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Analysis of institutional authors

Becerra, AlvaroCorresponding AuthorDaza, RobertoAuthorCobos, RuthAuthorMorales, AythamiAuthorFierrez, JulianAuthor

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December 17, 2025
Publications
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Proceedings Paper
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AI-Based Multimodal Biometrics for Detecting Smartphone Distractions: Application to Online Learning

Publicated to: Advances In Computational Intelligence, Iwann 2017, Pt Ii. 16063 31-46 - 2026-01-01 16063(), DOI: 10.1007/978-3-032-03870-8_3

Authors:

Becerra, Alvaro; Daza, Roberto; Cobos, Ruth; Morales, Aythami; Cukurova, Mutlu; Fierrez, Julian
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Affiliations

UCL, London, England - Author
Univ Autonoma Madrid, Madrid, Spain - Author

Abstract

This work investigates the use of multimodal biometrics to detect distractions caused by smartphone use during tasks that require sustained attention, with a focus on computer-based online learning. Although the methods are applicable to various domains, such as autonomous driving, we focus on the challenges learners face in maintaining engagement amid internal (e.g. motivation), system-related (e.g., course design) and contextual (e.g., smartphone use) factors. Traditional learning platforms often lack detailed behavioral data, but Multimodal Learning Analytics (MMLA) and biosensors provide new insights into learner attention. We propose an AI-based approach that leverages physiological signals and head pose data to detect phone use. Our results show that single biometric signals, such as brain waves or heart rate, offer limited accuracy, while head pose alone achieves 87%. A multimodal model that combines all signals reaches accuracy 91%, highlighting the benefits of integration. We conclude by discussing the implications and limitations of deploying these models for real-time support in online learning environments.
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Keywords

Artificial intelligenceBiometricsBiosensorsLearning analyticsMachine learningMultimodal learning analyticsOnline learningPhone

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2017, PT II due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2026, it was in position , thus managing to position itself as a Q2 (Segundo Cuartil), in the category Computer Science (Miscellaneous).

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-05:

  • WoS: 1
  • Scopus: 1
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-05:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 7.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 7 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: United Kingdom.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (BECERRA JIMENEZ, ALVARO) and Last Author (FIERREZ AGUILAR, JULIAN).

the author responsible for correspondence tasks has been BECERRA JIMENEZ, ALVARO.

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Awards linked to the item

Support by projects: Catedra ENIA UAM-VERIDAS en IA Responsable (NextGenerationEU PRTR TSI-100927-2023-2), HumanCAIC (TED2021-131787B-I00 MICINN) and SNOLA (RED2022-134284-T).
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