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Antonio García H.
Departamento de Automática, Escuela Politécnica Superior, Universidad de Alcalá, Alcalá de Henares, Spain

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Journal article
Published: 28 August 2019 in JMIR mHealth and uHealth
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Background Pegboard tests are a powerful technique used by health and education professionals to evaluate manual dexterity and fine motor speed, both in children and adults. Using traditional pegboards in tests, the total time that, for example, a 4-year-old child needs for inserting pegs in a pegboard, with the left or right hand, can be measured. However, these measurements only allow for studying the variability among individuals, whereas no data can be obtained on the intraindividual variability in inserting and removing these pegs with one and the other hand. Objective The aim of this research was to study the intraindividual variabilities in fine manual motor skills of 2- to 3-year-old children during playing activities, using a custom designed electronic pegboard. Methods We have carried out a pilot study with 39 children, aged between 25 and 41 months. The children were observed while performing a task involving removing 10 pegs from 10 holes on one side and inserting them in 10 holes on the other side of a custom-designed sensor-based electronic pegboard, which has been built to be able to measure the times between peg insertions and removals. Results A sensor-based electronic pegboard was successfully developed, enabling the collection of single movement time data. In the piloting, a lower intraindividual variability was found in children with lower placement and removal times, confirming Adolph et al’s hypothesis. Conclusions The developed pegboard allows for studying intraindividual variability using automated wirelessly transmitted data provided by its sensors. This novel technique has been useful in studying and validating the hypothesis that children with lower movement times present lower intraindividual variability. New research is necessary to confirm these findings. Research with larger sample sizes and age ranges that include additional testing of children’s motor development level is currently in preparation.

ACS Style

Diego Rivera; Antonio García; Jose Eugenio Ortega; Bernardo Alarcos; Kevin Van Der Meulen; Juan R Velasco; Cristina Del Barrio; Wu-Chen Su; Bjarne Worm; Alessia Paglialonga. Intraindividual Variability Measurement of Fine Manual Motor Skills in Children Using an Electronic Pegboard: Cohort Study. JMIR mHealth and uHealth 2019, 7, e12434 .

AMA Style

Diego Rivera, Antonio García, Jose Eugenio Ortega, Bernardo Alarcos, Kevin Van Der Meulen, Juan R Velasco, Cristina Del Barrio, Wu-Chen Su, Bjarne Worm, Alessia Paglialonga. Intraindividual Variability Measurement of Fine Manual Motor Skills in Children Using an Electronic Pegboard: Cohort Study. JMIR mHealth and uHealth. 2019; 7 (8):e12434.

Chicago/Turabian Style

Diego Rivera; Antonio García; Jose Eugenio Ortega; Bernardo Alarcos; Kevin Van Der Meulen; Juan R Velasco; Cristina Del Barrio; Wu-Chen Su; Bjarne Worm; Alessia Paglialonga. 2019. "Intraindividual Variability Measurement of Fine Manual Motor Skills in Children Using an Electronic Pegboard: Cohort Study." JMIR mHealth and uHealth 7, no. 8: e12434.

Journal article
Published: 07 January 2019 in IEEE Internet of Things Journal
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The growth of the Internet of Things (IoT) has favored the emergence of new applications and services. Consequently, new challenges in data security and protection have arisen because many IoT systems collect sensitive data that could be the target of attacks and intrusion attempts. Such is the case of smart toy platforms, where the loss of personal data is particularly serious because it involves children and therefore user privacy requires special protection. In this paper, we propose a series of security mechanisms to protect an IoT smart toy platform designed to help child development professionals in the early detection of psychomotor delays. Protecting information is crucially important in this environment, as a successful attack could be used to extract personal and health-related information. We have designed and built specific security mechanisms for the system by identifying the main threats in each submodule of the system, and then neutralizing or minimizing them. Due to the smart toys’ hardware restrictions, a specific encryption and authentication mechanism is proposed and presented here. All the mechanisms have been validated on the platform, and have proved to be a feasible and secure solution for this sensitive environment.

ACS Style

Diego Rivera; Antonio Garcia; Maria Luisa Martin Ruiz; Bernardo Alarcos; Juan Ramon Velasco; Ana Gomez Oliva. Secure Communications and Protected Data for a Internet of Things Smart Toy Platform. IEEE Internet of Things Journal 2019, 6, 3785 -3795.

