions of interest (ROI). The ROIs were defined all over the body in order to determine the most influenced by factors such as age or body mass index (BMI). The results obtained in this work highlight that in normal pregnant women the skin temperature is symmetrically distributed, with the symmetrical areas differing less than 0.5 degrees C, with a mean value of 0.25 +/- 0.23 degrees C. This study identified a significant negative correlation between the BMI and temperature. Age has been shown to have great influence on the skin temperature, with a significant increase of temperature observed with age. This work explores a novel medical application of infrared thermography and provides a characterization of thermal skin profile in human pregnancy for a large set of ROIs while also evaluating the effects of age and BMI.
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