Francisco J. Pelayo

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This paper proposes a framework for constructing and training a radial basis function (RBF) neural network. For this purpose, a sequential learning algorithm is presented to adapt the structure of the network, in which it is possible to create a new hidden unit and also to detect and remove inactive units. The structure of the Gaussian functions is modi"ed(More)
We describe a pipelined optical-flow processing system that works as a virtual motion sensor. It is based on a field-programmable gate array (FPGA) device enabling the easy change of configuring parameters to adapt the sensor to different speeds, light conditions and other environmental factors. We refer to it as a “virtual sensor” because it consists of a(More)
Clinical applications such as artificial vision require extraordinary, diverse, lengthy and intimate collaborations among basic scientists, engineers and clinicians. In this review, we present the state of research on a visual neuroprosthesis designed to interface with the occipital visual cortex as a means through which a limited, but useful, visual sense(More)
Fully auditory Brain-computer interfaces based on the dichotic listening task (DL-BCIs) are suited for users unable to do any muscular movement, which includes gazing, exploration or coordination of their eyes looking for inputs in form of feedback, stimulation or visual support. However, one of their disadvantages, in contrast with the visual BCIs, is(More)
Brain–computer interfaces (BCIs) are mainly intended for people unable to perform any muscular movement, such as patients in a complete locked-in state. The majority of BCIs interact visually with the user, either in the form of stimulation or biofeedback. However, visual BCIs challenge their ultimate use because they require the subjects to gaze, explore(More)
OBJECTIVE Brain-computer interfaces based on steady-state visual evoked potentials (SSVEP-BCIs) achieve the highest performance, due to their multiclass nature, in paradigms in which different visual stimuli are shown. Studies of independent binary SSVEP-BCIs have been previously presented in which it was not necessary to gaze at the stimuli at the cost of(More)
Steady-state visual evoked potential (SSVEP)-based brain–computer interfaces (BCIs) use the spectral power of the potentials for classification as they can be voluntarily enhanced or diminished by the subject by means of selective attention. The features traditionally extracted from the EEG and used for BCIs have been characterized as a normal distribution,(More)
The paper presents a VLSI approach to approximate the real-time dynamics of a neuron model inspired from the classical model of Hodgkin and Huxley, in which analog inputs and outputs are represented by short spikes. Both the transient and the steady-state behaviours of these circuits depend only on process-independent local ratios, thus enabling single or(More)
to increase the degree of detail, mitigate glares and enhance the visibility of the scene in both bright and dim lighting conditions. The proposed operator and its real-time implementation are specially aimed as an aid system for visually impaired people who struggle to manage themselves in environments where illumination is not uniform or changes rapidly.(More)