Desenvolvimento e caracterização de nanoemulsões cosméticas contendo extrato de Opuntia ficus-indica L. Mill e avaliação in vivo da eficácia hidratante

Nanoemulsions are emulsified systems, characterized for reduced droplet size (50- 500nm), which the main characteristic are kinect stability and thermodynamic instability. These are promising systems on cosmetic area due to their droplet size that provide different advantages when compared to conventional systems, among others, larger surface area and better permeability. The Opuntia ficus-indica (L.) Mill is a plant cultivated on Caatinga Brazilian biome, which has great socioeconomic importance to region. This plant shows carbohydrates utilized for cosmetic industry as moisturizing active in their chemical composition. The aim of study was to develop, characterize, evaluate stability and moisturizing efficacy of cosmetic nanoemulsions added to Opuntia ficus-indica (L.) Mill extract. Nanoemulsions preparation was made using a low energy method. Different nanoemulsions were formulated varying the ratio of oil, water and surfactant phases beyond xanthan gum (0.5% e 1%) and Opuntia ficus-indica (L.) Mill hydroglycolic extract addition on 1% and 3%. Obtained nanoemulsions were submitted to preliminary and accelerated stability tests. The evaluated parameters monitored were: macroscopic aspect, pH value, droplet size, zeta potential and polydispersion index, during 60 days on different temperatures. Stable formulations were submitted to moisturizing efficacy assessment by capacitance and transepidermal water loss methodologies during 5 hours. Stable samples were white and showed homogeneous and fluid aspect, pH value was inside ideal range (4,5-6,0) to topical application and droplet size under 200nm characterizing these system as nanoemulsions. Developed nanoemulsions did not decrease transepidermal water loss, however increased the water content on stratum corneum, highlighting the nanoemulsions containing 0.5% of xanthan gum and 1% of hydroglycolic extract. This work presents cosmetic moisturizing nanoemulsions composed to vegetal raw material from Brazilian Caatinga with potential to be used on cosmetic area.

Registro global de nuvens de pontos RGB-D em tempo real usando fluxo óptico e marcadores

Registration of point clouds captured by depth sensors is an important task in 3D reconstruction applications based on computer vision. In many applications with strict performance requirements, the registration should be executed not only with precision, but also in the same frequency as data is acquired by the sensor. This thesis proposes theuse of the pyramidal sparse optical flow algorithm to incrementally register point clouds captured by RGB-D sensors (e.g. Microsoft Kinect) in real time. The accumulated errorinherent to the process is posteriorly minimized by utilizing a marker and pose graph optimization. Experimental results gathered by processing several RGB-D datasets validatethe system proposed by this thesis in visual odometry and simultaneous localization and mapping (SLAM) applications.

Atividade eletroencefalográfica de pacientes com acidente vascular cerebral na aprendizagem motora de um jogo baseado em realidade virtual

Stroke is the leading cause of long-term disability among adults and motor relearning is essential in motor sequelae recovery. Therefore, various techniques have been proposed to achieve this end, among them Virtual Reality. The aim of the study was to evaluate electroencephalographic activity of stroke patients in motor learning of a virtual reality-based game. The study included 10 patients with chronic stroke, right-hande; 5 with left brain injury (LP), mean age 48.8 years (± 4.76) and 5 with injury to the right (RP), mean age 52 years (± 10.93). Participants were evaluated for electroencephalographic (EEG) activity and performance while performing 15 repetitions of darts game in XBOX Kinect and also through the NIHSS, MMSE, Fugl-Meyer and the modified Ashworth scale. Patients underwent a trainning with 45 repetitions of virtual darts game, 12 sessions in four weeks. After training, patients underwent reassessment of EEG activity and performance in virtual game of darts (retention). Data were analyzed using ANOVA for repeated measures. According to the results, there were differences between the groups (PD and PE) in frequencies Low Alpha (p = 0.0001), High Alpha (p = 0.0001) and Beta (p = 0.0001). There was an increase in alpha activation powers and a decrease in beta in the phase retention of RP group. In LP group was observed increased alpha activation potency, but without decrease in beta activation. Considering the asymmetry score, RP group increased brain activation in the left hemisphere with the practice in the frontal areas, however, LP group had increased activation of the right hemisphere in fronto-central areas, temporal and parietal. As for performance, it was observed a decrease in absolute error in the game for RP group between assessment and retention (p = 0.015), but this difference was not observed for LP group (p = 0.135). It follows then that the right brain injury patients benefited more from darts game training in the virtual environment with respect to the motor learning process, reducing neural effort in ipsilesionais areas and errors with the practice of the task. In contrast, patients with lesions in left hemisphere decrease neural effort in contralesionais areas important for motor learning and showed no performance improvements with practice of 12 sessions of virtual dart game. Thus, the RV can be used in rehabilitation of stroke patients upper limb, but the laterality of the injury should be considered in programming the motor learning protocol.

