公开(公告)号：US20210109371A1

公开(公告)日：2021-04-15

申请号：US16970570

申请日：2019-02-19

Applicant: Essilor International

Inventor： Muriel GODEAU ,  Mathieu FEUILLADE ,  Pauline COLAS ,  Anna YEO ,  Yee Ling WONG

IPC: G02C5/00 ,  G02C5/20

Abstract: An eyewear frame having at least one frame component including a stimuli-responsive polymer is provided. The at least one frame component has a physical property which is reversibly changeable in response to a stimulus of non-thermal origin applied to the stimuli-responsive polymer. An eyewear including the eyewear frame, and a method of adjusting the eyewear frame are also provided.

公开(公告)号：US20220084687A1

公开(公告)日：2022-03-17

申请号：US17416938

申请日：2019-12-04

Applicant: ESSILOR INTERNATIONAL

Inventor： Björn DROBE ,  Aurélie LE CAIN ,  Yee Ling WONG

IPC: G16H50/70 ,  G16H50/20 ,  G16H50/50

Abstract: This method for predicting evolution over time of at least one vision-related parameter of at least one person includes: obtaining successive values for the person, respectively corresponding to repeated measurements over time of at least one parameter of a first predetermined type for the person; predicting by at least one processor the evolution over time of the vision-related parameter of the person from the obtained successive values for the person, by using a prediction model associated with a group of individuals; the predicting including associating at least part of the successive values for the person with the predicted evolution over time of the vision-related parameter of the person, the associating including jointly processing the successive values associated with the same parameter of the first predetermined type. The predicted evolution depends differentially on each of the jointly processed values.

公开(公告)号：US20220028552A1

公开(公告)日：2022-01-27

申请号：US17414198

申请日：2019-12-04

Applicant: ESSILOR INTERNATIONAL

Inventor： Bjorn DROBE ,  Aurélie LE CAIN ,  Yee Ling WONG

IPC: G16H50/20 ,  G16H50/70 ,  G16H10/60 ,  G16H50/50 ,  G16H50/30 ,  A61B3/00

Abstract: This method for building a prediction model for predicting evolution over time of at least one vision-related parameter of at least one person includes: obtaining successive values respectively corresponding to repeated measurements over time of at least one parameter of a first predetermined type for at least one member of a group of individuals; obtaining evolution over time of the vision-related parameter(s) for the member(s) of the group of individuals; building by at least one processor the prediction model, including associating at least part of the successive values with the obtained evolution over time of the vision-related parameter(s) for the member(s) of the group of individuals, the associating including jointly processing the at least part of the successive values associated with a same one of the parameter(s) of the first predetermined type. The prediction model depends differentially on each of the jointly processed values.