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公开(公告)号:US20240075895A1
公开(公告)日:2024-03-07
申请号:US18462271
申请日:2023-09-06
申请人: Apple Inc.
发明人: Vinay R. Majjigi , Sriram Venkateswaran , Aniket Aranake , Tejal Bhamre , Alexandru Popovici , Parisa Dehleh Hossein Zadeh , Yann Jerome Julien Renard , Yi Wen Liao , Stephen P. Jackson , Rebecca L. Clarkson , Henry Choi , Paul D. Bryan , Mrinal Agarwal , Ethan Goolish , Richard G. Liu , Omar Aziz , Alvaro J. Melendez Hasbun , David Ojeda Avellaneda , Sunny Kai Pang Chow , Pedro O. Varangot , Tianye Sun , Karthik Jayaraman Raghuram , Hung A. Pham
IPC分类号: B60R21/013 , G06F18/213
CPC分类号: B60R21/013 , G06F18/213 , B60R2021/0027
摘要: Embodiments are disclosed for crash detection on one or more mobile devices (e.g., smartwatch and/or smartphone). In some embodiments, a method comprises: detecting, with at least one processor, a crash event on a crash device; extracting, with the at least one processor, multimodal features from sensor data generated by multiple sensing modalities of the crash device; computing, with the at least one processor, a plurality of crash decisions based on a plurality of machine learning models applied to the multimodal features; and determining, with the at least one processor, that a severe vehicle crash has occurred involving the crash device based on the plurality of crash decisions and a severity model.
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公开(公告)号:US20240233507A1
公开(公告)日:2024-07-11
申请号:US18617381
申请日:2024-03-26
申请人: Apple Inc.
发明人: Sriram Venkateswaran , Parisa Dehleh Hossein Zadeh , Vinay R. Majjigi , Yann Jerome Julien Renard
IPC分类号: G08B21/04
CPC分类号: G08B21/043
摘要: In an example method, a mobile device receives sensor data obtained by one or more sensor over a time period. The one or more sensors are worn by a user. Further, the mobile device determines a context of the user based on the sensor data, and obtains a set of rules for processing the sensor data based on the context, where the set of rules is specific to the context. The mobile device determines at least one of a likelihood that the user has fallen or a likelihood that the user requires assistance based on the sensor data and the set of rules, and generates one or more notifications based on at least one of the likelihood that the user has fallen or the likelihood that the user requires assistance.
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公开(公告)号:US11282362B2
公开(公告)日:2022-03-22
申请号:US16929013
申请日:2020-07-14
申请人: Apple Inc.
发明人: Xing Tan , Huayu Ding , Hung A. Pham , Karthik Jayaraman Raghuram , Parisa Dehleh Hossein Zadeh , Omar Aziz , Sriram Venkateswaran , Manjunath Shankar Rao , Xiaoyue Zhang , Vinay R. Majjigi , Yann Jerome Julien Renard
IPC分类号: G08B1/08 , G08B21/04 , G08B13/24 , A61B5/0205 , A61B5/00 , A61B5/024 , A61B5/11 , G01C5/06 , G01C21/12 , G01S19/13 , G06F3/01
摘要: In an example method, a mobile device obtains a database including a plurality of data records. Each data record includes an indication of a respective impact previously experienced by a user of the mobile device, and sensor data generated by one or more first sensors worn by the user during that impact. The mobile device obtains sensor data generated by one or more second sensors worn by the user over a period of time, and determines whether the user has fallen during the period of time based on the database and the additional sensor data. The mobile device generates one or more notifications based on the determination of whether the user has fallen during the period of time.
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公开(公告)号:US20230084356A1
公开(公告)日:2023-03-16
申请号:US17942018
申请日:2022-09-09
申请人: Apple Inc.
发明人: Sriram Venkateswaran , Parisa Dehleh Hossein Zadeh , Vinay R. Majjigi , Yann Jerome Julien Renard
IPC分类号: G08B21/04
摘要: In an example method, a mobile device receives sensor data obtained by one or more sensor over a time period. The one or more sensors are worn by a user. Further, the mobile device determines a context of the user based on the sensor data, and obtains a set of rules for processing the sensor data based on the context, where the set of rules is specific to the context. The mobile device determines at least one of a likelihood that the user has fallen or a likelihood that the user requires assistance based on the sensor data and the set of rules, and generates one or more notifications based on at least one of the likelihood that the user has fallen or the likelihood that the user requires assistance.
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公开(公告)号:US20200342735A1
公开(公告)日:2020-10-29
申请号:US16929013
申请日:2020-07-14
申请人: Apple Inc.
发明人: Xing Tan , Huayu Ding , Hung A. Pham , Karthik Jayaraman Raghuram , Parisa Dehleh Hossein Zadeh , Omar Aziz , Sriram Venkateswaran , Manjunath Shankar Rao , Xiaoyue Zhang , Vinay R. Majjigi , Yann Jerome Julien Renard
IPC分类号: G08B21/04 , A61B5/00 , G08B13/24 , A61B5/0205 , A61B5/024 , A61B5/11 , G01C5/06 , G01C21/12 , G01S19/13 , G06F3/01
摘要: In an example method, a mobile device obtains a database including a plurality of data records. Each data record includes an indication of a respective impact previously experienced by a user of the mobile device, and sensor data generated by one or more first sensors worn by the user during that impact. The mobile device obtains sensor data generated by one or more second sensors worn by the user over a period of time, and determines whether the user has fallen during the period of time based on the database and the additional sensor data. The mobile device generates one or more notifications based on the determination of whether the user has fallen during the period of time.
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公开(公告)号:US20240329277A1
公开(公告)日:2024-10-03
申请号:US18737920
申请日:2024-06-07
申请人: Apple Inc.
发明人: Vinay R. Majjigi , Bharath Narasimha Rao , Sriram Venkateswaran , Aniket Aranake , Tejal Bhamre , Alexandru Popovici , Parisa Dehleh Hossein Zadeh , Yann Jerome Julien Renard , Yi Wen Liao , Stephen P. Jackson , Rebecca L. Clarkson , Henry Choi , Paul D. Bryan , Mrinal Agarwal , Ethan Goolish , Richard G. Liu , Omar Aziz , Alvaro J. Melendez Hasbun , David Ojeda Avellaneda , Sunny Kai Pang Chow , Pedro O. Varangot , Tianye Sun , Karthik Jayaraman Raghuram , Hung A. Pham
摘要: Embodiments are disclosed for crash detection on one or more mobile devices (e.g., smartwatch and/or smartphone. In some embodiments, a method comprises: detecting a crash event on a crash device; extracting multimodal features from sensor data generated by multiple sensing modalities of the crash device; computing a plurality of crash decisions based on a plurality of machine learning models applied to the multimodal features, wherein at least one multimodal feature is a rotation rate about a mean axis of rotation; and determining that a severe vehicle crash has occurred involving the crash device based on the plurality of crash decisions and a severity model.
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