Rol de las tecnologías en el reconocimiento de movimientos generales en neonatos de hasta 20 semanas post término.
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| Title: | Rol de las tecnologías en el reconocimiento de movimientos generales en neonatos de hasta 20 semanas post término. |
|---|---|
| Alternate Title: | Role of technologies in the recognition of general movements in neonates up to 20 weeks post-term. |
| Authors: | Venegas-Norambuena, Edgardo Emanuel1 emanuel.mellarobles@gmail.com, Calderón-Petricic, Camila Fernanda, Mella-Robles, Emanuel Franco2 |
| Source: | Andes Pediatrica. may/jun2026, Vol. 97 Issue 3, p515-524. 10p. |
| Subjects: | Artificial intelligence, Deep learning, Neural development, Newborn infants, Application software, Neurorehabilitation, Infant psychology |
| Abstract (English): | The assessment of General Movements (GMs) has been used in clinical practice for the early detection of neurological disorders in neonates; however, its application requires a high level of expertise, time, and resources. Given these limitations, video-based technologies have emerged as an alternative approach for optimizing this evaluation. The objective of this Rapid Review is to update the role that technologies play in recognizing general movements and their relationship with the generation of clinical diagnoses. Four databases were reviewed (PubMed, Scopus, Web of Science, and BVS) following the PRISMA methodology. Studies focusing on neonates up to 20 weeks post-term that linked GM assessment with video-based and technology-assisted approaches, published between 2019 and 2023 in English, were included. A total of 30 studies were selected based on their methodological design and type of technology. The findings show that technological approaches, especially those based on deep learning and Artificial Intelligence (AI), contribute to earlier detection of neurodevelopmental disorders, are associated with the creation of automated databases, and improve access to assessment. The main benefits identified include optimization of clinical care, cost reduction, greater comfort for users and healthcare professionals, and improved opportunities for early intervention. In conclusion, technology applied to the assessment of general movements represents a significant advancement in the field of pediatric neurorehabilitation, supporting diagnostic processes, timely treatment, and facilitating implementation across diverse clinical settings. [ABSTRACT FROM AUTHOR] |
| Abstract (Spanish): | La evaluación de los movimientos generales (GMs) ha sido empleada en la práctica clínica para la detección temprana de trastornos neurológicos en neonatos, aunque su aplicación requiere alta especialización, tiempo y recursos. Dado estas limitaciones, el uso de tecnologías asociadas a video se presentan como una alternativa emergente para optimizar esta evaluación. El objetivo de esta Revisión Rápida es actualizar el rol que cumplen las tecnologías en el reconocimiento de los movimientos generales y su relación con la generación de diagnósticos clínicos. Se revisaron cuatro bases de datos, PubMed, Scopus, Web of Science y BVS, aplicando el método PRISMA. Se incluyeron estudios centrados en neonatos hasta las 20 semanas post término que relacionaran la evaluación de GMs con tecnologías que utilizaran video y apoyo tecnológico, publicados entre 2019-2023 en idioma inglés. Se seleccionaron 30 estudios considerando su diseño metodológico y tipo de tecnología. Los hallazgos evidencian que las tecnologías, especialmente aquellas basadas en el aprendizaje profundo e Inteligencia Artificial (IA), contribuyen a una detección más temprana de alteraciones del neurodesarrollo, se vinculan a la creación de bases de datos automatizadas, y mejoran la accesibilidad a la evaluación. Los principales beneficios identificados incluyen la optimización de la atención clínica, reducción de costos, mayor comodidad para usuarios y profesionales, y mejora en las oportunidades de intervención precoz. En conclusión, la tecnología aplicada a la evaluación de movimientos generales representa un avance significativo en el ámbito de la neurorehabilitación infantil, al apoyar los procesos diagnósticos, tratamiento oportuno y facilitar su implementación en diversos contextos clínicos. [ABSTRACT FROM AUTHOR] |
| Copyright of Andes Pediatrica is the property of Revista Chilena de Pediatria and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | MedicLatina |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: lth DbLabel: MedicLatina An: 195298128 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Rol de las tecnologías en el reconocimiento de movimientos generales en neonatos de hasta 20 semanas post término. – Name: TitleAlt Label: Alternate Title Group: TiAlt Data: Role of technologies in the recognition of general movements in neonates up to 20 weeks post-term. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Venegas-Norambuena%2C+Edgardo+Emanuel%22">Venegas-Norambuena, Edgardo Emanuel</searchLink><relatesTo>1</relatesTo><i> emanuel.mellarobles@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Calderón-Petricic%2C+Camila+Fernanda%22">Calderón-Petricic, Camila Fernanda</searchLink><br /><searchLink fieldCode="AR" term="%22Mella-Robles%2C+Emanuel+Franco%22">Mella-Robles, Emanuel Franco</searchLink><relatesTo>2</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Andes+Pediatrica%22">Andes Pediatrica</searchLink>. may/jun2026, Vol. 97 Issue 3, p515-524. