-
公开(公告)号：US11877861B2
公开(公告)日：2024-01-23
申请号：US17690369
申请日：2022-03-09
Applicant: Fitbit, Inc.
Inventor： Conor Joseph Heneghan , Jacob Anthony Arnold , Zachary Todd Beattie , Alexandros A. Pantelopoulos , Allison Maya Russell , Philip Foeckler , Adrienne M. Tucker , Delisa Lopez , Belen Lafon , Atiyeh Ghoreyshi
CPC classification number: A61B5/4812 , A61B5/02416 , A61B5/02438 , A61B5/11 , A61B5/1114 , A61B5/681 , A61B5/7264 , A61B5/7267 , A61B5/743 , A61B2562/0219
Abstract: A system, computer-readable storage medium, and a method capable of, directly or indirectly, estimating sleep states of a user based on sensor data from movement sensors and/or optical sensors.
-
公开(公告)号：US20200000441A1
公开(公告)日：2020-01-02
申请号：US16441536
申请日：2019-06-14
Applicant: Fitbit, Inc.
Inventor： Belen Lafon , Chris H. Sarantos , Conor Joseph Heneghan , Logan Niehaus , Jaclyn Leverett Wasson , Peter Colin Dess , Amir Bahador Farjadian , Zachary Todd Beattie , Atiyeh Ghoreyshi , Allison Shih Wu
IPC: A61B10/00 , A61B5/0205 , A61B5/1455 , A61B5/145 , A61B5/11 , A61B5/00 , A61B5/01
Abstract: Health information for a woman can be used to predict timing of events related to the woman's menstrual cycle. If available, historical cycle information for a woman can be used to predict upcoming cycle events, such as the start and stop of menstruation. To improve the accuracy of those predictions, one or more health metrics are monitored for the woman that can be correlated with the menstrual cycle. These can include, for example, the resting heart rate (RHR), blood oxygen concentration (SpO2) level, and hemoglobin concentration, among other such options. The metrics are monitored over time to determine patterns that can be correlated with menstrual cycle. This information can then be used to update the predictive model, as well as to update individual event predictions. Information about the predictions, and updates to the predictions, can be surfaced accordingly.
-
公开(公告)号：US11889994B2
公开(公告)日：2024-02-06
申请号：US17013337
申请日：2020-09-04
Applicant: Fitbit, Inc.
Inventor： Belen Lafon , Chris Hanrahan Sarantos , Conor Joseph Heneghan , Logan Niehaus , Jaclyn Leverett Wasson , Peter Colin Dess , Amir Bahador Farjadian , Zachary Todd Beattie , Atiyeh Ghoreyshi , Allison Shih Wu
IPC: A61B5/01 , A61B10/00 , A61B5/0205 , A61B5/11 , A61B5/145 , A61B5/1455 , A61B5/00 , A61B5/024
CPC classification number: A61B10/0012 , A61B5/01 , A61B5/02055 , A61B5/1118 , A61B5/14546 , A61B5/14551 , A61B5/4815 , A61B5/681 , A61B5/742 , A61B5/02405 , A61B5/02433 , A61B2010/0019
Abstract: Health information for a woman can be used to predict timing of events related to the woman's menstrual cycle. If available, historical cycle information for a woman can be used to predict upcoming cycle events, such as the start and stop of menstruation. To improve the accuracy of those predictions, one or more health metrics are monitored for the woman that can be correlated with the menstrual cycle. These can include, for example, the resting heart rate (RHR), blood oxygen concentration (SpO2) level, and hemoglobin concentration, among other such options. The metrics are monitored over time to determine patterns that can be correlated with menstrual cycle. This information can then be used to update the predictive model, as well as to update individual event predictions. Information about the predictions, and updates to the predictions, can be surfaced accordingly.
-
公开(公告)号：US20170035327A1
公开(公告)日：2017-02-09
申请号：US15231627
申请日：2016-08-08
Applicant: Fitbit, Inc.
