Method for cleaning teeth, and cleaning system

Abstract

A method for cleaning teeth using a tooth-cleaning device by removing tooth stains uses the following models: a tooth model, which describes the tooth structure of a user, a cleaning model of the particular user, which describes the tooth model by means of a state of staining, an expectation cleaning model, which describes the tooth model by means of an expected state of cleaning, an actual cleaning model, which is measured by means of corresponding sensors, and a cleaning deviation, which is determined by a comparison of the expected cleaning model with the actual cleaning model. The method comprises the steps of: a) determining the cleaning model and the expectation cleaning model; b) performing a cleaning process as defined by the cleaning model; c) determining the actual cleaning model; d) deriving the cleaning deviation from the actual cleaning model and the expectation cleaning model; e) using the actual cleaning model as new cleaning model, determining the expectation cleaning model on the basis of the new cleaning model, and adapting cleaning instructions on the basis of the cleaning deviation; and f) repeating steps b) to e) until a predetermined termination criterion has been reached.

Description

[0001] Method for cleaning teeth and cleaning system

[0002] The present invention relates to a method for cleaning teeth with a cleaning device and a cleaning system.

[0003] Brushing teeth, like daily washing, is one of the essential cleansing processes of the human body. Yet the technique hasn't changed significantly over the past few centuries.

[0004] Most users use simple, analogue manual toothbrushes or electric toothbrushes, which are constructed like manual toothbrushes but have a motorised, movable head that creates vibration.

[0005] However, the two systems do not differ in the basic way of brushing teeth.

[0006] U-shaped toothbrushes are known for their ability to clean all teeth simultaneously. This technique is also known as 3D cleaning.

[0007] US 2020 / 0179089 A1 discloses an oral hygiene monitoring system that monitors the movement and orientation of oral hygiene devices, such as a toothbrush, during use. This is done using one or more cameras that monitor the movement of the toothbrush from outside the body of the person brushing their teeth. A camera can also be arranged on the oral hygiene device itself, which can be used to record tooth quality.

[0008] US 2020 / 0201266 A1 discloses a cleaning device for a household. This cleaning device can be designed for a wide variety of applications, such as cleaning the floor of a building, shaving a human body, or cleaning teeth. This cleaning device can have a neural network that can determine various properties of an image of the object to be cleaned, such as the color of teeth, in order to influence the cleaning process.

[0009] US 2020 / 0121428 A1 discloses a toothbrushing device comprising a U-shaped and curved splint, allowing it to encompass a row of teeth. Tooth-cleaning elements, such as bristles, are arranged on the inside of the splint, allowing all teeth in a row to be cleaned simultaneously. This toothbrushing device can be configured to execute individual cleaning schedules for a specific person's rows of teeth.

[0010] US 2021 / 0393026 A1 describes an oral hygiene system that is a type of smart toothbrush with an optical sensor for optically scanning the oral cavity. The sensor data can be analyzed using a machine learning system, such as a neural network.

[0011] US 2012 / 0171657 A1 discloses a cleaning system, such as an electric toothbrush, which is connected to a display device on which information and instructions for using the cleaning device are displayed to the user.

[0012] The invention is based on the task of cleaning teeth thoroughly and quickly.

[0013] One or more objects are achieved by the subject matter of the independent claim. Advantageous further developments and preferred embodiments form the subject matter of the dependent claims.

[0014] A method for cleaning teeth with a tooth cleaning device by removing dental contamination uses the following models: - a tooth model that describes the tooth structure of a user,

[0015] - a cleaning model of the respective user, which describes the tooth model with a state of contamination, whereby cleaning instructions for a cleaning process of the teeth are defined on the basis of the cleaning model,

[0016] - an expected cleaning model that describes the tooth model with an expected cleaning state that should be achieved after performing a specific cleaning process as defined by the cleaning model,

[0017] - an actual cleaning model that is actually achieved after carrying out the specific cleaning process as defined by the cleaning model, the actual cleaning model being measured with appropriate sensors,

[0018] - a cleaning deviation, which is determined by comparing the expected cleaning model with the actual cleaning model. a) Determining the cleaning model and the expected cleaning model, b) Executing a cleaning process as defined by the cleaning model, c) Determining the actual cleaning model, d) Deriving the cleaning deviation from the actual cleaning model and the expected cleaning model, e) Using the actual cleaning model as the new cleaning model, determining the expected cleaning model based on the new cleaning model, and adapting the cleaning regulations based on the cleaning deviation, f) Repeating steps b) to e) until a predetermined termination criterion is reached.

[0019] Many users brush their teeth regularly. However, very few brush their teeth consciously or pay attention to the brushing process. Often, they look at their smartphone, watch television, or tidy up small things while brushing. Some people brush their teeth in the shower. Because users are not paying attention to the brushing process, it is comparatively difficult to carry out the brushing steps recommended by the dentist. This includes, for example, thoroughly brushing the necks of the back teeth or the insides of the lower incisors. Typically, users do not pay attention to the degree of dirt on their teeth, but instead perform their routine behavior in the same way every time. Variations in this behavior arise only due to external factors, such as stress, tiredness, or distraction.For example, a user under time pressure will brush their teeth less thoroughly than a user who is fully focused on brushing. This often leads to insufficient cleaning, increasing the likelihood of tooth decay and other dental diseases.

