Abstract
The laser diode self-mixing technique is a well-known and powerful interferometric technique that has been used in biomedical applications, namely for the extraction of cardiovascular parameters. However, to construct an optical probe using the self-mixing principle which is able to acquire signals in the human carotid artery, some problems are expected. The laser diode has a small aperture area, which means that, for physiological sensing purposes, it can be considered as a point-like detector. This feature imparts difficulties to quality recording of physiological signals since the number of photons collected and mixed in the cavity of the photodiode is very small. In order to overcome this problem, a new mixing geometry based on an external large area planar photodiode (PD) is used in the probe, enabling a much larger number of photons to be collected, hence improving the quality of the signal. In this work, the possibility to obtain the mixing effect outside the laser cavity using an external photodetector, such as a planar photodiode, is demonstrated. Two test benches were designed, both with of two reflectors. The first one, which reflects the light beam with the same frequency of the original one is fixed, and the second one, is movable, reflecting the Doppler shifted light to the photodetector. The first test bench has a fixed mirror in front of the movable mirror, creating an umbra and penumbra shadow above the movable mirror. To avoid this problem, another test bench was constructed using a wedged beam splitter (WSB) instead of a fixed mirror. This new assembly ensures the separation of a single input beam into multiple copies that undergo successive reflections and refractions. Some light waves are reflected by the planar surface of WSB, while other light beams are transmitted through the WSB, reaching the movable mirror. Also in this case, the movable mirror reflects the light with a Doppler frequency shift, and the PD receives both beams. The two test benches were designed to demonstrate that it is possible to obtain mixing effect outside the laser cavity, using a planar photodiode. The Doppler spectrograms from the signals acquired in the test benches show that the signal frequency changes along time which correspond to the modulus of the derivative of the mirror movement, as expected in the self-mixing signals. Nevertheless, the test bench A showed better results than the test bench B. This fact probably results from the attenuation that the original beam suffers in each reflection and refraction in the WBS. Tests developed in the test benches opened the possibility to construct a probe that uses a planar photodiode with a large area to collect medical signals, and improve the quality of the acquisition with a better SNR.

Abstract
The Arterial Pressure Waveform (APW) can provide essential information about arterial wall integrity and arterial stiffness. Most of APW analysis frameworks individually process each hemodynamic parameter and do not evaluate inter-dependencies in the overall pulse morphology. The key contribution of this work is the use of machine learning algorithms to deal with vectorized features extracted from APW. With this purpose, we follow a five-step evaluation methodology: (1) a custom-designed, non-invasive, electromechanical device was used in the data collection from 50 subjects; (2) the acquired position and amplitude of onset, Systolic Peak (SP), Point of Inflection (Pi) and Dicrotic Wave (DW) were used for the computation of some morphological attributes; (3) pre-processing work on the datasets was performed in order to reduce the number of input features and increase the model accuracy by selecting the most relevant ones; (4) classification of the dataset was carried out using four different machine learning algorithms: Random Forest, BayesNet (probabilistic), J48 (decision tree) and RIPPER (rule-based induction); and (5) we evaluate the trained models, using the majority-voting system, comparatively to the respective calculated Augmentation Index (AIx). Classification algorithms have been proved to be efficient, in particular Random Forest has shown good accuracy (96.95%) and high area under the curve (AUC) of a Receiver Operating Characteristic (ROC) curve (0.961). Finally, during validation tests, a correlation between high risk labels, retrieved from the multi-parametric approach, and positive AIx values was verified. This approach gives allowance for designing new hemodynamic morphology vectors and techniques for multiple APW analysis, thus improving the arterial pulse understanding, especially when compared to traditional single-parameter analysis, where the failure in one parameter measurement component, such as Pi, can jeopardize the whole evaluation. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Abstract
The rising challenges in the field of iris recognition, concerning the development of accurate recognition algorithms using images acquired under an unconstrained set of conditions, is leading to the a renewed interest in the area. Although several works already report excellent recognition rates, these values are obtained by acquiring images in very controlled environments. The use of such systems in daily security activities, such as airport security and bank account management, is therefore hindered by the inherent unconstrained nature under which images are to be acquired. The proposed work focused on mutual context information from iris centre and iris limbic contour to perform robust and accurate iris segmentation in noisy images. A random subset of the UBIRIS.v2 database was tested with a promising E1 classification rate of 0.0109.

Abstract
One line of research and development in robotics receiving increasing attention in recent years is the development of biologically inspired robots. The idea is to gain knowledge of biological beings and apply the knowledge thus acquired to implement the same methods of locomotion (or at least use the biological inspiration) on the machines we build. It is believed that this way it is possible to develop machines with capabilities similar to those of biological beings in terms of locomotion skills and energy efficiency. One way to better understand the functioning of these systems, without the need to develop prototypes with long and costly development, is to use simulation models. Given these ideas, this work concerns the study of the biomechanics of the spider crab, using the SimMechanics toolbox of Matlab/Simulink. This paper describes the anatomy and locomotion of the spider crab, its modeling and control and the locomotion simulation of a crab within the SimMechanics environment.

Abstract
Cardiovascular diseases are a growing epidemiological burden in today's society. A great deal of effort has been made to find solutions able to perform non-invasive monitoring and early diagnosis of such pathologies. The pulse wave velocity and certain waveform characteristics constitute some of the most important cardiovascular risk indicators. Optical sensors are an attractive instrumental solution in this kind of time assessment applications due to their truly non-contact operation capability and better resolution than commercial devices. This study consisted on the experimental validation and a clinical feasibility for a non-invasive and multi-parametric optical system for evaluation of the cardiovascular condition. Two prototypes, based on two different types of photodetectors (planar and avalanche photodiode) were tested in a small group of volunteers, and the main hemodynamic parameters were measured, such as pulse wave velocity and indexes of pulse waveform analysis: the Augmentation Index, Subendocardial Viability Ratio and Ejection Time Index. The probes under study proved to be able to measure the pulse pressure wave in a reliable manner at the carotid site, and demonstrated the consistency of the parameters determined using dedicated algorithms. This study represents a preliminary evaluation of an optical system devoted to the clinical evaluation environment. Further development to take this system to a higher level of clinical significance, by incorporating it in a multicenter study, is currently underway. © 2013 Biomedical Engineering Society.

Abstract
The goal of the Vital Responder research project is to explore the synergies between innovative wearable technologies, scattered sensor networks, intelligent building technology and precise localization services to provide secure, reliable and effective first-response systems in critical emergency scenarios. Critical events, such as natural disaster or other large-scale emergency, induce fatigue and stress in first responders, such as fire fighters, policemen and paramedics. There are distinct fatigue and stress factors (and even pathologies) that were identified among these professionals. Nevertheless, previous work has uncovered a lack of real-time monitoring and decision technologies that can lead to in-depth understanding of the physiological stress processes and to the development of adequate response mechanisms. Our "silver bullet" to address these challenges is a suite of non-intrusive wearable technologies, as inconspicuous as a t-shirt, capable of gathering relevant information about the individual and disseminating this information through a wireless sensor network. In this paper we will describe the objectives, activities and results of the first two years of the Vital Responder project, depicting how it is possible to address wearable sensing challenges even in very uncontrolled environments. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.