Elena López

Bio: Elena López is an academic researcher from University of Alcalá. The author has contributed to research in topics: Mobile robot & Stereo camera. The author has an hindex of 16, co-authored 47 publications receiving 1471 citations.

System for assisted mobility using eye movements based on electrooculography

Abstract: Describes an eye-control method based on electrooculography (EOG) to develop a system for assisted mobility. One of its most important features is its modularity, making it adaptable to the particular needs of each user according to the type and degree of handicap involved. An eye model based on electrooculographic signal is proposed and its validity is studied. Several human-machine interfaces (HMI) based on EOG are commented, focusing our study on guiding and controlling a wheelchair for disabled people, where the control is actually effected by eye movements within the socket. Different techniques and guidance strategies are then shown with comments on the advantages and disadvantages of each one. The system consists of a standard electric wheelchair with an on-board computer, sensors and a graphic user interface run by the computer. On the other hand, this eye-control method can be applied to handle graphical interfaces, where the eye is used as a mouse computer. Results obtained show that this control technique could be useful in multiple applications, such as mobility and communication aid for handicapped persons.

Wheelchair Guidance Strategies Using EOG

Abstract: This paper describes an eye-control method, based on electrooculography (EOG), for guiding and controlling a wheelchair for disabled people; the control is actually effected by eye movements within the socket. An eye model based on an electrooculographic signal is proposed and its validity is studied. Different techniques and guidance strategies are then shown with comments on the advantages and disadvantages of each one. The system consists of a standard electric wheelchair with an on-board computer, sensors and a graphic user interface run by the computer. This control technique could be useful in multiple applications, such as mobility and communication aid for handicapped persons.

EOG-based eye movements codification for human computer interaction

Abstract: Highlights? We present a new eye-control method for eye-based computer interaction using EOG. ? An electrooculographic eye model based on wavelet and neural networks is proposed. ? Results demonstrate the system's reliability in detecting eye movements. ? This model minimizes the problems associated with progressive user tiredness. ? Any HCI can be controlled using eye movements detected by EOG. This paper describes a new eye-control method for eye-based computer interaction using EOG. This work aims to resolve some of the problems encountered in current systems when used for long periods of time and users become tired. For this purpose, a new electrooculographic eye model based on wavelet transform and neural networks is proposed. The results obtained demonstrate the system's reliability in detecting eye movements and show an error of less than 2? during long periods of use. The system proposed may be used to control any graphical interface using eye movements detected by electrooculography.

Unifying Terrain Awareness for the Visually Impaired through Real-Time Semantic Segmentation.

Abstract: Navigational assistance aims to help visually-impaired people to ambulate the environment safely and independently. This topic becomes challenging as it requires detecting a wide variety of scenes to provide higher level assistive awareness. Vision-based technologies with monocular detectors or depth sensors have sprung up within several years of research. These separate approaches have achieved remarkable results with relatively low processing time and have improved the mobility of impaired people to a large extent. However, running all detectors jointly increases the latency and burdens the computational resources. In this paper, we put forward seizing pixel-wise semantic segmentation to cover navigation-related perception needs in a unified way. This is critical not only for the terrain awareness regarding traversable areas, sidewalks, stairs and water hazards, but also for the avoidance of short-range obstacles, fast-approaching pedestrians and vehicles. The core of our unification proposal is a deep architecture, aimed at attaining efficient semantic understanding. We have integrated the approach in a wearable navigation system by incorporating robust depth segmentation. A comprehensive set of experiments prove the qualified accuracy over state-of-the-art methods while maintaining real-time speed. We also present a closed-loop field test involving real visually-impaired users, demonstrating the effectivity and versatility of the assistive framework.

Electro-Oculographic Guidance of a Wheelchair Using Eye Movements Codification

Abstract: In this paper we present a new method to guide mobile robots. An eye-control device based on electro-oculography (EOG) is designed to develop a system for assisted mobility. Control is made by means eye movements detected using electro-oculographic potential. Using an inverse eye model, the saccadic eye movements can be detected and know where the user is looking. This control technique can be useful in multiple applications, but in this work it is used to guide a wheelchair for helping people with severe disabilities. The system consists of a standard electric wheelchair, an on-board computer, sensors and a graphical user interface. Finally, we comment on some experimental results and conclusions about electro-oculographic guidance using ocular commands.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Extreme learning machines: a survey

Abstract: Computational intelligence techniques have been used in wide applications. Out of numerous computational intelligence techniques, neural networks and support vector machines (SVMs) have been playing the dominant roles. However, it is known that both neural networks and SVMs face some challenging issues such as: (1) slow learning speed, (2) trivial human intervene, and/or (3) poor computational scalability. Extreme learning machine (ELM) as emergent technology which overcomes some challenges faced by other techniques has recently attracted the attention from more and more researchers. ELM works for generalized single-hidden layer feedforward networks (SLFNs). The essence of ELM is that the hidden layer of SLFNs need not be tuned. Compared with those traditional computational intelligence techniques, ELM provides better generalization performance at a much faster learning speed and with least human intervene. This paper gives a survey on ELM and its variants, especially on (1) batch learning mode of ELM, (2) fully complex ELM, (3) online sequential ELM, (4) incremental ELM, and (5) ensemble of ELM.

Deep learning in bioinformatics

Abstract: In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies.

Digital control of dynamic systems

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