[0020] The advantage of the present invention is that the user's level of contamination is determined independently of the user, and that, based on the contamination level, a cleaning procedure is then performed that is dependent on this level of contamination. The user then no longer needs to concentrate on the actual cleaning process and still receives a thorough cleaning of their teeth.

[0021] The individual tooth position of a user, as well as the user's behavior during the cleaning process, the frequency of cleaning sessions, and their diet all influence the quality of the cleaning process with a cleaning device. Recording all of these parameters and incorporating them into the cleaning instructions can be very complex or even impossible. For example, if the user is a smoker, they would have to record the time of each cigarette smoked to account for cigarette contamination. As described above, certain tooth positions can also minimize the cleaning success of a preset cleaning device.

[0022] To solve these problems, as shown above, the success of the cleaning process is checked at regular intervals in the control loop and compared with the expected cleaning success. This means that with each new cleaning model, the cleaning model is increasingly adapted to the actual conditions and the behavior of the user. At the beginning of the control loop, the cleaning model of all users may be very similar, but the further the control loop progresses, i.e. the more cycles are carried out, the more individual the user's cleaning model becomes compared to other users. The cleaning device can be designed such that a U-shaped section of the cleaning device is inserted into the user's mouth. The U-shaped section of the cleaning device has a nozzle arrangement and is placed over the teeth. A nozzle is arranged above each tooth surface.The nozzles spray a cleaning fluid onto the teeth, removing plaque. The cleaning instructions include parameters for operating the cleaning device, such as cleaning duration, fluid jet pressure, intensity, and / or direction.

[0023] The cleaning device can also be designed with an automatic or semi-automatic brushing device, alternatively or in combination with the nozzle arrangement. The brushing device can also be arranged in a U-shaped section of the cleaning device, which is placed over the teeth. The brushes can be controlled by vibration, rotation, or other translational and / or rotational movement to clean the teeth.

[0024] In principle, any cleaning device can be used for this procedure, but the cleaning instructions must be adapted accordingly. For example, with an electric toothbrush, the cleaning instructions can specify the vibration speed and / or vibration amplitude.

[0025] However, it is also conceivable that a simple manual toothbrush could be used. The brushing instructions would then contain instructions for using the manual toothbrush, which would be displayed to the user as notifications, for example, on their smartphone, such as "Clean the lower back molars more intensively!" or "Brush the upper left canine for 10 seconds!"

[0026] A tooth primarily refers to a natural tooth in the dentures, but the cleaning device also cleans artificial teeth or artificial tooth surfaces that are used as prostheses instead of natural teeth or tooth surfaces. The teeth, including artificial ones, are located in the user's oral cavity.

[0027] Here and in the following, we assume 32 teeth. The procedure described here also works with a different number of teeth. For example, teeth may be missing, especially wisdom teeth, or more teeth may be present in cases of hyperodontia.

[0028] The models are data models that describe processed data related to tooth cleaning and also define the relationships between the data.

[0029] The tooth model, which describes a user's tooth structure, is a mapping of a user's teeth to corresponding data. The tooth model defines a spatial arrangement of the teeth. In the simplest model, this can be the numbers 1-32. The FDI tooth scheme is preferred.

[0030] The cleaning model is based on the tooth model and uses the tooth model to describe the state of contamination of the teeth.

[0031] This can be done, for example, by assigning contamination to a specific tooth in such a way that the area of ​​the tooth surface covered with a biofilm or plaque is given as a percentage.

[0032] However, it is also conceivable that the contamination is indicated in the form of a contamination map of the tooth, whereby the contamination map represents the surface of the associated tooth and this map indicates where a biofilm or plaque is located on the tooth surface.

[0033] From the cleaning model, cleaning instructions for the cleaning process are defined in a predetermined manner. For example, such an assignment can be made such that if a tooth is 75% covered with biofilm, this tooth is cleaned for a specific duration and at a specific intensity.

[0034] The expected cleaning model is preferably calculated before the cleaning process, but can also be calculated independently of the cleaning process. While the expected cleaning model can be output to a user, it is especially crucial when compared to the actual cleaning model to verify how well the forecast and the actual application match.

[0035] Such a deviation can arise, for example, due to incorrect application by a user.

[0036] The cleaning deviation can also be caused by a tooth misalignment that deviates from the norm. To take such a tooth misalignment into account during cleaning, the control loop is executed as described above.

[0037] For example, if a tooth is slightly more indented than the neighboring teeth, cleaning elements cannot reach the corresponding surface of the tooth as easily. In this case, the cleaning elements would have to be set for a correspondingly longer duration or higher cleaning intensity for the affected tooth, even though the plaque on the tooth may not be thicker than that on the surrounding teeth.

[0038] Since there are usually several cleaning processes between a new determination of the cleaning model, individual deviations can add up over the individual cleaning processes, so that the cleaning deviation is negligible after a first cleaning process, but has a significant impact on the cleaning quality after 14 cleaning processes.