Serious Game no tratamento de obesidade infantil: uma proposta de interação natural com monitoramento remoto

The number of overweight people has increased in the last few years. Factors such as attention to diet and changes in lifestyle are crucial in the prevention and control of obesity and diseases related to it. Experts believe that such actions are most effective when initiated during childhood, and that children raised in an environment that encourages physical activity ultimately become healthier adults. However, to arouse and maintain interest in such activities represent a major challenge, which are initially perceived as repetitive and boring, and, thus, soon abandoned. Computer games, traditionally seen as stimulants to a sedentary lifestyle are changing this perception using non-conventional controls that require constant movement of the player. Applications that combine the playfulness of such games to physical activity through devices, like Microsoft Kinect, might become interesting tools in this scenario, by using the familiarity of Natural User Interfaces along with the challenge and the fun of video games, in order to make attractive exercise routines for schoolchildren. The project carried out consists of an exergame composed of several activities designed and implemented with the participation of a Physical Educator, aimed at children between eight and ten years old, whose performance and progress can be remotely monitored by a professional via web interface. The application arising from this work was accompanied by tests with a group of graduating Physical Education students from the University of Rio Verde GO, and subsequently validated through questionnaires whose results are shown on this work.

3D Navigation with Six Degrees-of-Freedom using a Multi-Touch Display

With the introduction of new input devices, such as multi-touch surface displays, the Nintendo WiiMote, the Microsoft Kinect, and the Leap Motion sensor, among others, the field of Human-Computer Interaction (HCI) finds itself at an important crossroads that requires solving new challenges. Given the amount of three-dimensional (3D) data available today, 3D navigation plays an important role in 3D User Interfaces (3DUI). This dissertation deals with multi-touch, 3D navigation, and how users can explore 3D virtual worlds using a multi-touch, non-stereo, desktop display. The contributions of this dissertation include a feature-extraction algorithm for multi-touch displays (FETOUCH), a multi-touch and gyroscope interaction technique (GyroTouch), a theoretical model for multi-touch interaction using high-level Petri Nets (PeNTa), an algorithm to resolve ambiguities in the multi-touch gesture classification process (Yield), a proposed technique for navigational experiments (FaNS), a proposed gesture (Hold-and-Roll), and an experiment prototype for 3D navigation (3DNav). The verification experiment for 3DNav was conducted with 30 human-subjects of both genders. The experiment used the 3DNav prototype to present a pseudo-universe, where each user was required to find five objects using the multi-touch display and five objects using a game controller (GamePad). For the multi-touch display, 3DNav used a commercial library called GestureWorks in conjunction with Yield to resolve the ambiguity posed by the multiplicity of gestures reported by the initial classification. The experiment compared both devices. The task completion time with multi-touch was slightly shorter, but the difference was not statistically significant. The design of experiment also included an equation that determined the level of video game console expertise of the subjects, which was used to break down users into two groups: casual users and experienced users. The study found that experienced gamers performed significantly faster with the GamePad than casual users. When looking at the groups separately, casual gamers performed significantly better using the multi-touch display, compared to the GamePad. Additional results are found in this dissertation.

Redefinición de las TIC en el museo: del discurso invasivo al inclusivo

Las TIC son inseparables de la museografía in situ e imprescindibles en la museografía en red fija y móvil. En demasiados casos se han instalado prótesis tecnológicas para barnizar de modernidad el espacio cultural, olvidando que la tecnología debe estar al servicio de los contenidos de manera que resulte invisible y perfectamente imbricada con la museografía tradicional. Las interfaces móviles pueden fusionar museo in situ y en red y acompañar a las personas más allá del espacio físico. Esa fusión debe partir de una base de datos narrativa y abierta a obras materiales e inmateriales de otros museos de manera que no se trasladen las limitaciones del museo físico al virtual. En el museo in situ tienen sentido las instalaciones hipermedia inmersivas que faciliten experiencias culturales innovadoras. La interactividad (relaciones virtuales) debe convivir con la interacción (relaciones físicas y personales) y estar al servicio de todas las personas, partiendo de que todas, todos tenemos limitaciones. Trabajar interdisciplinarmente ayuda a comprender mejor el museo para ponerlo al servicio de las personas.

