System for detecting blood in an oral cavity during tooth brushing

Abstract

In one aspect, a system for detecting blood in an oral cavity during tooth brushing is disclosed. A toothbrush includes a sensor configured to emit a first light of a first wavelength and a second light of a second wavelength, and to receive a reflected portion of the lights having a first intensity and a second intensity, respectively. A processor calculates a ratio of the first intensity to the second intensity for each of a plurality of different times in a tooth brushing session. The processor identifies a peak of the ratio for the different times, and determines whether hemoglobin is present in the oral cavity based on a number of peaks of the ratio.

Description

[0001] Cross-references to related applications

[0002] This application claims priority to U.S. Provisional Application No. 63 / 109,031, filed November 3, 2020, the contents of which are incorporated herein by reference in their entirety. Background Technology

[0003] There are several different causes of bleeding gums and other oral cavity problems. Some of these are mechanical, such as excessive brushing force, using a toothbrush with hard bristles, incorrect brushing or flossing technique, or improperly fitted dentures. Gum disease can also cause bleeding due to inflammation of the gum tissue. Other important causes can be systemic, such as medications (e.g., blood thinners), pregnancy (hormonal changes), diabetes, vitamin deficiencies (e.g., C or K deficiency), leukemia, etc. Although the American Dental Association recommends that people with bleeding gums see a dentist or doctor, most people do not experience pain when they have bleeding gums and therefore ignore this advice. Therefore, there is a need to provide consumers with brushing systems that can monitor and / or record bleeding gums during regular brushing. Summary of the Invention

[0004] This invention relates to a system and / or method for detecting hemoglobin and / or blood in the oral cavity during brushing, and a toothbrush capable of performing the same operation.

[0005] In one aspect, a system for detecting blood in the oral cavity during brushing includes a toothbrush comprising a sensor configured to: emit a first light of a first wavelength and a second light of a second wavelength; receive reflected portions of the first light and the second light; and, for a plurality of different times, generate a first signal indicating a first intensity of the reflected portion of the first light and a second signal indicating a second intensity of the reflected portion of the second light; and a processor operatively coupled to the sensor and configured to, for each of the plurality of different times, receive the first signal and the second signal and calculate a ratio of the first intensity to the second intensity; identify peaks of the ratio corresponding to the different times; and determine the presence of hemoglobin in the oral cavity based on the number of peaks of the ratio corresponding to the different times.

[0006] On the other hand, a method for detecting blood in the oral cavity during brushing includes, during a brushing period when the toothbrush is used to brush the oral cavity, emitting a first light of a first wavelength and a second light of a second wavelength into the oral cavity via a sensor on the toothbrush; receiving reflected portions of the first light and the second light via the sensor on the toothbrush; and for each of a plurality of different times during the brushing period, sending from the sensor to a processor a first signal indicating a first intensity of the reflected portion of the first light and a second signal indicating a second intensity of the reflected portion of the second light; for each of the plurality of different times, calculating by the processor a ratio of the first intensity to the second intensity; identifying peaks of the ratio corresponding to different times by the processor; and determining, by the processor, the presence of hemoglobin in the oral cavity based on the number of peaks of the ratio corresponding to different times.

[0007] On the other hand, a system for detecting blood in the oral cavity during brushing includes a toothbrush comprising a sensor configured to: emit a first light of a first wavelength and emit a second light of a second wavelength; receive reflected portions of the first light and the second light, and generate a first signal indicating a first intensity of the reflected portion of the first light and a second signal indicating a second intensity of the reflected portion of the second light; and a processor operatively coupled to the sensor and configured to receive the first signal and the second signal for a plurality of different times; and calculate a ratio of the first intensity to the second intensity; wherein the ratio at the different times forms data points; identify which data points are within a predetermined boundary and which data points are outside the predetermined boundary; and determine the presence of hemoglobin in the oral cavity based on the characteristics of the data points within or outside the predetermined boundary.

[0008] On the other hand, a method for detecting blood in the oral cavity during brushing includes, during a brushing period when the toothbrush is used to brush the oral cavity, emitting a first light of a first wavelength and a second light of a second wavelength into the oral cavity via a sensor on the toothbrush; receiving reflected portions of the first light and the second light via the sensor on the toothbrush; and, for a plurality of different times during the brushing period, sending from the sensor to a processor a first signal indicating a first intensity of the reflected portion of the first light and a second signal indicating a second intensity of the reflected portion of the second light; for each of the plurality of different times, calculating by the processor a ratio of the first intensity to the second intensity, wherein the ratios of the different times form data points; identifying by the processor which of the data points are within a predetermined boundary and which of the data points are outside the predetermined boundary; and determining by the processor, based on the characteristics of the data points within the predetermined boundary or the data points outside the predetermined boundary, whether hemoglobin is present in the oral cavity. Attached Figure Description

[0009] The present invention will be more fully understood from the specific embodiments and accompanying drawings, in which:

[0010] Figure 1 This is a perspective view of a toothbrush having a body and a replacement head (wherein the replacement head is in a disassembled state) according to an embodiment of the present invention.