Inventor： Shelten Gee Jao Yuen , James Park , Atiyeh Ghoreyshi
CPC classification number: G06F3/017 , A61B5/0002 , A61B5/0022 , A61B5/0024 , A61B5/02416 , A61B5/02438 , A61B5/0402 , A61B5/0404 , A61B5/1032 , A61B5/11 , A61B5/1112 , A61B5/1118 , A61B5/112 , A61B5/1123 , A61B5/117 , A61B5/1172 , A61B5/441 , A61B5/6802 , A61B5/681 , A61B5/6844 , A61B5/725 , A61B5/7257 , A61B5/7264 , A61B5/7267 , A61B5/7271 , A61B5/742 , A61B5/7475 , A61B2560/0223 , A61B2562/0219 , A63B24/0062 , A63B69/36 , G01C22/006 , G01P1/02 , G01P13/00 , G01S19/00 , G01S19/19 , G06F1/163 , G06F19/00 , G06F21/32 , G06K9/00335 , G06K9/00342 , G06K9/0053 , G06K9/00885 , G06K2009/00939 , G06Q50/01 , G09B5/02
Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.
Abstract translation: 本公开涉及使用可穿戴适应性监视器获得的数据来识别穿戴式健身器具的使用者的方法，装置和系统。 从穿戴式健身监视器的运动传感器得到的数据和从穿戴式健身监视器的心跳波形传感器获得的数据可用于识别用户。
-
公开(公告)号：US20220265208A1
公开(公告)日：2022-08-25
申请号：US17690369
申请日：2022-03-09
Applicant: Fitbit, Inc.
Inventor： Conor Joseph Heneghan , Jacob Anthony Arnold , Zachary Todd Beattie , Alexandros A. Pantelopoulos , Allison Maya Russell , Philip Foeckler , Adrienne M. Tucker , Delisa Lopez , Belen Lafon , Atiyeh Ghoreyshi
Abstract: A system, computer-readable storage medium, and a method capable of, directly or indirectly, estimating sleep states of a user based on sensor data from movement sensors and/or optical sensors.
-
Patent Agency Ranking
公开(公告)号：US20200167004A1
公开(公告)日：2020-05-28
申请号：US16663166
申请日：2019-10-24
Applicant: Fitbit, Inc.
Inventor： Shelten Gee Jao Yuen , James Park , Atiyeh Ghoreyshi , Anjian Wu
IPC: G06F3/01 , G01P13/00 , G01P1/02 , G01C22/00 , A61B5/00 , A61B5/11 , A61B5/0402 , A61B5/024 , G09B5/02 , G06F21/32 , A63B24/00 , G06K9/00 , G06F1/16 , G01S19/19 , G06Q50/00 , G01S19/00 , A61B5/117
Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.
-
公开(公告)号：US20180067565A1
公开(公告)日：2018-03-08
申请号：US15812879
申请日：2017-11-14
Applicant: Fitbit, Inc.
Inventor： Shelten Gee Jao Yuen , James Park , Atiyeh Ghoreyshi , Anjian Wu
IPC: G06F3/01 , G09B5/02 , A61B5/00 , G06K9/00 , G06Q50/00 , A61B5/0402 , A61B5/11 , A61B5/117 , G06F21/32 , G01S19/00 , G01P13/00 , G01P1/02 , G01C22/00 , A63B24/00 , A61B5/024 , A61B5/0404 , A63B69/36 , A61B5/103
CPC classification number: G06F3/017 , A61B5/0002 , A61B5/0022 , A61B5/0024 , A61B5/02416 , A61B5/02438 , A61B5/0402 , A61B5/0404 , A61B5/1032 , A61B5/11 , A61B5/1112 , A61B5/1118 , A61B5/112 , A61B5/1123 , A61B5/117 , A61B5/1172 , A61B5/441 , A61B5/6802 , A61B5/681 , A61B5/6844 , A61B5/725 , A61B5/7257 , A61B5/7264 , A61B5/7267 , A61B5/7271 , A61B5/742 , A61B5/7475 , A61B2560/0223 , A61B2562/0219 , A63B24/0062 , A63B69/36 , G01C22/006 , G01P1/02 , G01P13/00 , G01S19/00 , G01S19/19 , G06F1/163 , G06F19/00 , G06F21/32 , G06K9/00335 , G06K9/00342 , G06K9/0053 , G06K9/00885 , G06K2009/00939 , G06Q50/01 , G09B5/02
Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.