[0039] By selecting one or more specific cleaning processes, a specific cleaning effect is expected. By calculating an expected cleaning model and comparing it with the actual cleaning model, the efficiency of the one or more cleaning processes can be assessed. This makes it possible to determine whether the selection of the one or more cleaning processes was successful. Since the cleaning instructions are adjusted based on the cleaning deviation between the actual cleaning model and the expected cleaning model, the efficiency of the one or more cleaning processes performed is taken into account in the future cleaning process(es), and an optimized selection is made. Such an efficiency test of the individual cleaning processes is not known from the state of the art explained above.

[0040] Preferably, a detection device is introduced into the oral cavity, which detects tooth positions, tooth positions and / or tooth contamination, for example a biofilm.

[0041] This allows a tooth model and / or a cleaning model to be generated according to the data measured by the detection device.

[0042] In various embodiments, the cleaning rules are adapted by several cleaning deviations by at least one of the following rules:

[0043] - the areas of the teeth where insufficient cleaning was determined, a stronger, e.g. by more pressure, and / or longer cleaning is prescribed,

[0044] - the direction of the nozzles of the cleaning device are adjusted so that the areas of the teeth in which insufficient cleaning was determined are more in focus of the cleaning jet, and / or

[0045] - the cleaning fluid is adjusted in such a way that if the soiling is too heavy, a cleaning fluid with more particles should be used, and / or

[0046] - if inflammation is detected, the cleaning fluid is adjusted to include anti-inflammatory agents.

[0047] Such an adjustment increases the success of the cleaning without the user having to actively adjust it.

[0048] Preferably, a cleaning trend is formed from several cleaning deviations in a trend module and a user receives instructions according to the cleaning trend.

[0049] Furthermore, the method can be designed such that the cleaning model is executed by a setting module, the expected cleaning model by an analysis module and the actual cleaning model by an evaluation module, the cleaning deviation by a feedback module and that these modules and the trend module are each software modules that can be executed on a computer system that has a processor and a memory.

[0050] Because the individual models are formed by partially different modules, and these individual modules interact with each other, these modules can be arranged in any order. The modules can be implemented on a common computer system or on several individual computer systems, with the models then being exchanged between the modules.

[0051] In embodiments, the setting module, the evaluation module, the analysis module, the feedback module and the trend module can each be executed on at least one of the following devices: the detection device, the cleaning device, a base station, a mobile terminal, such as a smartphone, and / or on a central server.

[0052] The device on which at least one module is executed has a computing system.

[0053] Such a computing system can be designed, for example, as a microprocessor, small or microcomputer, central server, mobile computing unit (smartphone, laptop) or as a PC.

[0054] According to further training, the frequency of tooth cleaning procedures is taken into account.

[0055] For example, it's important to distinguish whether a user brushes their teeth with the cleaning device only once a week or three times a day. It might also be important to consider whether a user brushes their teeth with other cleaning devices, such as a conventional toothbrush, in between.

[0056] In the case of product liability claims, however, the frequency of use can also be used to prove insufficient regularity of use. The number of cleaning processes is preferably taken into account when creating the expected cleaning model for comparison with the actual cleaning model.

[0057] Alternatively, an expectation cleaning model is created for each cleaning process.

[0058] For example, a distinction must be made between whether a user creates a new cleaning pattern every two weeks and brushes twice a day, or whether a user creates a cleaning pattern once a day. The less frequently a user creates a cleaning pattern, the greater the cleaning deviation will be.

[0059] A cleaning system for cleaning teeth by removing dental contamination comprises a cleaning device and a detection device and is particularly designed to carry out a method described above.

[0060] Preferably, the detection device comprises a detection capsule containing a detection liquid, and the cleaning device comprises one containing a cleaning liquid.

[0061] The detection fluid contains a substance that adheres particularly well to a biofilm and glows with a second wavelength when illuminated with a specific wavelength.

[0062] The cleaning fluid contains elements that can remove biofilm.

[0063] Preferably, there are different cleansing capsules, each with different cleaning fluids, e.g. with different concentrations of particles and / or agents to combat inflammation.

[0064] The selection of a specific cleaning capsule can be time-controlled, e.g. a cleaning capsule of type 1 (intensive cleaning) should be used for the first ten applications and then a cleaning capsule of type 2 (standard) should be used for the next applications.

[0065] The selection of cleaning capsules can also be controlled by appropriate cleaning instructions. Depending on the requirements, a specific cleaning capsule is required for a specific cleaning fluid.

[0066] Alternatively, the cleaning fluid and / or detection fluid can also be manually introduced into the oral cavity. For this purpose, a predetermined amount of cleaning fluid and / or detection fluid is taken into the oral cavity by the user without swallowing and distributed throughout the oral cavity through mouth movements.

[0067] According to a further development, the detection capsule and / or the cleaning capsule is provided with a marker, wherein the marker contains one or more pieces of information.

[0068] This data can preferably also be added subsequently, e.g. during the sales process or by the user themselves.

