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Un conjunto continuo de datos del mundo real que comprende la variabilidad de la frecuencia cardíaca basada en
Aitolkyn Baigutanova1,2, Sungkyu Park3,4, Marios Constantinides5,6
1Korea Advanced Institute of Science and Technology (KAIST), School of Computing, Daejeon, 34141, Republic of Korea.
Scientific data
|August 23, 2025
Resumen
Este estudio introduce un nuevo conjunto de datos de la variabilidad del ritmo cardíaco en el mundo real (HRV) de los relojes inteligentes. Estos datos pueden ayudar a desarrollar análisis predictivos de salud utilizando tecnología portátil y patrones de sueño.
Área de la Ciencia:
- Fisiología e Informática de la Salud
- Tecnología portátil
- Ciencia de los datos biomédicos
Sus antecedentes:
- El monitoreo de la variabilidad de la frecuencia cardíaca (VRC) ofrece información sobre las condiciones de salud.
- Los conjuntos de datos de HRV existentes carecen de complejidad en el mundo real, ya que se recopilan en entornos clínicos controlados.
- Se necesitan datos fisiológicos robustos para el análisis de la salud.
Objetivo del estudio:
- Para recopilar y validar datos fisiológicos y de movimiento en el mundo real utilizando relojes inteligentes.
- Establecer un conjunto de datos de referencia para los registros de VHC en la naturaleza.
- Apoyar el desarrollo de análisis predictivos de la salud que integren datos portátiles y patrones de sueño.
Principales métodos:
- Recogió señales fisiológicas y de movimiento continuas de 49 adultos sanos durante cuatro semanas usando relojes inteligentes.
- Registros de muestreo a intervalos de 100 ms para el cálculo de la VRC a corto plazo a partir de segmentos de 5 minutos.
- Datos validados mediante análisis de la frecuencia de la señal, correlación sensor-HRV y comprobaciones de la distribución de las características basadas en la literatura.
Principales resultados:
- Recogió con éxito un nuevo conjunto de datos de grabaciones continuas de relojes inteligentes en un entorno real.
- Validación de la calidad y fiabilidad de los datos fisiológicos y de movimiento recogidos.
- Distribuciones esperadas de la VCR y de las características relacionadas con el sueño consistentes con la literatura existente.
Conclusiones:
- El conjunto de datos desarrollado proporciona un recurso valioso para la evaluación comparativa de la VHR en la naturaleza.
- Permite futuras investigaciones en el análisis de datos fisiológicos del mundo real para obtener información sobre la salud.
- Apoya los avances en análisis predictivos para el monitoreo de la salud utilizando tecnología portátil y datos de sueño.
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