{"id":11618,"date":"2020-12-23T10:55:20","date_gmt":"2020-12-23T16:55:20","guid":{"rendered":"https:\/\/saluddigital.com\/?p=11618"},"modified":"2025-10-21T14:02:25","modified_gmt":"2025-10-21T20:02:25","slug":"8-millones-de-usuarios-de-wearables","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/el-mundo-en-la-nube\/8-millones-de-usuarios-de-wearables\/","title":{"rendered":"Study collected heart health data from 8 million wearables users"},"content":{"rendered":"
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The study was published in the scientific journal The Lancet. Data from more than 8 million randomly selected wearables users over a 24-hour period were needed to conduct this research on heart rate variability.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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The study was published in December in the British journal under the title: \u201cHeart rate variability with photoplethysmography in 8 million individuals: a cross-sectional study\u201d. Among their main findings found through data obtained by wearables were that low-frequency power varies significantly between sexes, and the researchers observed an association between physical activity and heart rate variability metrics.<\/p>

The study explains that heart rate variability (the variation in the time interval between heartbeats), is a dynamic metric of the autonomic nervous system and one of the independent risk factors for cardiovascular death. Wearables or wrist devices are a useful tool for collecting this type of data; the wearables used in this study have photoplethysmography, which allows measuring and monitoring the substitutes of the nervous system activity through the analysis of the intervals between heartbeats. In response, the scientists explained that \u201cwe aimed to leverage wrist-worn trackers to derive and describe diverse measures of cardiac autonomic function among Fitbit device users (devices)\u201d.<\/p>

As this is a cross-sectional study, which includes statistical, demographic, and epidemiological data, the intervals between heartbeats were collected over a randomly selected 24-hour period from more than 8 million people. For the accuracy of the study, data from 90 days prior to the steps performed per day were collected, in addition to other essential data such as sex, BMI and age. Other parameters used for the heart rate variability (HRV) variable were rMSSD and SDRR.<\/p>

\u201cData from participants were analysed to establish the correlation between heart rate variability metrics and age, sex, time of day, and physical activity. We also determined benchmarks for heart rate variability (HRV) metrics among the users,\u201d they explain in the text.<\/p>

To learn more about the processes and results of this study you can consult for free through the following link: https:\/\/www.thelancet.com\/journals\/landig\/article\/PIIS2589-7500(20)30246-6\/fulltext#seccestitle140<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

El estudio fue publicado en la revista cient\u00edfica The Lancet. Los datos de m\u00e1s de 8 millones de usuarios de wearables elegidos al azar en un periodo de 24 horas fueron necesarios para conducir esta investigaci\u00f3n sobre la variabilidad de la frecuencia cardiaca. El estudio fue publicado en diciembre en la revista brit\u00e1nica con el t\u00edtulo: \u201cVariabilidad de la frecuencia card\u00edaca con fotopletismograf\u00eda en 8 millones de personas: un estudio transversal\u201d. Entre sus hallazgos principales encontrados a trav\u00e9s de datos obtenidos por wearables o fueron que la potencia de baja frecuencia var\u00eda significativamente entre sexos, adem\u00e1s los investigadores observaron una asociaci\u00f3n entre la actividad f\u00edsica y las m\u00e9tricas de variabilidad de frecuencia cardiaca. El estudio explica que la variabilidad de la frecuencia cardiaca (la variaci\u00f3n en el intervalo de tiempo entre latidos), es una m\u00e9trica din\u00e1mica del sistema nervioso aut\u00f3nomo y uno de los factores de riesgo independientes de muerte cardiovascular. Los wearables o dispositivos de mu\u00f1eca son una herramienta \u00fatil para recolectar este tipo de datos, los wearables utilizados en este estudio cuentan con fotopletismografia, lo que permite medir y monitorear los sustitutos de la actividad del sistema nervioso a trav\u00e9s del an\u00e1lisis de los intervalos entre latidos. Ante esto los cient\u00edficos explicaron que: \u201cNuestro objetivo era aprovechar los rastreadores de mu\u00f1eca para derivar y describir diversas medidas de la funci\u00f3n aut\u00f3noma card\u00edaca entre los usuarios de dispositivos Fitbit (los dispositivos utilizados)\u201d. Al ser un estudio transversal, lo que contempla son datos estad\u00edsticos, demogr\u00e1ficos y epidemiol\u00f3gicos, se recopilaron los intervalos entre latidos durante un periodo de 24 horas seleccionado aleatoriamente, de m\u00e1s de 8 millones de personas. Para la precisi\u00f3n del estudio se recopilaron datos de 90 d\u00edas anteriores de los pasos realizados al d\u00eda, adem\u00e1s de otros datos esenciales como el sexo, el IMC y la edad. Otros par\u00e1metros utilizados para la variable de variabilidad en frecuencia cardiaca (VFC) fueron rMSSD y SDRR. \u201cLos datos de los participantes se analizaron para establecer la correlaci\u00f3n entre las m\u00e9tricas de variabilidad de la frecuencia card\u00edaca y la edad, el sexo, la hora del d\u00eda y la actividad f\u00edsica. Tambi\u00e9n determinamos puntos de referencia para las m\u00e9tricas de variabilidad de la frecuencia card\u00edaca entre los usuarios\u201d, explican en el estudio. Para conocer m\u00e1s sobre los procesos y los resultados de este estudio puedes consultar de forma gratuita y libre a trav\u00e9s del siguiente enlace: https:\/\/www.thelancet.com\/journals\/landig\/article\/PIIS2589-7500(20)30246-6\/fulltext#seccestitle140<\/p>","protected":false},"author":1,"featured_media":11621,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[156,155,3401,1418],"tags":[145],"class_list":["post-11618","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-data","category-el-mundo-en-la-nube","category-iotapps","category-resena-de-publicaciones-cientificas","tag-noticias"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/11618","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/comments?post=11618"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/11618\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/11621"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=11618"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=11618"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=11618"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}