[0069] The marker contains information such as:

[0070] - Particle content, for example to select the cleaning program,

[0071] - Flavor, for example, to adjust the display color to the flavor, for example red for cherry, blue for peppermint,

[0072] - Liquid composition, for example, an indication that the device must be shaken before use if the composition is critical for sedimentation,

[0073] - Expiry date,

[0074] - Cleaning fluid and / or detection fluid, for example, to prevent them from being mixed up,

[0075] - whether it contains a disinfectant liquid,

[0076] - a serial number, so that, for example, previously used capsules cannot be reused or refilled capsules can be identified. In the case of multiple use or the detection of counterfeit capsules, compatibility, for example, whether the capsule fits in the device, is also checked.

[0077] - Source and distribution channel of the capsule for traceability from production through the distribution channel to the customer,

[0078] - Lead time from sale to use,

[0079] - Time in the cooling / heating / storage station, which allows tracking of the heating time applied,

[0080] - Information about the buyer (whether he is the user or someone else uses the device),

[0081] - User name for personal greeting,

[0082] - User language,

[0083] - Residential address including country and time zone of the user,

[0084] - User's email address,

[0085] - User's telephone number,

[0086] - Preference for the display background (images, gradients),

[0087] - User competence in beginner / advanced / expert for usability and expert settings,

[0088] - Calibration data for gestures from previous device.

[0089] In embodiments, the marker is an RFID tag, in particular an NFC tag.

[0090] Another possibility is that the marker has a barcode, QR code, color code or other printed marker.

[0091] Preferably, the detection device and / or the cleaning device also comprises a marker, in particular an NFC tag, as previously described.

[0092] This marker may include one or more of the following information:

[0093] - User name e.g. for personal greeting,

[0094] - User language,

[0095] - Residential address including country and time zone of the user,

[0096] - User's email address,

[0097] - User's phone number, - Preference for the display background (images, gradients),

[0098] - User competence in beginner / advanced / expert for usability and expert settings, and / or

[0099] - Calibration data for gestures from previous device.

[0100] The invention is explained in more detail below using the drawings. The drawings show:

[0101] Figure 1 shows a schematic block diagram of the cleaning system,

[0102] Figure 2a schematically shows part of the cleaning device for cleaning molars,

[0103] Figure 2b schematically shows part of the cleaning device for cleaning incisors,

[0104] Figure 3 shows the time course of a cleaning trend and

[0105] Figure 4 Cleaning process in block diagram.

[0106] The cleaning system 1 comprises a cleaning device 2, a detection device 3, a base station 4, an interface for a data terminal 5, e.g., a smartphone 5, and a central server 6, each of which comprises a computing system 7. Each computing system 7, in turn, comprises a processor and a memory.

[0107] Such a detection device 3 is described in detail, for example, in the not yet published German patent application DE 102022 102 045.2, to which reference is made in its entirety. The detection device 3 is designed to generate the cleaning model 14.

[0108] Basically, the detection device 3 is designed such that a U-shaped section of the detection device 3 is inserted into the oral cavity of a user. The U-shaped section of the detection device 3 has a sensor arrangement.

[0109] The U-shaped section is placed over the teeth so that all tooth surfaces can be detected by a sensor.

[0110] To make a biofilm more visible, a detection fluid is introduced into the oral cavity prior to the detection procedure. The detection fluid interacts with the biofilm and, under the influence of light of a predetermined wavelength, causes it to glow at a different predetermined wavelength.

[0111] The detection fluid is arranged in a detection capsule that can be inserted into the detection device 3. The detection device then extracts the detection fluid and pumps it onto the teeth.

[0112] For this purpose, the detection device 3 consists of a handpiece, which may have a display on the side facing away from the user. On the side facing the user, there is a mouthpiece that is inserted into the oral cavity and guides the sensor unit over the teeth.

[0113] The mouthpiece has at least one camera unit with a camera.

[0114] The camera unit alone, for example, measures 1 x 1 x 2.7 mm, while the entire sensor unit, including a protective glass, PCB (printed circuit board), filter, and camera mount, has a diameter of 8 mm and a height of 3.8 mm. These dimensions allow the unit to be easily inserted into the oral cavity.

[0115] To ensure a good signal-to-noise ratio, an optical long-pass filter is preferably placed directly in front of the camera. Ideally, this filter has a cutoff wavelength of approximately 510 nm and cuts off signals below this wavelength. Additionally, a band-pass or short-pass filter can be placed in front of the LEDs illuminating the area to be detected to limit the wavelength spectrum of the LEDs. The cleaning device 2 is described in detail in the not yet published German patent application 10 2020 134 154.7, and this patent application is incorporated by reference in its entirety.

[0116] Basically, the cleaning device 2 is designed such that a U-shaped section of the cleaning device 2 is inserted into the oral cavity of a user. The U-shaped section of the cleaning device 2 has a nozzle arrangement and is placed over the teeth. A nozzle is arranged over each tooth surface.

[0117] The nozzle of the nozzle assembly pumps a cleaning fluid onto the teeth in such a way that a biofilm located on the teeth is removed.

[0118] In this embodiment, the cleaning fluid is a cleaning liquid and may contain particles to accelerate the removal process.

[0119] The cleaning fluid is contained in a cleaning capsule that can be inserted into the cleaning device 2. The cleaning device 2 then removes the cleaning fluid and pumps it onto the teeth.

