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1. WO2020198023 - SYSTÈME ET PROCÉDÉ DE CONCEPTION ET DE FABRICATION BASÉES SUR L'APPRENTISSAGE AUTOMATIQUE DE DISPOSITIFS DE LOGEMENT À L'OREILLE

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CLAIMS

What is claimed is:

1. A computer- implemented method to create a model used for fabrication of a device configured for placement in an anatomical cavity of a wearer, the method comprising:

(a) obtaining feedback data for a plurality of devices fabricated for a plurality of subjects, wherein each of the plurality of devices are fabricated based on a three-dimensional scan of an anatomical cavity of one of the plurality of subjects, and wherein the feedback data relates to at least one of a user experience, a fit, a comfort, and a performance of the plurality of devices;

(b) utilizing the feedback data to select a training data set for a model for transforming a three-dimensional scan of an anatomical cavity to a three-dimensional representation of a device for fabrication;

(c) training the model with the training data set, wherein the training data set comprises devices paired with three-dimensional scans upon which the devices were based;

(d) obtaining a three-dimensional scan of an anatomical cavity of a wearer and at least one parameter for a device; and

(e) transforming the three-dimensional scan into a three-dimensional representation of the device for fabrication in accordance with the model and the at least one parameter.

2. The method of claim 1 , wherein transforming at least one of adds dimension or reduces dimension of a portion of the three-dimensional scan.

3. The method of claim 1, wherein the model is a neural network.

4. The method of claim 1 , wherein the anatomical cavity is an ear.

5. The method of claim 1, wherein the device is an in-ear device.

6. The method of claim 1, further comprising, wherein the feedback data are further utilized to select a testing data set for the model, and testing the model with the testing data set.

7. The method of claim 1, wherein the three-dimensional scan is in a first format and is converted to a second format to do modeling.

8. The method of claim 7, wherein at completion of modeling, the three-dimensional representation is converted back to the first format prior to fabrication.

9. The method of claim 1 , wherein the three-dimensional representation is an STL file.

10. A computer-implemented method for fabrication of a device configured for placement in an anatomical cavity of a wearer, the method comprising:

(a) obtaining feedback data for a plurality of devices worn by subjects, the feedback data relating to at least one of a user experience, a fit, a comfort, and a performance of the plurality of devices;

(b) training a model with a dataset selected based on the feedback data;

(c) obtaining a three-dimensional scan of the anatomical cavity of a wearer;

(d) transforming the three-dimensional scan in accordance with the model and at least one parameter for a device into a modified scan; and

(e) providing the modified scan to a fabricator to fabricate the device based on the modified scan.

11. A system to fabricate a custom device to be worn in an anatomical cavity of a wearer, the system comprising:

a processor that: (i) trains a machine learning model on datasets selected based on feedback data for a plurality of devices worn by subjects, the feedback relating to a user experience, a fit, a comfort, or a performance of the plurality of devices; (ii) receives at least one parameter for the custom device; and (iii) receives a three-dimensional scan of the anatomical cavity of a wearer, the processor further comprising stored instructions that when executed cause the processor to:

generate modifications of the three-dimensional scan to obtain a modified scan, wherein the modifications of the three-dimensional scan are in accordance with the machine learning model and wherein the modifications comprise at least one of adding or reducing dimension of the three-dimensional scan.

12. The system of claim 11, wherein the processor is further programmed to send the modified scan to a fabricator for fabrication of the custom device.

13. The system of claim 11, further comprising, a user interface to provide input to the system.

14. The system of claim 11, wherein a fabricator fabricates the custom device based on the modified scan.

15. The system of claim 11, wherein the anatomical cavity of the wearer is an ear.

16. The system of claim 11, wherein the custom device is an in-ear device.

17. A method to fabricate and deliver a custom device to be worn in an anatomical cavity of a wearer, the method comprising:

(a) providing a three-dimensional scanner configured to scan the anatomical cavity of a wearer;

(b) providing an order interface to a user, wherein the order interface provides the user with an option to select a device type;

(c) based on the device type, obtaining a three-dimensional scan for the anatomical cavity of the wearer from the three-dimensional scanner;

(d) modifying the scan based on a model previously trained on data related to at least one of a fit, a comfort, or a performance of similar devices in similar anatomical cavities of subjects; and

(e) providing the modified scan to a fabricator for fabrication and delivery of the custom device to at least one of the user or wearer.

18. A computer-implemented method to determine a device design for placement in a cavity, the method comprising:

(a) obtaining feedback data from a user for a device, wherein the feedback data relates to at least one of a user experience, a fit, a comfort, and a performance of the device;

(b) obtaining a three-dimensional scan of an anatomical cavity of the user;

(c) generating a training vector, wherein the training vector includes: the feedback data, the three-dimensional scan, and an identification of the device;

(d) training a model using the training vector;

(e) obtaining three-dimensional scans of an anatomical cavity of a second user;

(f) providing the three-dimensional scan of the anatomical cavity of the second user to the model; and

(g) receiving, from the model, data indicative of a selected design of a device for the second user.

19. The method of claim 18, wherein training the model further comprises training the model using a plurality of training vectors corresponding to feedback data and three dimensional scans from a plurality of users.

20. A computer-implemented method to determine a device design for placement in a cavity, the method comprising:

(a) obtaining a three-dimensional scan of an anatomical cavity of a user;

(b) obtaining a three-dimensional data of a device that is placed in the anatomical cavity of the user;

(c) obtaining feedback data from a user for a device, wherein the feedback data relates to at least one of a user experience, a fit, a comfort, and a performance of the device;

(d) generating a training vector, wherein the training vector includes: the feedback data, the three-dimensional scan, and the three-dimensional data of the device;

(e) training a model using the training vector;

(f) obtaining a three-dimensional scan of an anatomical cavity of a second user;

(g) obtaining a design data of base device design;

(h) receive a modification to the base device design;

(i) providing to the model: the three-dimensional scan of the anatomical cavity of the second user to the model, data representative of the base device design, and the modification to the base device design; and

(j) receiving, from the model, data indicative of a predictive rating of the modification to the base device design for the second user.