Abstract: A method for orthodontic treatment is provided. The method comprises obtaining feedback data including patient feedback data points collected by fitting an orthodontic appliance configured to apply a force to a tooth of a patient and indicating a level of discomfort experienced by the patient, wherein the force is a function of a critical force that is specific to the patient, correlating the level of discomfort to the force applied to the tooth of the patient, and, determining whether or not the feedback data is optimized for determining a target orthodontic force for orthodontic treatment that is an optimal orthodontic force based on the critical force.

Abstract: Disclosed is a machine learning architecture for a two-dimensional image protocol detector configured to receive a first image representing at least a portion of a mouth of a user, and output user feedback for capturing a second image representing a portion of the mouth of the user, where the machine learning architecture outputs the user feedback in response to an image quality score of the first image not satisfying an image quality threshold.

Abstract: Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images include a model training system that receives data packets of a training set. Each data packet may include data corresponding to training images of a respective dental arch and a 3D training model of the respective dental arch. The model training system identifies, for a data packet, correlation points between the one or more training images and the 3D training model of the respective dental arch. The model training system generates a machine learning model using the correlation points for the data packets of the training set. A model generation system receives one or more images of a dental arch. The model generation system generates a 3D model of the dental arch by applying the images of the dental arch to the machine learning model.

Abstract: Systems and methods for determining an updated target orthodontic force are provided. A method includes receiving feedback data obtained during use of an orthodontic appliance configured to apply a target orthodontic force to a tooth of a patient. The feedback data includes one or both of patient feedback data points and treatment feedback data points. A value of the target orthodontic force having been determined by inputting periodontal ligament (PDL) behavior data into an algorithm. The method includes updating the algorithm using the feedback data and using the updated algorithm to determine an updated value corresponding to an updated target orthodontic force for use in reconfiguring or replacing the orthodontic appliance so as to apply the updated target orthodontic force.

Abstract: Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images of dental impressions include a model training system that provides a machine learning model using training image(s) of a dental impression of a respective dental arch and a 3D training model of the respective dental arch. A model generation system receives first image(s) of a first dental impression of a user's dental arch and second image(s), which may be of the first dental impression or a second dental impression of the dental arch. The model generation system generates a first and second 3D model of the dental arch by applying the first image(s) and second image(s) to the machine learning model.

Abstract: A system and method for orthodontic appliance configuration are provided. A method includes obtaining a force value which approximates a target orthodontic force value having been determined based on patient data and PDL behavior data associated with the patient data. The patient data includes patient treatment data and patient characteristic data, the patient treatment data at least including one or both of a tooth type indicator and a tooth position indicator associated with a tooth of a patient to be treated and a treatment movement value which describes the required tooth movement to effect treatment of the tooth. The force value is used to determine configuration parameters for configuring an orthodontic appliance to apply the force value to the tooth of the patient. The configuration parameters are output.

Abstract: A system and method for orthodontic treatment staging are described. A method includes receiving patient data including patient treatment data and patient characteristic data. One or more stage movement values and corresponding stage force values are determined. Each stage force value is based on a target orthodontic force value that is based on one or more determinate points of PDL behavior data associated with at least a subset of the patient data. The PDL behavior data includes or is based on force measurement data points and corresponding displacement measurement data points having been measured in-vivo while applying a force to a particular tooth of a human or animal subject. The sum of the one or more stage movement values approximates a treatment movement value. The one or more stage movement values and corresponding stage force values are output as a treatment plan for treatment of a tooth of the patient.

Abstract: Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images of dental impressions include a model training system that provides a machine learning model using training image(s) of a dental impression of a respective dental arch and a 3D training model of the respective dental arch. A model generation system receives first image(s) of a first dental impression of a user's dental arch and second image(s), which may be of the first dental impression or a second dental impression of the dental arch. The model generation system generates a first and second 3D model of the dental arch by applying the first image(s) and second image(s) to the machine learning model. A model merging system merges the first 3D model and the second 3D model to generate a merged model of the dental arch.

Abstract: A measurement device and associated systems and methods are described. The device includes a body and an attachment mechanism fixed to and extending from the body. The attachment mechanism is configured for attachment to a part of a human or animal subject. The or a part of the body is configured for gripping by a user. The device incudes a processor in communication with a force sensor module and a position sensor module. The force sensor module is configured to measure a force applied to the attachment mechanism, in use, and output force measurement data relating to the measured force. The position sensor module is configured to measure the position of the part of the human or animal relative to other parts thereof, in use, and output position measurement data. The processor is configured to store the force measurement data and position measurement data in a memory component associated therewith.

Abstract: A system and method for determining a target orthodontic force are provided. A method includes receiving patient data associated with a patient and including patient characteristic data and patient treatment data including one or both of a tooth type indicator and a tooth position indicator associated with a tooth of the patient to be corrected. Periodontal ligament (PDL) behavior data including or being based on force measurement data points and corresponding displacement measurement data points having been measured in-vivo while applying a force to a tooth of a human or animal subject and associated with at least a subset of the patient data is retrieved. A target orthodontic force value that is specific to the patient data is determined by inputting the PDL behavior data into an algorithm which determines the target orthodontic force based on the PDL behavior data and the target orthodontic force value is output.

Abstract: Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images of dental impressions include a model training system that provides a machine learning model using training image(s) of a dental impression of a respective dental arch and a 3D training model of the respective dental arch. A model generation system receives first image(s) of a first dental impression of a user's dental arch and second image(s), which may be of the first dental impression or a second dental impression of the dental arch. The model generation system generates a first and second 3D model of the dental arch by applying the first image(s) and second image(s) to the machine learning model. A model merging system merges the first 3D model and the second 3D model to generate a merged model of the dental arch.

Abstract: Systems and methods for generating a three-dimensional (3D) model of a user's dental arch based on two-dimensional (2D) images of dental impressions include a model training system that provides a machine learning model using training image(s) of a dental impression of a respective dental arch and a 3D training model of the respective dental arch. A model generation system receives first image(s) of a first dental impression of a user's dental arch and second image(s), which may be of the first dental impression or a second dental impression of the dental arch. The model generation system generates a first and second 3D model of the dental arch by applying the first image(s) and second image(s) to the machine learning model. A model merging system merges the first 3D model and the second 3D model to generate a merged model of the dental arch.

Abstract: A medical apparatus for use in the corrective treatment of malocclusion and other dentofacial defects is provided. The apparatus has at least one stimulator which is configured to apply a stimulus to a part of the dento-oral complex and includes at least one actuator controllable by means of electronic signals. A feedback system is also provided and is configured to measure parameters relating to the biomechanical tissue response resulting from the stimulus applied by the at least one stimulator, to analyze the parameters by means of a processor, and to adjust the stimulus applied by the at least one stimulator by means of the required control signals in order to apply a stimulus representing an optimal orthodontic force.

Abstract: A medical apparatus for use in the corrective treatment of malocclusion and other dentofacial defects is provided. The apparatus has at least one stimulator which is configured to apply a stimulus to a part of the dento-oral complex and includes at least one actuator controllable by means of electronic signals. A feedback system is also provided and is configured to measure parameters relating to the biomechanical tissue response resulting from the stimulus applied by the at least one stimulator, to analyse the parameters by means of a processor, and to adjust the stimulus applied by the at least one stimulator by means of the required control signals in order to apply a stimulus representing an optimal orthodontic force.