Artificial intelligence-based system for intraoral support and receiving parts of intraoral appliances

Abstract

This disclosure provides an AI-based system for an intraoral support receptacle (OSR) of an intraoral appliance. The AI-based system comprises an electronic device (ED) and an OSR. The OSR determines whether an intraoral appliance is present inside the OSR and, if an intraoral appliance is present, emits a mist. The OSR captures an image / video of the intraoral appliance and transmits the captured image / video to the ED. The ED receives the captured image / video, uses the image / video to determine the type of intraoral appliance, and uses the image / video to determine at least one feature of the intraoral appliance based on the type. The ED generates a 2D and / or 3D dental structure based on at least one feature of the intraoral appliance and the image / video. The ED uses a trained AI model to compare the 2D and / or 3D dental structure with at least one of historical dental structure images and associated metadata within the ED and provides information about the dental structure data based on the comparison.

Claims

1. An artificial intelligence (AI)-based system for the intraoral support receiving portion of an intraoral appliance, wherein the AI-based system is Electronic devices and, The oral cavity support receiving portion is communicatively coupled to the electronic device, Determine whether the oral device is located inside the oral support receiving portion. When it is determined that the intraoral device is located inside the intraoral support receiving portion, a first sensor located in the intraoral support receiving portion is used to discharge mist. The oral cavity support receiving portion is configured as follows, An AI-based system equipped with [this feature].

2. The aforementioned intraoral support receiving portion is Using a scanner positioned in the oral cavity support receiving portion, at least one of the image and video data of the oral cavity device is captured. The electronic device transmits at least one of the image and video data of the intraoral device. It is configured in such a way, The aforementioned electronic device The oral cavity support receiving portion receives at least one of the image and video data of the oral cavity device. Using at least one of the image and video data of the oral appliance, the type of oral appliance is determined. Based on the type of the intraoral device, at least one feature of the intraoral device is determined using at least one of the image and video data of the intraoral device. Based on the at least one feature of the intraoral device and at least one of the image and video data of the intraoral device, at least one of the 2D and 3D dental structures of the user using the intraoral device is generated. Using a trained AI model, at least one of the 2D or 3D dental structures is compared with at least one of the historical dental structure images and associated metadata stored in the electronic device. Based on the above comparison, information regarding the user's dental structure data is provided. The AI-based system according to claim 1, configured as described above.

3. The aforementioned electronic device Receiving multiple historical dental structure image or video data and associated metadata from one or more sources for one or more users, The progress of each user's dental structure data is determined by comparing the plurality of historical dental structure images or video data and associated metadata with a predetermined dental structure and associated metadata. The AI ​​model is configured to be trained by The progress in the dental structure data refers to detecting one of the following: an abnormality in the dental structure data, a normal state in the dental structure data, or movement of the intraoral device over time. The AI-based system according to claim 2.

4. The aforementioned intraoral support receiving portion is Using the second sensor positioned in the oral cavity support receiving portion, the opening and closing of the lid of the oral cavity support receiving portion is detected. At least one of a laser sensor, a scanner, and an infrared sensor placed in the oral cavity support receiving portion is used to detect the presence or absence of the oral cavity device inside the oral cavity support receiving portion. The AI-based system according to claim 1, configured as described above.

5. The aforementioned intraoral support receiving portion is A temperature and humidity sensor and at least one of a scanner, positioned in the oral cavity support receiving portion, are used to determine whether the mist has been discharged. The AI-based system according to claim 1, configured as described above.

6. The mist is an ultrafine aerosolized droplet, The droplet size of the aforementioned ultrafine aerosolized droplets is in the range of 1 to 10 μm. The aforementioned mist is either a coloring dye or a disinfecting solvent. The AI-based system according to claim 1.

7. The aforementioned intraoral support receiving portion is It is determined whether the intraoral device is located inside the intraoral support receiving portion, and here, the intraoral device using the coloring dye is being used by the user. When it is determined that the intraoral device is located inside the intraoral support receiving portion, a scanner placed in the intraoral support receiving portion is used to capture at least one of the image and video data of the intraoral device. Transmit at least one of the image and video data of the intraoral device to the electronic device. It is configured in such a way, The aforementioned electronic device The oral cavity support receiving portion receives at least one of the image and video data of the oral cavity device. Based on at least one of the image and video data of the intraoral device, the oral condition present in the user's dental structure is determined by the change in the color of the coloring dye in the intraoral device. The AI-based system according to claim 6, configured as described above.