AMA Style

Diego Rivera, Antonio Garcia, Maria Luisa Martin Ruiz, Bernardo Alarcos, Juan Ramon Velasco, Ana Gomez Oliva. Secure Communications and Protected Data for a Internet of Things Smart Toy Platform. IEEE Internet of Things Journal. 2019; 6 (2):3785-3795.

Chicago/Turabian Style

Diego Rivera; Antonio Garcia; Maria Luisa Martin Ruiz; Bernardo Alarcos; Juan Ramon Velasco; Ana Gomez Oliva. 2019. "Secure Communications and Protected Data for a Internet of Things Smart Toy Platform." IEEE Internet of Things Journal 6, no. 2: 3785-3795.

Journal article
Published: 24 September 2018 in IEEE Access
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Autonomous devices able to evaluate diverse situations without external help have become especially relevant in recent years because they can be used as an important source of relevant information about the activities performed by people (daily habits, sports performance, and health-related activities). Specifically, the use of this kind of device in childhood games might help in the early detection of developmental problems in children. In this paper, we propose a method for the detection and classification of movements performed with an object, based on an acceleration signal. This method can automatically generate patterns associated with a given movement using a set of reference signals, analyze sequences of acceleration trends, and classify the sequences according to the previously established patterns. This method has been implemented, and a series of experiments has been carried out using the data from a sensor-embedded toy. For the validation of the obtained results, we have, in parallel, developed two other classification systems based on popular techniques, i.e., a similarity search based on Euclidean distances and machine-learning techniques, specifically a support vector machine model. When comparing the results of each method, we show that our proposed method achieves a higher number of successes and higher accuracy in the detection and classification of isolated movement signals as well as in sequences of movements.

ACS Style

Diego Rivera; Luis Cruz-Piris; Susel Fernandez; Bernardo Alarcos; Antonio Garcia; Juan R. Velasco. A Novel Method for Automatic Detection and Classification of Movement Patterns in Short Duration Playing Activities. IEEE Access 2018, 6, 53409 -53425.

AMA Style

Diego Rivera, Luis Cruz-Piris, Susel Fernandez, Bernardo Alarcos, Antonio Garcia, Juan R. Velasco. A Novel Method for Automatic Detection and Classification of Movement Patterns in Short Duration Playing Activities. IEEE Access. 2018; 6 ():53409-53425.

Chicago/Turabian Style

Diego Rivera; Luis Cruz-Piris; Susel Fernandez; Bernardo Alarcos; Antonio Garcia; Juan R. Velasco. 2018. "A Novel Method for Automatic Detection and Classification of Movement Patterns in Short Duration Playing Activities." IEEE Access 6, no. : 53409-53425.

Journal article
Published: 20 November 2016 in Sensors
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In this paper, we describe the design considerations and implementation of a smart toy system, a technology for supporting the automatic recording and analysis for detecting developmental delays recognition when children play using the smart toy. To achieve this goal, we take advantage of the current commercial sensor features (reliability, low consumption, easy integration, etc.) to develop a series of sensor-based low-cost devices. Specifically, our prototype system consists of a tower of cubes augmented with wireless sensing capabilities and a mobile computing platform that collect the information sent from the cubes allowing the later analysis by childhood development professionals in order to verify a normal behaviour or to detect a potential disorder. This paper presents the requirements of the toy and discusses our choices in toy design, technology used, selected sensors, process to gather data from the sensors and generate information that will help in the decision-making and communication of the information to the collector system. In addition, we also describe the play activities the system supports.

ACS Style

Diego Rivera; Antonio García H.; Bernardo Alarcos; Juan R. Velasco; José Eugenio Ortega; Isaías Martínez-Yelmo. Smart Toys Designed for Detecting Developmental Delays. Sensors 2016, 16, 1953 .

AMA Style

Diego Rivera, Antonio García H., Bernardo Alarcos, Juan R. Velasco, José Eugenio Ortega, Isaías Martínez-Yelmo. Smart Toys Designed for Detecting Developmental Delays. Sensors. 2016; 16 (11):1953.

Chicago/Turabian Style

Diego Rivera; Antonio García H.; Bernardo Alarcos; Juan R. Velasco; José Eugenio Ortega; Isaías Martínez-Yelmo. 2016. "Smart Toys Designed for Detecting Developmental Delays." Sensors 16, no. 11: 1953.