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Análisis de movimiento basado en sensores para la detección de demencia: una revisión sistemática

Zongyi Jiang1, Maryam Ghahramani1,2, Nathan M D'Cunha3,4

  • 1Faculty of Science and Technology, University of Canberra, Canberra, ACT, Australia.

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Resumen
Este resumen es generado por máquina.

Los sensores de movimiento muestran potencial para la detección temprana de demencia mediante el análisis de la marcha y las actividades diarias. Esta revisión destaca los tipos de sensores, tareas y métodos para mejorar el diagnóstico, allanando el camino para intervenciones más precisas y oportunas.

Palabras clave:
demenciadiagnósticoaprendizaje automáticoanálisis de movimientotecnologías de sensoresanálisis estadístico

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Área de la Ciencia:

  • Ingeniería Biomédica
  • Neurociencia
  • Gerontología

Sus antecedentes:

  • El diagnóstico de demencia depende de cambios cognitivos y motores sutiles.
  • La detección temprana es fundamental para un manejo y atención eficaces.
  • La tecnología de sensores ofrece nuevas vías para el monitoreo continuo del movimiento.

Objetivo del estudio:

  • Revisar sistemáticamente los métodos de detección de demencia basados en el movimiento.
  • Analizar los tipos de sensores, ubicaciones, tareas, características y enfoques analíticos.
  • Identificar lagunas en la investigación y guiar estudios futuros en la evaluación del movimiento para la demencia.

Principales métodos:

  • Revisión sistemática de la literatura de enero de 2015 a mayo de 2025.
  • Se buscaron en PubMed, Web of Science, IEEE Xplore y Scopus.
  • Se incluyeron 23 artículos centrados exclusivamente en la detección de demencia basada en el movimiento.

Principales resultados:

  • Se utilizaron varios sensores (IMU, alfombras de presión, cámaras) y ubicaciones.
  • Las tareas de movimiento incluyeron la marcha, las actividades de la vida diaria y el control postural.
  • Se emplearon el aprendizaje automático y los análisis estadísticos, que mostraron que las características del movimiento son indicadores sensibles de demencia.

Conclusiones:

  • Las evaluaciones basadas en el movimiento tienen un potencial significativo para la detección de demencia.
  • Se necesita estandarización de métodos para mejorar la reproducibilidad.
  • La investigación futura debe centrarse en datos a gran escala, integración multimodal e IA explicable.