Gesture-Based Children Computer Interaction for Inclusive Education: A Systematic Literature Review

Torres-Carrión, Pablo; González-González, Carina S.; Bravo, César Bernal; Moro, Alfonso Infante

doi:10.1007/978-3-030-05532-5_10

Cited by 10 publications

(15 citation statements)

References 55 publications

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“…The literature review was conducted using the recommendations given by Khan et al [52], the methodology proposed by Torres-Carrión [53,54], and the protocol proposed by Moher et al [55]. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram [55] is shown in Figure 2.…”

Section: The Literature Review: Selection Criteriamentioning

confidence: 99%

“…To conduct an appropriate search, it is important to focus our attention on the real context of the research, a method proposed by Torres-Carrión [54], the so-called conceptual mindfact (mentefacto conceptual), which can be used to organize the scientific thesaurus of the research theme [53]. Figure 3 describes the conceptual mindfact used in this work to focus and constrain the topic to MRI Brain Algorithm Difference Ischemic and Demyelinating Diseases and obtain an adequate semantic search structure of the literature in the relevant scientific databases.…”

Section: The Literature Review: Selection Criteriamentioning

confidence: 99%

“…Figure 3 describes the conceptual mindfact used in this work to focus and constrain the topic to MRI Brain Algorithm Difference Ischemic and Demyelinating Diseases and obtain an adequate semantic search structure of the literature in the relevant scientific databases. Conceptual mindfact (mentefacto conceptual) according to [53,54]. This allows the key word identification for a systemic search of the literature in scientific databases.…”

Section: The Literature Review: Selection Criteriamentioning

confidence: 99%

See 2 more Smart Citations

MR Images, Brain Lesions, and Deep Learning

2021

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Medical brain image analysis is a necessary step in computer-assisted/computer-aided diagnosis (CAD) systems. Advancements in both hardware and software in the past few years have led to improved segmentation and classification of various diseases. In the present work, we review the published literature on systems and algorithms that allow for classification, identification, and detection of white matter hyperintensities (WMHs) of brain magnetic resonance (MR) images, specifically in cases of ischemic stroke and demyelinating diseases. For the selection criteria, we used bibliometric networks. Of a total of 140 documents, we selected 38 articles that deal with the main objectives of this study. Based on the analysis and discussion of the revised documents, there is constant growth in the research and development of new deep learning models to achieve the highest accuracy and reliability of the segmentation of ischemic and demyelinating lesions. Models with good performance metrics (e.g., Dice similarity coefficient, DSC: 0.99) were found; however, there is little practical application due to the use of small datasets and a lack of reproducibility. Therefore, the main conclusion is that there should be multidisciplinary research groups to overcome the gap between CAD developments and their deployment in the clinical environment.

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Section: The Literature Review: Selection Criteriamentioning

confidence: 99%

Section: The Literature Review: Selection Criteriamentioning

confidence: 99%

Section: The Literature Review: Selection Criteriamentioning

confidence: 99%

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MR Images, Brain Lesions, and Deep Learning

2021

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“…However, we found studies which investigate topics related to NUI. Torres‐Carrión et al [16 ] conducted an SLR to investigate state‐of‐the‐art regarding gesture‐based children's–computer interactions, and how they may help in the inclusive education. The result shows that design guidelines for natural interfaces are applied in studies and highlight human cognitive and sensory factors, not considering emotional factors.…”

Section: Related Workmentioning

confidence: 99%

Usability and user experience evaluation of natural user interfaces: a systematic mapping study

Guerino

Valentim

2020

IET softw.

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Natural user interface (NUI) is considered a recent topic in human–computer interaction (HCI) and provides innovative forms of interaction, which are performed through natural movements of the human body like gestures, voice, and gaze. In the software development process, usability and user eXperience (UX) evaluations are a relevant step, since they evaluate several aspects of the system, such as efficiency, effectiveness, user satisfaction, and immersion. Thus, the goal of the authors’ systematic mapping study (SMS) is to identify usability and UX evaluation technologies used by researchers and developers in software with NUIs. Their SMS selected 56 papers containing evaluation technologies for NUI. Overall, the authors identified 30 different usability and UX evaluation technologies for NUI. The analysis of these technologies reveals most of them are used to evaluate software in general, without considering the specificities of NUI. Besides, most technologies evaluate only one aspect, Usability or UX. In other words, these technologies do not consider Usability and UX together. For future work, they intend to develop an evaluation technology for NUIs that fills the gaps identified in their SMS and combining Usability and UX.

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“…Down syndrome (DS) is a genetic disorder that causes a reduction in cognitive abilities to varying degrees. The cognitive visual-motor ability (CVMA) is one of the most sensitive, and it is a fact that this cognitive ability can be improved in people with DS [1,2,3,4]. In general, CVMA refers to the ability to integrate vision with the motor system, a requirement to comply with visually guided motor actions.…”

Section: Introductionmentioning

confidence: 99%

Improving Cognitive Visual-Motor Abilities in Individuals with Down Syndrome

Torres-Carrión

González-González

Toledo-Delgado

et al. 2019

Sensors

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Down syndrome causes a reduction in cognitive abilities, with visual-motor skills being particularly affected. In this work, we have focused on this skill in order to stimulate better learning. The proposal relies on stimulating the cognitive visual-motor skills of individuals with Down Syndrome (DS) using exercises with a gestural interaction platform based on the KINECT sensor named TANGO:H, the goal being to improve them. To validate the proposal, an experimental single-case study method was designed using two groups: a control group and an experimental one, with similar cognitive ages. Didactic exercises were provided to the experimental group using visual cognitive stimulation. These exercises were created on the TANGO:H Designer, a platform that was designed for gestural interaction using the KINECT sensor. As a result, TANGO:H allows for visual-motor cognitive stimulation through the movement of hands, arms, feet and head. The “Illinois Test of Psycholinguistic Abilities (ITPA)” was applied to both groups as a pre-test and post-test in its four reference sections: visual comprehension, visual-motor sequential memory, visual association, and visual integration. Two checks were made, one using the longitudinal comparison of the pre-test/post-test of the experimental group, and another that relied on comparing the difference of the means of the pre-test/post-test. We also used an observational methodology for the working sessions from the experimental group. Although the statistical results do not show significant differences between the two groups, the results of the observations exhibited an improvement in visual-motor cognitive skills.

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Gesture-Based Children Computer Interaction for Inclusive Education: A Systematic Literature Review

Cited by 10 publications

References 55 publications

MR Images, Brain Lesions, and Deep Learning

MR Images, Brain Lesions, and Deep Learning

Usability and user experience evaluation of natural user interfaces: a systematic mapping study

Improving Cognitive Visual-Motor Abilities in Individuals with Down Syndrome

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