首页> 外国专利> SYSTEM AND METHODS UTILIZING ARTIFICIAL INTELLIGENCE ALGORITHMS TO ANALYZE WEARABLE ACTIVITY TRACKER DATA

SYSTEM AND METHODS UTILIZING ARTIFICIAL INTELLIGENCE ALGORITHMS TO ANALYZE WEARABLE ACTIVITY TRACKER DATA

机译:利用人工智能算法利用人工智能算法来分析可穿戴活动跟踪器数据的系统和方法

摘要

A system and method are disclosed for monitoring health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In some embodiments, the input vector can also include social determinants data and/or demographic data. The output of the deep learning algorithms provides classifiers that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.
机译:公开了一种基于由可穿戴设备(例如活动跟踪器或智能手表)收集的数据监测健康状况的系统和方法。 深度学习算法被配置为处理包括可穿戴设备收集的监视参数数据的输入向量以及从对应于登记到可穿戴设备的用户帐户的健康记录获得的嵌入数据。 在一些实施例中,输入载体还可以包括社会决定因素数据和/或人口统计数据。 深度学习算法的输出提供了代表可穿戴设备的用户具有底层健康状况的概率的分类器。 如果检测到任何底层的健康状况,则可以通过可穿戴设备或相关应用程序或技术或间接地通过与用户相关联的初级保险提供商直接通知用户。

著录项

  • 公开/公告号WO2022006103A1

    专利类型

  • 公开/公告日2022-01-06

    原文格式PDF

  • 申请/专利权人 AETNA INC.;

    申请/专利号WO2021US39611

  • 申请日2021-06-29

  • 分类号G16H20/30;G16H50/70;

  • 国家 US

  • 入库时间 2022-08-24 23:16:24

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