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Analysis of institutional authors

Santonja A.AuthorSantonja, AAuthorSánchez-Diaz, CAuthor

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Article

Classification Predictive Model for Air Leak Detection in Endoworm Enteroscopy System

Publicated to:Sensors. 22 (14): 5211- - 2022-07-01 22(14), DOI: 10.3390/s22145211

Authors: Zazo-Manzaneque, R; Pons-Beltrán, V; Vidaurre, A; Santonja, A; Sánchez-Díaz, C

Affiliations

Biomed Res Networking Ctr Bioengn Biomat & Nanome - Author
IIS Hosp La Fe, Gastrointestinal Endoscopy Res Grp - Author
Univ Politecn Valencia, Ctr Biomat & Tissue Engn CBIT - Author
Univ Politecn Valencia, Dept Elect Engn - Author
Univ Politecn Valencia, Sch Design Engn ETSID - Author
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Abstract

Current enteroscopy techniques present complications that are intended to be improved with the development of a new semi-automatic device called Endoworm. It consists of two different types of inflatable cavities. For its correct operation, it is essential to detect in real time if the inflatable cavities are malfunctioning (presence of air leakage). Two classification predictive models were obtained, one for each cavity typology, which must discern between the Right or Leak states. The cavity pressure signals were digitally processed, from which a set of features were extracted and selected. The predictive models were obtained from the features, and a prior classification of the signals between the two possible states was used as input to different supervised machine learning algorithms. The accuracy obtained from the classification predictive model for cavities of the balloon-type was 99.62%, while that of the bellows-type was 100%, representing an encouraging result. Once the models are validated with data generated in animal model tests and subsequently in exploratory clinical tests, their incorporation in the software device will ensure patient safety during small bowel exploration.

Keywords

Classification predictive modelsDigital signal processingDouble-balloon enteroscopyEfficacyEnteroscopyFeature extractionFeature-selectionInflatable cavitiesMedical deviceReal-time detection systemSafetySoft robotSpiral enteroscopyTime

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Sensors 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, 2022, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Analytical Chemistry.

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 2025-06-29:

  • 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: 10 (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:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.

Leadership analysis of institutional authors

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 (Zazo-Manzaneque, R) and Last Author (Sánchez Díaz, Carlos).

the author responsible for correspondence tasks has been Zazo-Manzaneque, R.