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公开(公告)号：US20240197167A1
公开(公告)日：2024-06-20
申请号：US18584409
申请日：2024-02-22
Applicant: Alcon Inc.
Inventor： Ramesh Sarangapani , Kevin Baker
CPC classification number: A61B3/0025 , G06N5/04 , G06N20/00 , G16H50/20 , G16H50/70
Abstract: Systems and methods for determining a compatibility between a multi-focal contact lens and a patient seeking presbyopia vision correction include receiving, from a first device associated with a first eye-care professional (ECP), a request for selecting a contact lens for a consumer, wherein the request comprises biometric information associated with the consumer; obtaining a performance metric associated with the first ECP; determining, using the machine learning model and based on the performance metric, a customized compatibility index indicating a compatibility between a particular contact lens and the consumer for the first ECP; and presenting a report indicating the compatibility index on the first device. Additional systems, methods, and non-transitory machine-readable mediums are also provided.
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Patent Agency Ranking
公开(公告)号：US20230162828A1
公开(公告)日：2023-05-25
申请号：US18160238
申请日：2023-01-26
Applicant: Alcon Inc.
Inventor： Kevin Baker , Ramesh Sarangapani
Abstract: A personalized assistance system for a user of a vision correction device includes a remote computing unit with a controller having a processor and tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute one or more machine learning models. A user device is operable by the user and includes an electronic diary module configured to prompt the user to answer one or more preselected questions at specific intervals. The electronic diary module is configured to store respective answers, entered by the user in response to the one or more preselected questions, as self-reported data. The controller is configured to obtain the self-reported data from the electronic diary module and generate an analysis of the self-reported data, via the one or more machine learning models. The controller is configured to assist the user based in part on the analysis.
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公开(公告)号：US11944379B2
公开(公告)日：2024-04-02
申请号：US16896006
申请日：2020-06-08
Applicant: Alcon Inc.
Inventor： Ramesh Sarangapani , Kevin Baker
CPC classification number: A61B3/0025 , G06N5/04 , G06N20/00 , G16H50/20 , G16H50/70
Abstract: Systems and methods for determining a compatibility between a multi-focal contact lens and a patient seeking presbyopia vision correction include receiving, from a first device associated with a first eye-care professional (ECP), a request for selecting a contact lens for a consumer, wherein the request comprises biometric information associated with the consumer; obtaining a performance metric associated with the first ECP; determining, using the machine learning model and based on the performance metric, a customized compatibility index indicating a compatibility between a particular contact lens and the consumer for the first ECP; and presenting a report indicating the compatibility index on the first device. Additional systems, methods, and non-transitory machine-readable mediums are also provided.
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公开(公告)号：US11587656B2
公开(公告)日：2023-02-21
申请号：US17127735
申请日：2020-12-18
Applicant: Alcon Inc.
Inventor： Kevin Baker , Ramesh Sarangapani
Abstract: A personalized assistance system for a user of a vision correction device includes a remote computing unit with a controller having a processor and tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute one or more machine learning models. A user device is operable by the user and includes an electronic diary module configured to prompt the user to answer one or more preselected questions at specific intervals. The electronic diary module is configured to store respective answers, entered by the user in response to the one or more preselected questions, as self-reported data. The controller is configured to obtain the self-reported data from the electronic diary module and generate an analysis of the self-reported data, via the one or more machine learning models. The controller is configured to assist the user based in part on the analysis.
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公开(公告)号：US20230049316A1
公开(公告)日：2023-02-16
申请号：US17855445
申请日：2022-06-30
Applicant: Alcon Inc.
Inventor： Kevin Baker , Hyo Won Choi , David Borja , Carolina Kunnen
Abstract: Aspects of the present disclosure provide techniques for quantitatively assessing tear-film dynamics associated with contact lenses. An example method includes projecting an image of one or more shapes on a tear film surface of the contact lens worn on the eye, capturing video data, comprising a plurality of image frames, of the one or more shapes projected on the tear film surface of the contact lens over a period of time, performing image segmentation on a plurality of reflection patterns included in the plurality of image frames, generating a plurality of maps of the tear film surface of the contact lens indicating changes to the tear film surface of the contact lens during the period of time, and outputting, based on the plurality of maps, one or more metrics quantifying the changes to the tear film surface of the contact lens over the period of time.
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公开(公告)号：US20210193278A1
公开(公告)日：2021-06-24
申请号：US17127735
申请日：2020-12-18
Applicant: Alcon Inc.
Inventor： Kevin Baker , Ramesh Sarangapani
Abstract: A personalized assistance system for a user of a vision correction device includes a remote computing unit with a controller having a processor and tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute one or more machine learning models. A user device is operable by the user and includes an electronic diary module configured to prompt the user to answer one or more preselected questions at specific intervals. The electronic diary module is configured to store respective answers, entered by the user in response to the one or more preselected questions, as self-reported data. The controller is configured to obtain the self-reported data from the electronic diary module and generate an analysis of the self-reported data, via the one or more machine learning models. The controller is configured to assist the user based in part on the analysis.
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