8. The at least one feature of the intraoral appliance includes the shape of the intraoral appliance, the size of the intraoral appliance, the structure of the intraoral appliance, discoloration of the intraoral appliance, and damage to the appearance of the intraoral appliance. The AI-based system according to claim 2.

9. The first sensor is at least one of an ultrasonic disk sensor, a vibrating disk sensor, and a pressurized mist sensor. The AI-based system according to claim 1.

10. The second sensor is at least one of the following: a Hall effect sensor, a reed switch sensor, a light sensor, a tilt sensor, an ultrasonic sensor, a microswitch, a strain gauge sensor, a light-dependent resistor, and an infrared (IR) break beam sensor. The AI-based system according to claim 4.

11. An artificial intelligence (AI)-based system for the intraoral support receiving portion of an intraoral appliance, wherein the AI-based system is Determine whether the oral device is located inside the oral support receiving portion. When it is determined that the intraoral device is located inside the intraoral support receiving portion, a first sensor located in the intraoral support receiving portion is used to discharge mist. The oral cavity support receiving portion is configured as follows: An AI-based system equipped with [this feature].

12. The aforementioned intraoral support receiving portion is Using a scanner positioned in the oral cavity support receiving portion, at least one of the image and video data of the oral cavity device is captured. Using at least one of the image and video data of the oral appliance, the type of oral appliance is determined. Based on the type of the intraoral device, at least one feature of the intraoral device is determined using at least one of the image and video data of the intraoral device. Based on the at least one feature of the intraoral device and at least one of the image and video data of the intraoral device, at least one of the 2D and 3D dental structures of the user using the intraoral device is generated. Using a trained AI model, at least one of the 2D or 3D dental structures is compared with at least one of the historical dental structure images and associated metadata stored in an electronic device. Based on the above comparison, information regarding the user's dental structure data is provided. The AI-based system according to claim 11, configured as described above.

13. The aforementioned intraoral support receiving portion is The electronic device receives multiple historical dental structure image or video data and associated metadata from one or more users. The progress of each user's dental structure data is determined by comparing the plurality of historical dental structure images or video data and associated metadata with a predetermined dental structure and associated metadata. The AI ​​model is configured to be trained by The progress in the dental structure data refers to detecting one of the following: an abnormality in the dental structure data, a normal state in the dental structure data, or movement of the intraoral device over time. The AI-based system according to claim 12.

14. The aforementioned intraoral support receiving portion is Using the second sensor positioned in the oral cavity support receiving portion, the opening and closing of the lid of the oral cavity support receiving portion is detected. At least one of a laser sensor, a scanner, and an infrared sensor placed in the oral cavity support receiving portion is used to detect the presence or absence of the oral cavity device inside the oral cavity support receiving portion. The AI-based system according to claim 11, configured as described above.

15. The aforementioned intraoral support receiving portion is A temperature and humidity sensor and at least one of a scanner, positioned in the oral cavity support receiving portion, are used to determine whether the mist has been discharged. The AI-based system according to claim 11, configured as described above.

16. The mist is an ultrafine aerosolized droplet, The droplet size of the aforementioned ultrafine aerosolized droplets is in the range of 1 to 10 μm. The aforementioned mist is either a coloring dye or a disinfecting solvent. The AI-based system according to claim 11.

17. The aforementioned intraoral support receiving portion is It is determined whether the intraoral device is located inside the intraoral support receiving portion, and here, the intraoral device using the coloring dye is being used by the user. When it is determined that the intraoral device is located inside the intraoral support receiving portion, a scanner placed in the intraoral support receiving portion is used to capture at least one of the image and video data of the intraoral device. Based on at least one of the image and video data of the intraoral device, the oral condition present in the user's dental structure is determined by the change in the color of the coloring dye in the intraoral device. The AI-based system according to claim 16, configured as described above.

18. The at least one feature of the intraoral appliance includes the shape of the intraoral appliance, the size of the intraoral appliance, the structure of the intraoral appliance, discoloration of the intraoral appliance, and damage to the appearance of the intraoral appliance. The AI-based system according to claim 12.

19. The first sensor is at least one of an ultrasonic disk sensor, a vibrating disk sensor, and a pressurized mist sensor. The AI-based system according to claim 11.

20. The second sensor is at least one of the following: a Hall effect sensor, a reed switch sensor, a light sensor, a tilt sensor, an ultrasonic sensor, a microswitch, a strain gauge sensor, a light-dependent resistor, and an infrared (IR) break beam sensor. The AI-based system according to claim 14.

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