[0120] To prevent the cleaning fluid from entering the oral cavity uncontrollably, sealing elements in the form of sealing lips are arranged on a nozzle arrangement, i.e., a sequence of nozzles. The sealing lips seal off the area around the nozzle arrangement, creating a fluid cushion similar to an air cushion, but with the difference that the fluid is prevented from escaping to the outside.

[0121] Accordingly, in this simplified embodiment, a nozzle housing is shown in a highly schematic manner (Figures 2a and 2b) which has a nozzle opening, wherein the nozzle housing is simplified here with a rectangular cross-section.

[0122] On an outer outlet side facing the surface to be cleaned

[0123] Appropriate sealing elements are provided in the area of ​​the outer edges of the nozzle housing. The sealing elements can also be designed as a single, circumferential sealing element and are rubber-elastic, so that they adapt to the geometry of the surface to be cleaned and are also capable of maintaining a certain internal pressure of the fluid in the enclosed space.

[0124] The sealing elements can be designed, in particular, as circumferential sealing elements or sealing lips that extend from the outlet-side surface of the nozzle housing. The sealing elements or sealing lips can be designed with a certain inherent rigidity, so that the basic shape of the enclosed space is formed and maintained.

[0125] In addition, the sealing elements or sealing lips can be hollow in order to be inflated, for example, with the cleaning fluid, so that the sealing elements only achieve the shape they are intended to have during operation after being inflated, for example, with the cleaning fluid or by the cleaning fluid or by other fluids that are supplied separately.

[0126] In a simple embodiment, particularly for cleaning in the area of ​​the molars, the nozzle housing has, for example, five nozzle openings located one above the other in the (jaw) sides or opposite the tooth flanks and four adjacent nozzle openings on the bottom, opposite a tooth crown and the corresponding sealing elements which close off the corresponding enclosed space.

[0127] In the incisor region, such an embodiment differs in particular in the shape of the sealing elements, if applicable, but also in the angulation of the nozzle housing and the base nozzle housing in order to achieve adaptation to the incisor region. In the incisor region, the base nozzle housing can also be designed without nozzles if sufficient flow to an incisor is ensured through the nozzle openings in the nozzle housings, which are located opposite one another. In order to prevent the enclosed space from filling with liquid without this liquid being drained away again in a controlled manner, one embodiment provides for the inventive re-suction. In the simplest case, the liquid is ejected through the nozzle or the nozzle opening into the enclosed space and then sucked back through the nozzle opening.In order to avoid having to fill the enclosed space with one or more nozzles before the actual cleaning operation begins, an inlet can be provided in the nozzle housing for one or more or all nozzles.

[0128] Since the cleaning fluid may contain particles, the cleaning performance is also determined by the particles and the particle flow. Since the particles have a higher density than the surrounding fluid, the fluid moves tangentially away from the surface when it hits it, while the particles hit the surface and damage the biofilm or plaque, thereby contributing to its removal.

[0129] The cleaning capsule and the detection capsule each contain an NFC tag that stores a variety of information. The NFC tag can be read by the individual devices. The stored information includes, among other things:

[0130] - type of liquid contained,

[0131] - taste of the liquid,

[0132] - Expiry date, and

[0133] - Serial number.

[0134] Various software modules are stored in executable form on the computer systems 7 of the individual devices. A setting module 8, an evaluation module 9, and an analysis module 10 are provided on the detection device 3, a feedback module 11 on the smartphone 5, and a trend module 12 on the central server 6.

[0135] The modules are designed to communicate with each other via wireless communication, such as Wi-Fi, Bluetooth, 433 MHz band, Zigbee, and Z-Wave. In this exemplary embodiment, a cleaning model 14 is created by the setting module 8, an expected cleaning model 15 by the analysis module 10, an actual cleaning model 16 by the evaluation module 9, a cleaning deviation 17 by the feedback module 11, and a cleaning trend 18 by the trend module 12.

[0136] In principle, the individual modules can also be implemented on other devices. For example, it is conceivable that the base station 4, instead of the smartphone 5, could implement the feedback module 11. The base station 4 can also be designed such that several or all modules can be implemented on it. The detection device 3 and the cleaning device 2 then send and receive the data accordingly.

[0137] The tooth model 13 used here corresponds to the FDI (Federation Dentaire Internationale) tooth chart. Here the teeth are divided into four quadrants: quadrant 1 with the upper jaw on the right, quadrant 2 with the upper jaw on the left, quadrant 3 with the lower jaw on the left and quadrant 4 with the lower jaw on the right. Each quadrant indicates the tens digit of a tooth number for the tooth model 13. For example, the teeth in quadrant 1 are teeth 11 - 18 and the teeth in quadrant 4 are teeth 41 - 48. The ones digits are determined by the position of the teeth in the respective quadrant. For example, the first two teeth are given the numbers 1 and 2, the canine the number 3, the small molars the numbers 4 and 5, the large molars the numbers 6 and 7 and the wisdom tooth the number 8. For example, the canine of the upper jaw on the left is numbered 23.