Design and Implementation of a Low Cost Virtual Rugby Decision Making Interactive

The paper describes the design and implementation of a novel low cost virtual rugby decision making interactive for use in a visitor centre. Original laboratory-based experimental work in decision making in rugby, using a virtual reality headset [1] is adapted for use in a public visitor centre, with consideration given to usability, costs, practicality and health and safety. Movement of professional rugby players was captured and animated within a virtually recreated stadium. Users then interact with these virtual representations via use of a lowcost sensor (Microsoft Kinect) to attempt to block them. Retaining the principles of perception and action, egocentric viewpoint, immersion, sense of presence, representative design and game design the system delivers an engaging and effective interactive to illustrate the underlying scientific principles of deceptive movement. User testing highlighted the need for usability, system robustness, fair and accurate scoring, appropriate level of difficulty and enjoyment.

Real-time depth camera tracking with CAD models and ICP

In recent years, depth cameras have been widely utilized in camera tracking for augmented and mixed reality. Many of the studies focus on the methods that generate the reference model simultaneously with the tracking and allow operation in unprepared environments. However, methods that rely on predefined CAD models have their advantages. In such methods, the measurement errors are not accumulated to the model, they are tolerant to inaccurate initialization, and the tracking is always performed directly in reference model's coordinate system. In this paper, we present a method for tracking a depth camera with existing CAD models and the Iterative Closest Point (ICP) algorithm. In our approach, we render the CAD model using the latest pose estimate and construct a point cloud from the corresponding depth map. We construct another point cloud from currently captured depth frame, and find the incremental change in the camera pose by aligning the point clouds. We utilize a GPGPU-based implementation of the ICP which efficiently uses all the depth data in the process. The method runs in real-time, it is robust for outliers, and it does not require any preprocessing of the CAD models. We evaluated the approach using the Kinect depth sensor, and compared the results to a 2D edge-based method, to a depth-based SLAM method, and to the ground truth. The results show that the approach is more stable compared to the edge-based method and it suffers less from drift compared to the depth-based SLAM.

IntelliChair: a non-intrusive sitting posture and sitting activity recognition system

Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.

Navegação de robô móvel em ambiente com humanos

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Bin picking de objetos polimórficos convexos usando perceção 3D

O bin picking é um processo de grande interesse na indústria, uma vez que permite maior automatização, aumento da capacidade de produção e redução dos custos. Este tem vindo a evoluir bastante ao longo dos anos e essa evolução fez com que sistemas de perceção 3D começassem a ser implementados. Este trabalho tem como principal objetivo desenvolver um sistema de bin picking usando apenas perceção 3D. O sistema deve ser capaz de determinar a posição e orientação de objetos com diferentes formas e tamanhos, posicionados aleatoriamente numa superfície de trabalho. Os objetos utilizados para fazer os testes experimentais, são esferas, cilindros e prismas, uma vez que abrangem as formas geométricas existentes em muitos produtos submetidos a bin picking. Após a identi cação e seleção do objeto a apanhar, o manipulador deve autonomamente posicionar-se para fazer a aproximação e recolha do mesmo. A aquisição de dados é feita através de uma câmara Kinect. Dos dados recebidos apenas são trabalhados os referentes à profundidade, centrando-se assim este trabalho na análise e tratamento de nuvem de pontos. O sistema desenvolvido cumpre com os objetivos estabelecidos. Consegue localizar e apanhar objetos em várias posições e orientações. Além disso apresenta uma velocidade de processamento compatível com a aplicação em causa.

