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    Physical activity inference from environmental metrics
    1.
    发明授权
    Physical activity inference from environmental metrics 有权

    公开(公告)号：US10984440B2

    公开(公告)日：2021-04-20

    申请号：US16104683

    申请日：2018-08-17

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Julia Maureen Letchner ,  Scott Saponas ,  Alice Jane Brush ,  Aman Kansal ,  Daniel Morris

    IPC: G06Q30/02 ,  G06Q30/06 ,  G06F16/95

    Abstract: Portable devices include environmental sensors that generate metrics about the environment (e.g., accelerometers detecting impulses and vibration, and GPS receivers detecting position and velocity). Such devices often use environmental metrics to extract user input directed at the device by the user, and status information about the device and the environment. Presented herein are techniques for using environmental metrics to infer physical activities performed by the user while attached to the device. For example, jogging may be inferred from regular, strong impulses and typical jogging speed; walking may be inferred from regular, weak impulses and typical walking speed; and riding in a vehicle may be inferred from low-level vibrations and high speed (optionally identifying the type of vehicle ridden by the user). Based on these inferences, the device may automatically present applications and/or or adjust user interfaces suitable for the user's physical activity, rather than responsive to user input.

    Wearable pulse sensing device signal quality estimation
    2.
    发明授权
    Wearable pulse sensing device signal quality estimation 有权

    公开(公告)号：US10765331B2

    公开(公告)日：2020-09-08

    申请号：US14750037

    申请日：2015-06-25

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Daniel Morris ,  Sumit Basu ,  Jeremiah Wander ,  Gregory R. Smith ,  T. Scott Saponas

    IPC: A61B5/024 ,  A61B5/00 ,  A61B5/021

    Abstract: A first data window of a pulse waveform signal comprising a first number of samples is analyzed to determine a level of confidence that a pulse sensing device is placed correctly. If an initial level of confidence is met, the user is given positive feedback, and a second data window of a pulse waveform signal comprising a second, larger number of samples is analyzed. If an increased level of confidence is met, the user is given increased positive feedback. If a level of confidence is not met, the user is given negative feedback. If a final level of confidence is met, the user is given feedback that the pulse sensing device is placed correctly.

    Blood pressure estimation by wearable computing device
    3.
    发明授权
    Blood pressure estimation by wearable computing device 有权

    公开(公告)号：US10716518B2

    公开(公告)日：2020-07-21

    申请号：US15443969

    申请日：2017-02-27

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Sumit Basu ,  Daniel Morris ,  Jeremiah Wander

    IPC: A61B5/00 ,  A61B5/022 ,  A61B5/021 ,  A61B5/0245 ,  A61B5/0402 ,  A61B5/024

    Abstract: According to one aspect of the present disclosure, a method for estimating blood pressure is provided, comprising training a machine learning model on a cohort data set. The cohort data set may include subject-specific contextual data, time-varying features, and blood pressure measurements for a plurality of subjects. The method may include receiving contextual data for a specific subject, wherein the contextual data includes medical history data of the subject. The method may further include personalizing the machine learning model to the subject based on the contextual data. The method may include calibrating the machine learning model to the subject based on a set of time-varying features and blood pressure measurements of the subject. In addition, the method may include using the machine learning model and the time-varying features for the subject to generate a blood pressure estimate.

    PHYSICAL ACTIVITY INFERENCE FROM ENVIRONMENTAL METRICS
    5.
    发明申请
    PHYSICAL ACTIVITY INFERENCE FROM ENVIRONMENTAL METRICS 审中-公开

    公开(公告)号：US20180357662A1

    公开(公告)日：2018-12-13

    申请号：US16104683

    申请日：2018-08-17

    Applicant: Microsoft Technology Licensing, LLC

    Inventor： Julia Maureen Letchner ,  Scott Saponas ,  Alice Jane Brush ,  Aman Kansal ,  Daniel Morris

    IPC: G06Q30/02 ,  G06F17/30 ,  G06Q30/06

    CPC classification number: G06Q30/0242 ,  G06F17/30861 ,  G06Q30/0254 ,  G06Q30/0277 ,  G06Q30/0613

    Abstract: Portable devices include environmental sensors that generate metrics about the environment (e.g., accelerometers detecting impulses and vibration, and GPS receivers detecting position and velocity). Such devices often use environmental metrics to extract user input directed at the device by the user, and status information about the device and the environment. Presented herein are techniques for using environmental metrics to infer physical activities performed by the user while attached to the device. For example, jogging may be inferred from regular, strong impulses and typical jogging speed; walking may be inferred from regular, weak impulses and typical walking speed; and riding in a vehicle may be inferred from low-level vibrations and high speed (optionally identifying the type of vehicle ridden by the user). Based on these inferences, the device may automatically present applications and/or or adjust user interfaces suitable for the user's physical activity, rather than responsive to user input.

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