Method for physically adjusting a hearing device, hearing device and hearing device system
US-2017295442-A1 · Oct 12, 2017 · US
US11510016B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11510016-B2 |
| Application number | US-201817283266-A |
| Country | US |
| Kind code | B2 |
| Filing date | Oct 8, 2018 |
| Priority date | Oct 8, 2018 |
| Publication date | Nov 22, 2022 |
| Grant date | Nov 22, 2022 |
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A method for adjusting a hearing device ( 12 ) adapted to be worn behind an ear ( 28 ) comprises: determining a cymba angle ( 54 ) between a cartilage ( 50 ) above the cymba ( 46 ) of the ear ( 28 ) and a viewing direction ( 38 ) of the user; estimating a tilt angle ( 39 ) of the hearing device ( 12 ) with respect to the viewing direction ( 38 ) from the cymba angle ( 54 ); and adjusting a beam former direction ( 37 ) of a beam former ( 34 ) of the hearing device ( 12 ), such that the beam former direction ( 37 ) is aligned with the viewing direction ( 38 ).
Opening claim text (preview).
The invention claimed is: 1. A method for adjusting a hearing device adapted to be worn behind an ear of a user, the method comprising: receiving image data from the ear, the image data containing at least one image of the ear; determining, from the image data, a cymba angle between a cartilage above a cymba of the ear and a viewing direction of the user, wherein a direction of the cartilage is determined by averaging a curve along the cartilage and the cymba angle is determined as an angle between the direction of the cartilage and the viewing direction; estimating a tilt angle of the hearing device worn by the user with respect to the viewing direction from the cymba angle; adjusting a beam former direction of a beam former of the hearing device, such that the beam former direction is aligned with the viewing direction. 2. The method of claim 1 , wherein the cymba angle is determined with an image recognition algorithm adapted for identifying parts of the ear. 3. The method of claim 1 , wherein the cymba angle is determined with a machine learning algorithm trained with image data of ears with known cymba angles. 4. The method of claim 1 , wherein the image data contains images of the ear from different directions and a three-dimensional representation is determined from the image data; wherein the cymba angle is determined from the three-dimensional representation. 5. The method of claim 1 , wherein the image data contains an image of a marker provided besides the ear, the marker having at least one of a scale or an indication of the viewing direction. 6. The method of claim 1 , further comprising: determining an ear size from the image data; wherein a distance from a front of a helix of the ear to an ear channel is determined from the image data. 7. The method of claim 1 , further comprising: determining an optimal tube length of a tube interconnecting a part of the hearing device behind the ear with a part of the hearing device in the ear from the image data. 8. The method of claim 1 , further comprising: determining, whether the user wears glasses, from the image data. 9. The method of claim 1 , wherein the tilt angle is determined from a lookup table. 10. The method of claim 1 , wherein the tilt angle is determined with a machine learning algorithm, which has been trained with known cymba angles. 11. The method of claim 1 , wherein the tilt angle is determined from the cymba angle and at least one of: an ear size, a selected tube length of a tube interconnecting a part of the hearing device behind the ear with a part of the hearing device in the ear, information about, whether the user wears glasses or not. 12. A non-transitory computer-readable medium storing instructions, which when executed by a processor, cause a hearing system to perform operations, the operations comprising: receiving image data from an ear of a user, the image data containing at least one image of the ear; determining, from the image data, a cymba angle between a cartilage above a cymba of the ear and a viewing direction of the user, wherein a direction of the cartilage is determined by averaging a curve along the cartilage and the cymba angle is determined as an angle between the direction of the cartilage and the viewing direction; estimating a tilt angle of the hearing device worn by the user with respect to the viewing direction from the cymba angle; adjusting a beam former direction of a beam former of the hearing device, such that the beam former direction is aligned with the viewing direction. 13. The non-transitory computer-readable medium of claim 12 , wherein the cymba angle is determined with an image recognition algorithm adapted for identifying parts of the ear. 14. The non-transitory computer-readable medium of claim 12 , wherein the cymba angle is determined with a machine learning algorithm trained with image data of ears with known cymba angles. 15. The non-transitory computer-readable medium of claim 12 , wherein the image data contains images of the ear from different directions and a three-dimensional representation is determined from the image data; wherein the cymba angle is determined from the three-dimensional representation. 16. The non-transitory computer-readable medium of claim 12 , wherein the image data contains an image of a marker provided besides the ear, the marker having at least one of a scale or an indication of the viewing direction. 17. The non-transitory computer-readable medium of claim 12 , further comprising: determining an ear size from the image data; wherein a distance from a front of a helix of the ear to an ear channel is determined from the image data. 18. The non-transitory computer-readable medium of claim 12 , further comprising: determining an optimal tube length of a tube interconnecting a part of the hearing device behind the ear with a part of the hearing device in the ear from the image data. 19. The non-transitory computer-readable medium of claim 12 , further comprising: determining, whether the user wears glasses, from the image data. 20. The non-transitory computer-readable medium of claim 12 , wherein the tilt angle is determined from a lookup table.
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