[0138] In this exemplary embodiment, the cleaning model 14 supplements the tooth model 13 with a contamination value that represents the surface contamination of a tooth as a percentage of the total surface of the respective tooth. The contamination value is, for example, 50% if half of the surface of the tooth is covered with a biofilm. The cleaning model 14 has such a percentage value for each entry for each tooth from the tooth model 13. For example, if the wisdom tooth of the lower jaw on the right is 32% covered with a biofilm, the entry would be: "48: 32%." This contamination value is determined by the detection device 3, preferably for each tooth, and assigned to the cleaning model 14. In principle, it is also possible to determine contamination values ​​for several adjacent teeth.

[0139] It is also conceivable that several contamination values ​​are determined for one tooth in order to take into account the inner, outer and, if applicable, chewing surfaces of the tooth.

[0140] The cleaning device 2 with the computing system 7a receives the user's cleaning model 14 and generates cleaning instructions based on this cleaning model 14.

[0141] These cleaning instructions specify how long and with what intensity the jets should act on the teeth. Generally speaking, the more severe the contamination, determined by the contamination level, the longer and more intensive the tooth cleaning is. The relationship between cleaning time and / or pumping power and the contamination level can be linear, exponential, or quadratic.

[0142] The cleaning instructions for the respective contamination levels can be stored in a database or table or given by a function.

[0143] For example, if an entry in cleaning model 14 is “14: 73%”, it means that the front small molar of the upper right jaw is covered with 73% biofilm.

[0144] The cleaning device 2 compares this with a stored table and determines that if the front small molar of the upper jaw on the right is covered with a biofilm between 70 and 80%, the corresponding nozzle works at 90% of the maximum intensity for a duration of 1 to 2 seconds.

[0145] In one cleaning process, the user's teeth are then cleaned according to all cleaning instructions.

[0146] The detection device 3, on which an analysis module 10 is running, calculates an expected cleaning model 15 based on the cleaning instructions sent by the cleaning device 2. In this exemplary embodiment, this model has the same formatting as the cleaning model 14. This means that for a single tooth with the entry "14: 73%" in the cleaning model 14, a corresponding expected cleaning model 15 would look like this: "14: 3%." The detection device therefore calculates that the contamination will drop from 73% to 3%.

[0147] The detection device 3 also determines the actual cleaning model 16 after a cleaning process. The actual cleaning model 16 is determined using the same method as the cleaning model 14. The data structure of the cleaning model 16 is also identical to the cleaning model 14.

[0148] The smartphone 5, which has the computing system 7b on which the feedback module 11 is executed, receives the expected cleaning model 15 and the actual cleaning model 16 from the detection device 3 and compares them to determine the cleaning deviation 17. For example, if the actual cleaning model 16 has been determined such that the entry for a tooth is "14: 13%," a cleaning deviation 17 will have the following form: "14: 10%," since the difference between the expected and the target value for tooth 14 is 10%.

[0149] The actual cleaning model 16 and the cleaning model 14 are transmitted from the detection device 3 to the central server 6, which uses the central server's computing system 7c, on which the trend module 12 is executed, to determine a cleaning trend 18. The cleaning trend 18 is sent from the central server 6 to the smartphone 5, where a user can be notified of potential misconduct, for example, if the cleaning trend indicates that they are not using the cleaning device 2 correctly. It is also possible for the cleaning trend 18 to be used to adjust the cleaning instructions of a cleaning device 2.

[0150] The following describes the method for cleaning teeth with a tooth cleaning device (see Figure 4). The method begins with step S1.

[0151] In the next step (S2), the cleaning model 14 and the expectation cleaning model 15 are determined.

[0152] For this purpose, the detection device 3 is inserted into the oral cavity of a user and the detection device 3 detects the degree of contamination of the individual teeth of the user.

[0153] The setting module 8 of the detection device 3 creates the cleaning model 14 by adding a predefined tooth model 13 with the results of the detection.

[0154] What the tooth model 13 and the cleaning model 14 can look like is described in detail above.

[0155] The cleaning model 14 is sent to the cleaning device 2. The cleaning device 2 generates cleaning instructions based on the cleaning model 14 and sends the cleaning instructions back to the detection device 3.

[0156] The detection device 3 generates an expected cleaning model 15 based on the cleaning model 14 and the cleaning instructions.

[0157] In the simplest case, it is possible to read from a stored table what the expected cleaning model 15 will be for a given cleaning model 14 with given cleaning instructions. As described above, for example, an entry in the cleaning model 14 is "14: 73%." This means that the right front molar of the upper jaw is covered with 73% biofilm. The cleaning device 2 compares this with a stored table and determines that if the right front molar of the upper jaw is covered with between 70 and 80% biofilm, the corresponding nozzle must operate at 90% of its maximum intensity for a duration of 1.5 seconds. A cleaning process is then carried out (step S3).

[0158] For this purpose, the cleaning device 2 is inserted into the user's mouth and the nozzles clean the teeth according to the cleaning instructions.

[0159] Step S4 follows, in which the actual cleaning model 16 is determined.

[0160] The actual cleaning model 16, like the cleaning model 14, is determined by the detection device 3. The actual cleaning model 16 is determined in the same way as the cleaning model 14. The data structure of the cleaning model 16 is also identical to the cleaning model 14.

[0161] In the following step (S5), a cleaning deviation 17 is derived. For this purpose, the expected cleaning model 15 and the actual cleaning model 16 are sent from the detection device 3 to the feedback module 11 of the smartphone 5.

