The Efficacy of Motor Imagery Additional to Task-Oriented Training for Children with Developmental Coordination Disorder: A Study Protocol for a Randomized Open-Label Controlled Trial.

Background: Developmental Coordination Disorder (DCD) affects school-age children and interferes with the practice of their daily activities. Task-oriented work and motor imagery have shown great efficacy in addressing this problem.

Objective: This study presents a protocol that seeks to understand the effectiveness of a combined program of both modalities on the motor competence of children susceptible to the presence of DCD.

Eye State Detection Using Frequency Features from 1 or 2-Channel EEG.

Brain-computer interfaces (BCIs) establish a direct communication channel between the human brain and external devices. Among various methods, electroencephalography (EEG) stands out as the most popular choice for BCI design due to its non-invasiveness, ease of use, and cost-effectiveness. This paper aims to present and compare the accuracy and robustness of an EEG system employing one or two channels.

Proposals and Comparisons from One-Sensor EEG and EOG Human-Machine Interfaces.

Human-Machine Interfaces (HMI) allow users to interact with different devices such as computers or home elements. A key part in HMI is the design of simple non-invasive interfaces to capture the signals associated with the user's intentions. In this work, we have designed two different approaches based on Electroencephalography (EEG) and Electrooculography (EOG).

A Prototype of EEG System for IoT.

In this work, we develop open source hardware and software for eye state classification and integrate it with a protocol for the Internet of Things (IoT). We design and build the hardware using a reduced number of components and with a very low-cost. Moreover, we propose a method for the detection of open eyes (oE) and closed eyes (cE) states based on computing a power ratio between different frequency bands of the acquired signal.

Calculation of the Connected Dominating Set Considering Vertex Importance Metrics.

The computation of a set constituted by few vertices to define a virtual backbone supporting information interchange is a problem that arises in many areas when analysing networks of different natures, like wireless, brain, or social networks. Recent papers propose obtaining such a set of vertices by computing the connected dominating set (CDS) of a graph. In recent works, the CDS has been obtained by considering that all vertices exhibit similar characteristics.