-
8.发明申请USER IDENTIFICATION VIA DATA COLLECTED FROM SENSORS OF A WEARABLE FITNESS MONITOR 审中-公开用户通过可靠的维修监视器传感器收集的数据公开(公告)号：US20170035328A1
公开(公告)日：2017-02-09
申请号：US15231636
申请日：2016-08-08
Applicant: Fitbit, Inc.
Inventor： Shelten Gee Jao Yuen , James Park , Atiyeh Ghoreyshi
CPC classification number: G06F3/017 , A61B5/0002 , A61B5/0022 , A61B5/0024 , A61B5/02416 , A61B5/02438 , A61B5/0402 , A61B5/0404 , A61B5/1032 , A61B5/11 , A61B5/1112 , A61B5/1118 , A61B5/112 , A61B5/1123 , A61B5/117 , A61B5/1172 , A61B5/441 , A61B5/6802 , A61B5/681 , A61B5/6844 , A61B5/725 , A61B5/7257 , A61B5/7264 , A61B5/7267 , A61B5/7271 , A61B5/742 , A61B5/7475 , A61B2560/0223 , A61B2562/0219 , A63B24/0062 , A63B69/36 , G01C22/006 , G01P1/02 , G01P13/00 , G01S19/00 , G01S19/19 , G06F1/163 , G06F19/00 , G06F21/32 , G06K9/00335 , G06K9/00342 , G06K9/0053 , G06K9/00885 , G06K2009/00939 , G06Q50/01 , G09B5/02
Abstract: The disclosure relates to methods, devices, and systems to recognize a user of a wearable fitness monitor using information obtained using the wearable fitness monitor. Motion data obtained from motion sensors of the wearable fitness monitor may be used to recognize or authenticate the user.
Abstract translation: 本公开涉及使用使用可穿戴适应性监视器获得的信息识别穿戴式健身器具的用户的方法，装置和系统。 从穿戴式健身监视器的运动传感器获得的运动数据可用于识别或认证用户。
-
公开(公告)号：US11207021B2
公开(公告)日：2021-12-28
申请号：US15438643
申请日：2017-02-21
Applicant: Fitbit, Inc.
Inventor： Conor Joseph Heneghan , Jacob Antony Arnold , Zachary Todd Beattie , Alexandros A. Pantelopoulos , Allison Maya Russell , Philip Foeckler , Adrienne M. Tucker , Delisa Lopez , Belen Lafon , Atiyeh Ghoreyshi
Abstract: A system, computer-readable storage medium, and a method capable of, directly or indirectly, estimating sleep states of a user based on sensor data from movement sensors and/or optical sensors.
-
公开(公告)号：US20210145415A1
公开(公告)日：2021-05-20
申请号：US17013337
申请日：2020-09-04
Applicant: Fitbit, Inc.
Inventor： Belen Lafon , Chris Hanrahan Sarantos , Conor Joseph Heneghan , Logan Niehaus , Jaclyn Leverett Wasson , Peter Colin Dess , Amir Bahador Farjadian , Zachary Todd Beattie , Atiyeh Ghoreyshi , Allison Shih Wu
IPC: A61B10/00 , A61B5/01 , A61B5/0205 , A61B5/11 , A61B5/145 , A61B5/1455 , A61B5/00
Abstract: Health information for a woman can be used to predict timing of events related to the woman's menstrual cycle. If available, historical cycle information for a woman can be used to predict upcoming cycle events, such as the start and stop of menstruation. To improve the accuracy of those predictions, one or more health metrics are monitored for the woman that can be correlated with the menstrual cycle. These can include, for example, the resting heart rate (RHR), blood oxygen concentration (SpO2) level, and hemoglobin concentration, among other such options. The metrics are monitored over time to determine patterns that can be correlated with menstrual cycle. This information can then be used to update the predictive model, as well as to update individual event predictions. Information about the predictions, and updates to the predictions, can be surfaced accordingly.
-
-
-
-
-
-
-
-
-
Search Results
20
records
(took 0.015 seconds)