[0162] Feedback module 11 checks how much the actual cleaning model 16 and the expected cleaning model 15 differ from each other. In the examples described above for the actual cleaning model 16 and the expected cleaning model 15, the difference is 10% (see above).

[0163] This 10% corresponds to the cleaning deviation value for the corresponding tooth. Cleaning deviation 17 has the same data structure as cleaning model 14, expected cleaning model 15, and actual cleaning model 16. However, the percentage here indicates the difference between expected cleaning model 15 and actual cleaning model 16.

[0164] The cleaning deviation value can also be negative if the cleaning is performed better than predicted. Then, in step S6, the actual cleaning model 16 is used as the new cleaning model 14, a new expected cleaning model 15 is determined (comparable to step S2), and the cleaning specifications are adjusted.

[0165] The cleaning instructions are adjusted, preferably only if the cleaning deviation 17 exceeds a predetermined threshold. This could be, for example, 5%.

[0166] It is also conceivable to select only the amount of cleaning deviation 17 above a predetermined threshold as the criterion for adjusting the cleaning regime. Thus, the cleaning deviation 17 can certainly be negative if the teeth are cleaned better than expected. Even in this case, adjusting the cleaning regime makes sense, as this may save time or reduce the pressure exerted by the nozzles on the teeth and gums, thus protecting the user's gums.

[0167] In order to adapt the cleaning instructions, a corresponding instruction is sent from the feedback module 11 of the smartphone 5 to the cleaning device 2.

[0168] The new cleaning model 14 is in turn sent to the detection device 3, which receives the revised cleaning instructions from the cleaning device 2.

[0169] In the subsequent step S7, it is checked whether a termination condition exists.

[0170] A termination condition exists, for example, if the user has disposed of the cleaning system 1 or has not used it for a predetermined period of time, such as one year. It is also conceivable that such a termination condition exists if the user of the cleaning system has changed, for example, by reselling the device.

[0171] If no termination condition exists, the process repeats, beginning with step S2. If a termination condition exists, the process ends with step S8.

[0172] Another possibility is to determine the cleaning trend 18 using the trend module 12 on the central server 6. Here, each cleaning model 14 and each actual cleaning model 16 is sent from the detection device 3 to the central server 6. The trend module 12 of the central server 6 determines the cleaning trend 18 from the individual cleaning models 14 and actual cleaning models 16 by examining the degree of cleaning over time for each tooth.

[0173] During normal use, it can be assumed that the overall cleaning success will increase over time with regular use of the cleaning device 2 compared to the state before the first use, ie the user's teeth will gradually be freed from the biofilm and the teeth will become cleaner.

[0174] However, it may be the case that individual teeth or rows of numbers, or even all of the user's teeth, are not getting cleaner or are even becoming more contaminated. This is a strong indication that the user is using the cleaning device 2 incorrectly. For example, the user may not be fully applying the cleaning device 2 over their teeth.

[0175] If the cleaning trend 18 does not follow the desired course, this could also be an indication that the cleaning device 2 is defective and / or individual components need to be replaced because they have become defective or dilapidated after intensive use.

[0176] The central server 6 then sends a corresponding notification to the smartphone 5 to notify the user. Here, the user can be prompted to use the cleaning device 2 correctly according to the instructions or, if necessary, to replace individual elements.

[0177] The cleaning trend 18 can also provide information on how to adjust the cleaning instructions. In this case, a user is not necessarily notified by the smartphone 5; instead, the central server 6 sends corresponding instructions to the smartphone 5, which forwards them to the cleaning device 2 to adjust the cleaning instructions.

[0178] Preferably, in the steps before the cleaning model 14 and / or the actual cleaning model 16 is created, the NFC tag of the detection capsule is read by the detection device 3 so that the information stored there is stored as metadata in the corresponding model.

[0179] It is also advantageous if, before the cleaning process, the NFC tag of the cleaning capsule is read by the cleaning device 2 and sent to the detection device 3. Alternatively, the data can also be sent to the smartphone 5 for further processing.

[0180] Another possibility is for the cleaning device 2 and / or the detection device 3 to have sensors that allow conclusions to be drawn about the state of these devices. The sensors can be, for example, acceleration sensors that measure acceleration values ​​due to device vibrations and analyze their change over time. The data can be sent to the central server 6 for analysis. In the case of acceleration sensors, it can be determined, for example, that the frequency spectrum and / or the amplitude of the acceleration is changing. The central server 6 can then send a corresponding message to the smartphone 15 to inform the user of the necessary steps.

[0181] Acceleration sensors can also be used to detect whether the device suddenly stops measuring gravitational acceleration and is therefore in free fall. Based on the length of this phase, the fall height can be determined, which could help prevent unjustified warranty claims and / or send a message to the user that the device requires servicing.

[0182] In an alternative embodiment, the images captured by the detection device 3 are analyzed using a self-learning system. Due to the detection fluid used and the selected wavelength filter, the contrast for the biofilm is very high. The biofilm has a high signal-to-noise ratio, which, however, makes other objects, such as the tooth surface, difficult to detect. The areas not covered by a biofilm are difficult to distinguish from one another. The particular difficulty here is distinguishing the tooth from the surrounding tissue, such as the gums, lip, and other features in the mouth.

