公开(公告)号：US20220117549A1

公开(公告)日：2022-04-21

申请号：US17564301

申请日：2021-12-29

Applicant: Fitbit, Inc.

Inventor： Man-Chi Liu ,  Alexander Statan ,  Derrick Steven Vickers ,  Paul Francis Stetson ,  Elena Perez ,  James Horng-Kuang Lin ,  Belen Lafon ,  Lindsey Michelle Sunden

IPC: A61B5/00 ,  A61B5/346 ,  H04Q9/00 ,  G16H40/60 ,  A61B5/0205 ,  A61B5/0531 ,  H04B1/3827

Abstract: Arousal events can be determined for a user associated with a wearable device, such as a user wearing a wearable computing device including one or more sensors. The one or more sensors may obtain EDA information that may determine a sympathetic nervous system response of the user, which may be responsive to an arousal event or an activation. Detection of events that increase the EDA response may provide information to the user regarding arousal events and provide recommendations to the user to address the arousal events to decrease their response.

公开(公告)号：US11191466B1

公开(公告)日：2021-12-07

申请号：US16457582

申请日：2019-06-28

Applicant: Fitbit, Inc.

Inventor： Conor Joseph Heneghan ,  Alexander Statan ,  Jonathan David Charlesworth

IPC: A61B5/16 ,  A61B5/0205 ,  A61B5/00 ,  A61B5/11 ,  A61B5/145 ,  A61B5/01 ,  G16H50/30 ,  A61B5/1455 ,  A61B5/024

Abstract: Physiological variables, metrics, biomarkers, and other data points can be used, in connection with a non-invasive wearable device, to screen for, and predict, mental health issues and cognitive states. In addition to metrics such as heart rate, sleep data, activity level, gamification data, and the like, information such as text message and email data, as well as vocal data obtained through a phone and/or a microphone, may be analyzed, provided user authorization. Applying predictive modeling, one or more of the monitored metrics can be correlated with mental states and disorders. Identified patterns can be used to update the predictive models, such as via machine learning-trained models, as well as to update individual event predictions. Information about the mental state predictions, and updates thereto, can be surfaced to the user accordingly.

公开(公告)号：US10555698B2

公开(公告)日：2020-02-11

申请号：US16155139

申请日：2018-10-09

Applicant: Fitbit, Inc.

Inventor： Allison Maya Russell ,  Zachary Todd Beattie ,  Alexander Statan ,  Emma Jane Quinn

IPC: A61B5/00 ,  A61B5/02 ,  A61B5/0205 ,  A61B5/04

Abstract: Assessing the sleep quality of a user in association with an electronic device with one or more physiological sensors includes detecting an attempt by the user to fall asleep, and collecting physiological information associated with the user. The disclosed method of assessing sleep quality may include determining respective values for one or more sleep quality metrics, including a first set of sleep quality metrics associated with sleep quality of a plurality of users, and a second set of sleep quality metrics associated with historical sleep quality of the user, based at least in part on the collected physiological information and at least one wakeful resting heart rate of the user, and determining a unified score for sleep quality of the user, based at least in part on the respective values of the one or more sleep quality metrics.

公开(公告)号：US20190254589A1

公开(公告)日：2019-08-22

申请号：US16155139

申请日：2018-10-09

Applicant: Fitbit, Inc.

Inventor： Allison Maya Russell ,  Zachary Todd Beattie ,  Alexander Statan ,  Emma Jane Quinn

IPC: A61B5/00 ,  A61B5/02

Abstract: Assessing the sleep quality of a user in association with an electronic device with one or more physiological sensors includes detecting an attempt by the user to fall asleep, and collecting physiological information associated with the user. The disclosed method of assessing sleep quality may include determining respective values for one or more sleep quality metrics, including a first set of sleep quality metrics associated with sleep quality of a plurality of users, and a second set of sleep quality metrics associated with historical sleep quality of the user, based at least in part on the collected physiological information and at least one wakeful resting heart rate of the user, and determining a unified score for sleep quality of the user, based at least in part on the respective values of the one or more sleep quality metrics.