Causes of low vision and use of optical aids in the elderly

PURPOSE: To determine the causes of low vision in an elderly population attended by a university visual rehabilitation service and to check for the use of prescribed optical aids. METHOD: A cross-sectional study was carried out on patients aged 60 years or over attending for the first time a university low vision service in 2001. Ophthalmic reevaluation and interview were performed by means of a structured questionnaire in 2002. RESULTS: The sample comprised 50 subjects aged between 60 and 90 years. Severe low vision (<20/200) was present in 68.0% of patients. The main cause of low vision was age-related macular degeneration (44.0%). Regarding literacy, 16.0% were illiterate and 72.0% had completed fundamental schooling. Thirty-one patients (62.0%) had been prescribed optical aids; 54.8% of these patients stated that they use them. A majority (70.6%) held a favorable opinion of these aids. CONCLUSIONS: The main cause of low vision was age-related macular degeneration. Approximately half of those receiving prescriptions reported actually using the aids in their daily activities. Making best use of residual vision in the elderly population with visual impairment is a priority, given the social context, if the independence necessary for enhanced quality of life is to be achieved.

Vision-based hand Wheel-chair control

Several studies have shown that people with disabilities benefit substantially from access to a means of independent mobility and assistive technology. Researchers are using technology originally developed for mobile robots to create easier to use wheelchairs. With this kind of technology people with disabilities can gain a degree of independence in performing daily life activities. In this work a computer vision system is presented, able to drive a wheelchair with a minimum number of finger commands. The user hand is detected and segmented with the use of a kinect camera, and fingertips are extracted from depth information, and used as wheelchair commands.

[Preface to] RoboCup 2007: Robot Soccer World Cup XI

[Excerpt] The 11th RoboCup International Symposium was held during July 9–10, 2007 at the Fox Theatre in Atlanta, GA, immediately after the 2007 Soccer, Rescue and Junior Competitions. The RoboCup community has observed an increasing interest from other communities over the past few years, e.g., the robotics community.RoboCupisseenasasignificantapproachtotheevaluationofnewlydeveloped methods to many difficult problems in robotics. Atlanta was also the location of a RoboCup@Space demonstration, which reflected the role of AI and robotics in space exploration. Prior to the symposium, space agencies had expressed an interest in cooperating with RoboCup. A first step in this direction was a successful demonstration at RoboCup 2007, which was accompanied with aninvitedtalkgivenbyaleadingscientistfromtheJapanAerospaceExploration Agency JAXA. [...]

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Generating timed trajectories foran autonomous robot

Tese de Doutoramento Programa Doutoral em Engenharia Electrónica e Computadores

IEA EBC Annex56 vision for cost effective energy and carbon emissions optimization in building renovation

Building sector has become an important target for carbon emissions reduction, energy consumption and resources depletion. Due to low rates of replacement of the existing buildings, their low energy performances are a major concern. Most of the current regulations are focused on new buildings and do not account with the several technical, functional and economic constraints that have to be faced in the renovation of existing buildings. Thus, a new methodology is proposed to be used in the decision making process for energy related building renovation, allowing finding a cost-effective balance between energy consumption, carbon emissions and overall added value.

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

Global vs. local nonlinear optimization techniques for human-like movement of an anthropomorphic robot

In this paper a comparison between using global and local optimization techniques for solving the problem of generating human-like arm and hand movements for an anthropomorphic dual arm robot is made. Although the objective function involved in each optimization problem is convex, there is no evidence that the admissible regions of these problems are convex sets. For the sequence of movements for which the numerical tests were done there were no significant differences between the optimal solutions obtained using the global and the local techniques. This suggests that the optimal solution obtained using the local solver is indeed a global solution.

Sistema de visão robótico baseado no sensor kinect para orientação no espaço e contorno de obstáculos

Dissertação de mestrado em Engenharia Eletrónica Industrial e Computadores (área de especialização em Robótica)

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

A bio-inspired computational model for motion detection

Tese de Doutoramento (Programa Doutoral em Engenharia Biomédica)

Neural mechanisms of attentional selection in vision : locations, features, and objects

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2012

Data mining in diagnostic charts and treatment outcome prediction for vision restoration therapy

Data Mining, Vision Restoration, Treatment outcome prediction, Self-Organising-Map