[0183] Using artificial intelligence, pattern recognition can analyze slight differences in brightness to distinguish tooth from non-tooth objects.

[0184] Preferably, trained pattern recognition is used here.

[0185] For this purpose, captured images are manually analyzed by manually marking the area of ​​the image that corresponds to the tooth. This information, along with additional information such as the camera position and / or tooth position, is then passed on to the self-learning system, which preferably comprises a neural network, for learning.

[0186] If the self-learning system has been given enough images with appropriate additional data and markings to learn from, the system is able to independently mark new images of teeth in such a way that the tooth areas can be distinguished from non-tooth areas.

[0187] According to a further development, one or more devices of the cleaning system can be unlocked by a biometric method.

[0188] Reference symbol

[0189] cleaning system

[0190] Cleaning device

[0191] Detection device

[0192] Base station

[0193] Smartphone central server

[0194] Calculation system

[0195] Setting module

[0196] Evaluation module

[0197] Analysis module

[0198] Feedback module

[0199] Trend module

[0200] Tooth model

[0201] Cleaning model

[0202] Expectation cleaning model

[0203] Current cleaning model

[0204] Cleaning deviation

[0205] Cleaning trend

Claims

Claims 1. Method for cleaning teeth with a dental cleaning device by removing dental plaque, which uses the following models - a dental model that describes a user's tooth structure, - a cleaning model of the respective user, which describes the tooth model with a state of soiling, whereby cleaning instructions for a cleaning process of the teeth are defined based on the cleaning model, - an expectation cleaning model that describes the tooth model with an expected state of cleanliness that should be achieved after performing a specific cleaning procedure as defined by the cleaning model, - an actual cleaning model that is actually achieved after performing the specific cleaning process as defined by the cleaning model, whereby the actual cleaning model is measured with appropriate sensors, - a cleaning deviation, which is determined by comparing the expected cleaning model with the actual cleaning model, whereby a control loop is executed with the following steps: a) Determine the cleaning model and the expected cleaning model, b) Execute a cleaning process as defined by the cleaning model, c) Determine the actual cleaning model, d) Derive the cleaning deviation from the actual cleaning model and the expected cleaning model, e) Use the actual cleaning model as the new cleaning model, determine the expected cleaning model based on the new cleaning model and adjust the cleaning instructions based on the cleaning deviation, f) Repeat steps b) to e) until a predetermined termination criterion is reached.

2. Method according to one of the preceding claims, characterized in that a detection device is inserted into the oral cavity which detects tooth positions, tooth positions and / or tooth soiling, e.g. a biofilm.

3. Method according to one of the preceding claims, characterized in that the adaptation of the cleaning instructions by several cleaning deviations is carried out by at least one of the following rules: - In areas of the teeth where insufficient cleaning was identified, a more intensive cleaning is prescribed, e.g. by more pressure, and / or longer cleaning. - The direction of the nozzles of the cleaning device is adjusted so that the areas of the teeth where insufficient cleaning has been identified are more in focus of the cleaning jet, and / or - The cleaning fluid is adjusted so that in case of excessive soiling, a cleaning fluid with more particles should be used, and / or - If inflammation is detected, the cleaning fluid is adjusted to include anti-inflammatory agents.

4. Method according to one of the preceding claims, characterized in that a cleaning trend (CT) is formed from several cleaning deviations (CD) in a trend module and a user receives instructions according to the cleaning trend.

5. Method according to one of the preceding claims, characterized in that the cleaning model is formed by a setting module, the expected cleaning model by an analysis module, and the actual cleaning model by an evaluation module, and the cleaning deviation by a feedback module, and that these modules and the trend module are each software modules that are executable on at least one computing system which has a processor and a memory.

6. Method according to one of the preceding claims, characterized in that the setting module, the evaluation module, the analysis module, the feedback module and the trend module can each be implemented on at least one of the following devices: the detection device, the cleaning device, a base station, a data terminal, e.g. a smartphone, and / or on a central server.

7. Method according to one of the preceding claims, characterized in that the setting module is executed on the detection device, the evaluation module on the detection device, the analysis module on the detection device, the feedback module on the smartphone and the trend module on the central server.

8. Method according to one of the preceding claims, characterized in that the frequency of tooth cleaning procedures is taken into account.

9. Method according to one of the preceding claims, characterized in that the number of cleaning processes is taken into account when creating the expected cleaning model in order to compare it with the actual cleaning model.

10. A cleaning system for cleaning teeth by removing dental stains comprises a cleaning device and a detection device and is particularly designed to perform a method according to one of claims 1 to 9.

11. Cleaning system according to claim 10, characterized in that the detection device has a detection capsule which has a detection- The cleaning device contains a cleaning fluid and has a cleaning capsule which contains a cleaning fluid.

12. Cleaning system according to claim 10 or 11, characterized in that the detection capsule and / or the cleaning capsule is provided with a marker, wherein the marker contains one or more pieces of information.

13. Cleaning system according to one of claims 10 to 12, characterized in that the marker is an RFID tag, in particular an NFC tag.

Images