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Robotics, Artificial Intelligence (AI), and the Internet of Things (IoT) support various processes in many scenarios of modern life such as e-health and psychological treatments. This article presents the design, development, implementation, and assessment of a Robotic Assistant (RA), named “Atent@”, as a support tool in the homework activities of children with Attention Deficit Hyperactivity Disorder (ADHD). Interacting with the children the RA helps them correct their bad habits and misbehavior caused by the disorder. Its features and functionalities were designed by therapists, implementing AI algorithms to process information and make decisions in real-time to help children to be focused on their homework. This RA interacts with smart objects deployed at home, which are associated with the activity under observation (desk and chair). This solution allows therapists to receive more accurate information about the homework sessions inside the home. At the same time, remote interaction with the child is made possible (through the RA) to provide new instructions and support him/her along with the sessions. This RA is a significant evolution of an earlier version. All the improvements brought to the project by the modifications in technical and qualitative features are explained. Furthermore, the experiment and its results are presented to illustrate the clinical potential. This project shows that the RA can not only make observations with a high degree of precision like an expert (teacher/therapist) but also positively influences the homework performance of children with and without ADHD.

The Central Nervous System of humans continuously evolves when children engage in new activities. These activities are progressing from learning to eat as a baby over playing during childhood up to homework in all its dimensions. These activities, which are meaningful and relevant to everyone, constitute what occupational therapists call “occupations”. The successful execution of these occupations makes the development of new roles as well as the construction of a correct state of health possible. Due to these reasons, occupational performance is a fundamental part of development throughout childhood. Homework is complex and extends beyond the school context to the home. For many children, the performance of these homework items is a difficult challenge or even impossible to overcome without the help of an adult. This article presents the design, implementation, and functional validation of an intelligent home environment that uses homework activities as a support tool for children with or without attention disabilities. In this project, the Internet of Things (IoT) paradigm is combined with the development of robotic assistance to implement an intelligent home environment. In this environment, we have included intelligent things (where the usual study chairs and desks become smart objects) that determine in real-time the child's behavior during the development of homework and a robotic assistant which interacts with the children providing the necessary accompaniment (supervision and guidelines) just as a therapist would do. This development has been functionally validated by tests on several school-aged children without pathologies. In a later phase of the study, the proposal will be validated with children with different pathologies with an impact on learning, including Attention Disorder Hyperactivity Disorder (ADHD). The goal is the generation of intelligent places for therapeutic purposes within the home as assistance for children having difficulties to work with their homework assignment due to ADHD.

This article is a proposal for an intelligent system that facilitates the therapy process for children with Attention Deficit Hyperactivity Disorder - ADHD. This project focuses on the analysis, design, and implementation of an intelligent architecture, which uses machine learning techniques for a therapeutic robot to help develop new tests and other resources to support the treatment of ADHD. Its general purpose is to identify common patterns in the behavior of children with ADHD, between 6 and 9 years old during the performance of homework to help the therapist diagnose and predict the future behavior of children in this area. A system has been proposed whose development and implementation is carried out by a cloud computing platform, taking advantage of all its benefits such as low latency, unlimited storage, functionalities to deploy a project based on artificial intelligence and data security. Therefore, using these functionalities from the platform, a machine learning model has been deployed. This model is a binary classification since it groups the results according to the diagnosis (ADHD or not ADHD). However, what this model provides are the rules that compare the data obtained from the robot’s sensors to the set of results expected to be obtained (ADHD or not ADHD). To obtain these rules, an algorithm already developed by this platform and a set of data will be used. This first part is known as model training, in which the model has been built. Once the rules are obtained, another set of data will be used for testing. In this second part, the model will be able to identify whether the new data entered matches the criteria of a child with ADHD or with a typical development. The data processing is carried out from the cloud platform, offering data availability and accessibility at all times. The results of the correlation between the obtained data and the predicted diagnosis showed remarkable results.

This manuscript presents a system for homework assistance for children with Attention Deficit Hyperactivity Disorder - ADHD. This system consists of a robot and a set of smart objects constantly monitoring the child’s activities during the performance of his tasks. The design of this system is focused on creating a robot-child relationship. It is possible for the child with this type of disorder to acquire the different capacities that allow him to carry out his tasks independently and effectively through short instructions and different methodologies (such as short physical exercise). Besides, it is a support tool for parents and therapists to better comprehend the behavior of their children and patients, respectively. This system allows a better understanding of the patient’s clinical characteristics, his evolution, and the therapeutic options that may have a greater effect on him. This project is focused on the implementation of an information processing software and a User Interface UI for the Atent@ robot. Thanks to the software the robot is provided with many functionalities for inter-acting with the child. This system is based on IoT architecture. Both the robot and the smart objects are connected to a Realtime Database so that the data can be processed and shared with parents and therapists in real-time through a mobile application. This work shows the entire design and implementation of this software as well as the functional tests and their results.

Each year, trauma accidents generate about five million deaths worldwide. Additionally, these accidents increase the number of people with disabilities in their most productive years. This is a problem that represents social and economic impacts on families. Most of these accidents occur due to a lack of information about prevention. Low-income and middle-income countries are especially affected because here there are no programs to provide information about trauma accident prevention. This document details the development of a robotic assistant to support the process of teaching about accident prevention in different scenarios: prevention of transit accidents (to be hit by a car) as well as prevention of home accidents (burns and intoxications). This assistant is equipped with an audiovisual user-friendly interface for the child and teacher to be used at initial schools. It is focused to teach children from ages three-six years old. The experiment’s results show that the information provided by the robotic assistant during the teaching process is retained by the children over a long time. This methodology provides a more interactive teaching process compared to traditional methods. The design, developing, implementation, experiments, results, and conclusions are detailed below.

Cerebral Palsy (CP) is a disorder originated in the motor cortex of the brain. Its causes are unknown but many theories detail that it occurs during the gestation period when the fetus has not enough oxygen in the brain (hypoxia). This paper shows the last investigative stage in the development of transmitters of needs, here is detailed the third version of it, which is based on completely improving its predecessorsin order to cover a larger population of boys and girls with cerebral palsy that present clinical pictures of hemiplegia and quadriplegia. Children who suffer this disorder cannot communicate their needs, thoughts or desires even with language of gestures, because it is difficult for them to learn it and in many cases their bodies do not even allow them to move their arms. So it is necessary to find a way to provide these children with a means of communication, a non-invasive method, that is; a system that adapts its functionality to the specific needs of children. This latest version of the device brings an update of the mobile application. This is necessary for the child's interaction with their parents, teachers or therapists. The validation method of the device is the contrast of the results obtained with respect to its predecessor version. All these points including the process of development of said system, is detailed in the chapters below.

The leading cause of disability in Ecuadorian children is cerebral palsy, this disorder in most cases produces a deficiency of the ability to move fingers, hands and wrists at various levels, this happens too with the intellect of the patient. Many of the treatments and therapies are seeking that the patient can develop all of your motor ability and intellectual skills, using activities that involve the part Intellectual and practicality of their extremities. Today technology gives us the opportunity to manage devices of aid and assistance that not only complement the daily activities that are performed during the therapies in the help centers, they need to give results that show leaps and bounds in the progress that you want to get. The purpose of this project is to make a device that helps a patient to develop their fine motor ability to the patient can use their hands, fingers and wrists movements in various ways in coordination with their vision in conjunction with occipital lobe causing that brain activity in the patient, present alterations of amplitude in the beta waves in the hemispheres of the brain that allow move muscles, with only maneuver a fully digital device and low cost. These brain and muscles signals will be analyzed in this project, to test the efficiency of this project.