Utilising presence in places to support mobile interaction

Physical places are given contextual meaning by the objects and people that make up the space. Presence in physical places can be utilised to support mobile interaction by making access to media and notifications on a smartphone easier and more visible to other people. Smartphone interfaces can be extended into the physical world in a meaningful way by anchoring digital content to artefacts, and interactions situated around physical artefacts can provide contextual meaning to private manipulations with a mobile device. Additionally, places themselves are designed to support a set of tasks, and the logical structure of places can be used to organise content on the smartphone. Menus that adapt the functionality of a smartphone can support the user by presenting the tools most likely to be needed just-in-time, so that information needs can be satisfied quickly and with little cognitive effort. Furthermore, places are often shared with people whom the user knows, and the smartphone can facilitate social situations by providing access to content that stimulates conversation. However, the smartphone can disrupt a collaborative environment, by alerting the user with unimportant notifications, or sucking the user in to the digital world with attractive content that is only shown on a private screen. Sharing smartphone content on a situated display creates an inclusive and unobtrusive user experience, and can increase focus on a primary task by allowing content to be read at a glance. Mobile interaction situated around artefacts of personal places is investigated as a way to support users to access content from their smartphone while managing their physical presence. A menu that adapts to personal places is evaluated to reduce the time and effort of app navigation, and coordinating smartphone content on a situated display is found to support social engagement and the negotiation of notifications. Improving the sensing of smartphone users in places is a challenge that is out-with the scope of this thesis. Instead, interaction designers and developers should be provided with low-cost positioning tools that utilise presence in places, and enable quantitative and qualitative data to be collected in user evaluations. Two lightweight positioning tools are developed with the low-cost sensors that are currently available: The Microsoft Kinect depth sensor allows movements of a smartphone user to be tracked in a limited area of a place, and Bluetooth beacons enable the larger context of a place to be detected. Positioning experiments with each sensor are performed to highlight the capabilities and limitations of current sensing techniques for designing interactions with a smartphone. Both tools enable prototypes to be built with a rapid prototyping approach, and mobile interactions can be tested with more advanced sensing techniques as they become available. Sensing technologies are becoming pervasive, and it will soon be possible to perform reliable place detection in-the-wild. Novel interactions that utilise presence in places can support smartphone users by making access to useful functionality easy and more visible to the people who matter most in everyday life.

Contributions to 3D Data Registration and Representation

Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

Análisis comparativo de métodos de calibrado para sensores RGB-D y su influencia en el registro de múltiples vistas

Los sensores de propósito general RGB-D son dispositivos capaces de proporcionar información de color y de profundidad de la escena. Debido al amplio rango de aplicación que tienen estos sensores, despiertan gran interés en múltiples áreas, provocando que en algunos casos funcionen al límite de sensibilidad. Los métodos de calibración resultan más importantes, si cabe, para este tipo de sensores para mejorar la precisión de los datos adquiridos. Por esta razón, resulta de enorme transcendencia analizar y estudiar el calibrado de estos sensores RGBD de propósito general. En este trabajo se ha realizado un estudio de las diferentes tecnologías empleadas para determinar la profundidad, siendo la luz estructurada y el tiempo de vuelo las más comunes. Además, se ha analizado y estudiado aquellos parámetros del sensor que influyen en la obtención de los datos con precisión adecuada dependiendo del problema a tratar. El calibrado determina, como primer elemento del proceso de visión, los parámetros característicos que definen un sistema de visión artificial, en este caso, aquellos que permiten mejorar la exactitud y precisión de los datos aportados. En este trabajo se han analizado tres algoritmos de calibración, tanto de propósito general como de propósito específico, para llevar a cabo el proceso de calibrado de tres sensores ampliamente utilizados: Microsoft Kinect, PrimeSense Carmine 1.09 y Microsoft Kinect v2. Los dos primeros utilizan la tecnología de luz estructurada para determinar la profundidad, mientras que el tercero utiliza tiempo de vuelo. La experimentación realizada permite determinar de manera cuantitativa la exactitud y la precisión de los sensores y su mejora durante el proceso de calibrado, aportando los mejores resultados para cada caso. Finalmente, y con el objetivo de mostrar el proceso de calibrado en un sistema de registro global, diferentes pruebas han sido realizadas con el método de registro µ-MAR. Se ha utilizado inspección visual para determinar el comportamiento de los datos de captura corregidos según los resultados de los diferentes algoritmos de calibrado. Este hecho permite observar la importancia de disponer de datos exactos para ciertas aplicaciones como el registro 3D de una escena.

Interface natural baseado no movimento da cabeça e olhos

Dissertação de Mestrado, Engenharia Elétrica e Eletrónica, Especialização em Sistemas de Energia e Controlo, Instituto Superior de Engenharia, Universidade do Algarve, 2015