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink><br /><searchLink fieldCode="DE" term="%22Neural+development%22">Neural development</searchLink><br /><searchLink fieldCode="DE" term="%22Newborn+infants%22">Newborn infants</searchLink><br /><searchLink fieldCode="DE" term="%22Application+software%22">Application software</searchLink><br /><searchLink fieldCode="DE" term="%22Neurorehabilitation%22">Neurorehabilitation</searchLink><br /><searchLink fieldCode="DE" term="%22Infant+psychology%22">Infant psychology</searchLink> – Name: Abstract Label: Abstract (English) Group: Ab Data: The assessment of General Movements (GMs) has been used in clinical practice for the early detection of neurological disorders in neonates; however, its application requires a high level of expertise, time, and resources. Given these limitations, video-based technologies have emerged as an alternative approach for optimizing this evaluation. The objective of this Rapid Review is to update the role that technologies play in recognizing general movements and their relationship with the generation of clinical diagnoses. Four databases were reviewed (PubMed, Scopus, Web of Science, and BVS) following the PRISMA methodology. Studies focusing on neonates up to 20 weeks post-term that linked GM assessment with video-based and technology-assisted approaches, published between 2019 and 2023 in English, were included. A total of 30 studies were selected based on their methodological design and type of technology. The findings show that technological approaches, especially those based on deep learning and Artificial Intelligence (AI), contribute to earlier detection of neurodevelopmental disorders, are associated with the creation of automated databases, and improve access to assessment. The main benefits identified include optimization of clinical care, cost reduction, greater comfort for users and healthcare professionals, and improved opportunities for early intervention. In conclusion, technology applied to the assessment of general movements represents a significant advancement in the field of pediatric neurorehabilitation, supporting diagnostic processes, timely treatment, and facilitating implementation across diverse clinical settings. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Abstract (Spanish) Group: Ab Data: La evaluación de los movimientos generales (GMs) ha sido empleada en la práctica clínica para la detección temprana de trastornos neurológicos en neonatos, aunque su aplicación requiere alta especialización, tiempo y recursos. Dado estas limitaciones, el uso de tecnologías asociadas a video se presentan como una alternativa emergente para optimizar esta evaluación. El objetivo de esta Revisión Rápida es actualizar el rol que cumplen las tecnologías en el reconocimiento de los movimientos generales y su relación con la generación de diagnósticos clínicos. Se revisaron cuatro bases de datos, PubMed, Scopus, Web of Science y BVS, aplicando el método PRISMA. Se incluyeron estudios centrados en neonatos hasta las 20 semanas post término que relacionaran la evaluación de GMs con tecnologías que utilizaran video y apoyo tecnológico, publicados entre 2019-2023 en idioma inglés. Se seleccionaron 30 estudios considerando su diseño metodológico y tipo de tecnología. Los hallazgos evidencian que las tecnologías, especialmente aquellas basadas en el aprendizaje profundo e Inteligencia Artificial (IA), contribuyen a una detección más temprana de alteraciones del neurodesarrollo, se vinculan a la creación de bases de datos automatizadas, y mejoran la accesibilidad a la evaluación. Los principales beneficios identificados incluyen la optimización de la atención clínica, reducción de costos, mayor comodidad para usuarios y profesionales, y mejora en las oportunidades de intervención precoz. En conclusión, la tecnología aplicada a la evaluación de movimientos generales representa un avance significativo en el ámbito de la neurorehabilitación infantil, al apoyar los procesos diagnósticos, tratamiento oportuno y facilitar su implementación en diversos contextos clínicos. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Andes Pediatrica is the property of Revista Chilena de Pediatria and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.32641/andespediatr.v97i3.5858 Languages: – Code: spa Text: Spanish PhysicalDescription: Pagination: PageCount: 10 StartPage: 515 Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Deep learning Type: general – SubjectFull: Neural development Type: general – SubjectFull: Newborn infants Type: general – SubjectFull: Application software Type: general – SubjectFull: Neurorehabilitation Type: general – SubjectFull: Infant psychology Type: general Titles: – TitleFull: Rol de las tecnologías en el reconocimiento de movimientos generales en neonatos de hasta 20 semanas post término. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Venegas-Norambuena, Edgardo Emanuel – PersonEntity: Name: NameFull: Calderón-Petricic, Camila Fernanda – PersonEntity: Name: NameFull: Mella-Robles, Emanuel Franco IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: may/jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 24526045 Numbering: – Type: volume Value: 97 – Type: issue Value: 3 Titles: – TitleFull: Andes Pediatrica Type: main |
| ResultId | 1 |
