Described herein are computer-implemented methods for analyzing an input image of a mouth region from a user to provide information regarding a disease or condition of the mouth region, a computing device configured to receive the input images from a user; and a trained machine learning system. In some embodiments, the computing device is configured to transmit an oral health score to the user.

An artificial tongue is provided. The artificial tongue includes tongue tissue formed by a bioprinting process, an antenna embedded within the tongue tissue and configured to wirelessly receive power from an external device, a processor embedded within the tongue tissue and operatively coupled to the antenna, and a piezoelectric element embedded within the tongue tissue and operatively coupled to the processor. The piezoelectric element is configured to deform in response to an applied electric bias, and the processor is configured to cause the electric bias to be applied to the piezoelectric element based on the power received by the antenna.

A method for localizing gingival inflammation using an oral care device, comprising: emitting (520) light by one or more light emitters (42) of the oral care device; obtaining (530), at a first rate by one or more light detectors (40), reflectance measurements for a plurality of locations to generate first reflectance data; determining (540), by a controller (30) of the oral care device using the first reflectance data, whether the location comprises gingiva; obtaining (550), at a second rate by the one or more light detectors, reflectance measurements for each location determined to comprise gingiva to generate gingiva reflectance data, wherein the second rate is faster than the first rate; and determining (560), by the controller using the gingiva reflectance data, whether gingiva at that location is inflamed.

Neural stimulation is provided according to a closed loop algorithm to treat sleep disordered breathing (SOB), including obstructive sleep apnea (OSA). The closed loop algorithm is executed by a system comprising a processor (which can be within the neural stimulator). The closed loop algorithm includes monitoring physiological data (e.g., EMG data) recorded by a sensor implanted adjacent to an anterior lingual muscle; identifying a trigger within the physiological data, wherein the trigger is identified as a biomarker for a condition related to sleep (e.g., inspiration); and applying a rule-based classification (which can learn) to the trigger to determine whether one or more parameters of a stimulation should be altered based on the biomarker.

An intraoral moisture measuring device includes: a swing member that swings with respect to a main body about a predetermined swing center; a moisture amount detection unit provided at a tip of the swing member, for detecting a moisture amount by being directly or indirectly abutted against a measurement site in a mouth; and a biasing member for biasing the swing member in one of swing directions. Consequently, the intraoral moisture measuring device is capable of measuring intraoral moisture in a simple and highly-accurate manner.

A non-invasive method for determining a gingival pocket depth includes seating a photoacoustic probe tray in a subject's mouth; transmitting photonic energy transgingivally; receiving generated ultrasonic signals; determining and processing the time of flight between transmitting and receiving and a relative amplitude of the ultrasonic signals to the transmitted photonic energy to determine densities and a topography of the subject's dental anatomy; determining a repeatable reference point; and measuring the gingival pocket depth in relation to the repeatable reference point. A system includes a transducer tray a biogel-containing bite wafer seated within the transducer tray; a processor; a memory; a user interface; and a visual display. The transducer tray has at least one embedded pulsed laser source and at least one embedded ultrasonic sensor.

An intraoral measurement device includes: a device main body that holds a base end side of a prism by a housing, the housing accommodating an illumination member and an imaging member, a cover member that is attached to the device main body in a state of covering, with a space part interposed in between, a distal end side of the prism arranged to face a measurement target, in which a part arranged to face the measurement target is formed by a light transmission window; and a heat transfer member that extends from the device main body along a non-optical surface of the prism, and transfers heat of the device main body to the light transmission window through abutment of a protruding end provided to protrude from the prism against the light transmission window of the cover member.

A method (500) for localizing gingival inflammation using an oral care device (10), the method comprising: (i) emitting (520) light at a first intensity by a light emitter (42); (ii) obtaining (530) first reflectance measurements reflectance data; (iii) determining (540), by a controller (30) from the first reflectance data, whether the location comprises gingiva; (iv) automatically adjusting (550), based at least in part on the first reflectance data, the intensity of a light emitter to a second intensity different from the first intensity, and/or automatically adjusting (550) a gain of a light detector; (v) obtaining (560) a second plurality of reflectance measurements by the light detector of the oral care device for at least some of the locations; and (vi) determining (570), using the second plurality of reflectance measurements, whether gingiva at the location is inflamed.

An intraoral scanner generates 2D images of a dental site and 3D intraoral scans of the dental site. The computing device receives the 2D images of the dental site and the 3D intraoral scans of the dental site from the intraoral scanner, generates a 3D model of the dental site based on the 3D intraoral scans of the dental site, and processes at least one of a) one or more of the 2D images of the dental site, b) one or more of the 3D intraoral scans of the dental site, or c) data from the 3D model of the dental site to identify one or more intraoral areas of interest (AOIs) at the dental site. The computing device determines a dental condition associated with the one or more intraoral AOIs, and determines a manner for scanning the one or more intraoral AOIs.

A method for localizing gingival inflammation using an oral care device, comprising: (i) simultaneously emitting (520) light by a plurality of light sources (48) of the oral care device, wherein at least some of the plurality of light sources emit light of different wavelengths to result in a plurality of emitted light wavelengths, wherein each of the different wavelengths is modulated with a distinct code; (ii) obtaining (530), by a light detector (40) of the oral care device, reflectance measurements from a location within the user's mouth to generate reflectance data for the location; (iii) demodulating (540), by a controller (30) of the oral care device, the obtained reflectance data; and (iv) determining (560), by the controller using the demodulated reflectance data, whether gingiva at the location is inflamed.