[0011] Figure 2 yes Figure 1 A perspective view of a toothbrush, in which the replacement head is attached;

[0012] Figure 3 This is a perspective view of a replacement toothbrush (with the replacement head in an attached state) according to an embodiment of the present invention;

[0013] Figure 4 yes Figure 1 A schematic diagram of the sensor in a toothbrush;

[0014] Figure 5A and 5B This is according to an embodiment of the present invention. Figure 4 A schematic diagram of a sensor sending light into toothpaste slurry and receiving the reflected light;

[0015] Figure 6 It is based on the scatter plot of the experiment, which shows the result of... Figure 1 The toothbrush was used to perform calculations to determine the presence of hemoglobin in the oral cavity;

[0016] Figure 7 It is shown by Figure 1 A graph showing the experimental results of calculations performed using a toothbrush to determine the presence of hemoglobin in the oral cavity;

[0017] Figure 8 A system for detecting blood in the oral cavity is shown, the system comprising a toothbrush and a portable electronic device that are operatively communicating with each other;

[0018] Figure 9 yes Figure 8 Electrical block diagram of the electronic components of a toothbrush system and portable electronic devices;

[0019] Figure 10A and 10B Is Figure 8 An illustration of a software application launched on the display of the system's portable electronic device, in which the software application indicates whether blood is found in the mouth;

[0020] Figure 11 Is Figure 8An illustration of a software application launched on the display of a portable electronic device of the system, which displays data logs related to the detection of blood in the mouth during many brushing sessions.

[0021] Figures 12A to 12B These are graphs showing the R / G ratio and IR / G ratio over time in typical bleeding patients.

[0022] Figures 13A to 13B These are graphs showing the R / G ratio and IR / G ratio over time in typical non-bleeding patients.

[0023] Figure 14 This is a graph showing the average number of normalized peaks for each group member using the R / G ratio.

[0024] Figure 15 This is a graph showing the average number of normalized peaks for each group member using the IR / G ratio.

[0025] Figure 16A This is a graph showing the R / G ratio versus IR / G ratio for patients experiencing bleeding during a single brushing session.

[0026] Figure 16B This is a graph showing the R / G ratio relative to the IR / G ratio for those who did not bleed during a single brushing session.

[0027] Figure 17 It is a graph of the average normalized vector lengths of the R, G, and IR channels for data points outside the predetermined bounding box of each participant.

[0028] Figure 18 This is a graph showing the average normalized vector length for each participant over 5 brushing cycles for a model using only IR and G channels.

[0029] Figure 19 This is a graph showing the average normalized vector length for each participant over 5 brushing cycles for a model that uses only the R and G channels.

[0030] Figure 20A and 20B The graphs show the average normalized spread of the data points in the box for each group member over five brushing cycles, based on the first and second methods, respectively.

[0031] Figure 21 This is a graph showing the average normalized cluster distribution of participants over 5 brushing cycles for a model using only IR and G channels.

[0032] Figure 22 This is a graph showing the average normalized cluster distribution of 11 participants over 5 brushing cycles for a model using only R and G channels. Detailed Implementation

[0033] The following description of preferred embodiments is merely exemplary in nature and is in no way intended to limit the invention, its application, or its uses.

[0034] The description of exemplary embodiments of the invention is intended to be read in conjunction with the accompanying drawings, which will be considered part of the entire written description. Any references to orientation or direction in the description of embodiments of the invention disclosed herein are intended only for convenience of description and are not intended to limit the scope of the invention in any way. Relative terms such as “lower,” “upper,” “horizontal,” “vertical,” “above,” “below,” “upward,” “downward,” “top,” and “bottom,” and their derivatives (e.g., “horizontally,” “downward,” “upward,” etc.) should be understood to refer to orientations as shown in the drawings described later or discussed. These relative terms are for convenience of description only and do not require the device to be constructed or operated in a particular orientation unless explicitly stated otherwise. Terms such as “attach,” “connect,” “join,” “interconnect,” and similar terms refer to a relationship in which structures are fixed or attached to each other, either directly or indirectly, through an intermediary structure, and to a movable or rigid attachment or relationship between the two, unless otherwise explicitly stated otherwise. Furthermore, the features and beneficial effects of the invention are illustrated with reference to the exemplified embodiments. Therefore, the invention should not be obviously limited to such exemplary embodiments showing some possible non-limiting combinations of features that may exist alone or in combination with other features; the scope of the invention is defined by the appended claims.

[0035] The term "range" is used throughout as a concise expression to describe each value within the range. Any value within the range can be chosen as an endpoint of the range. Furthermore, all references cited herein are incorporated in full. In the event of any conflict between definitions in this disclosure and those in the cited references, this disclosure shall prevail.

[0036] The features of this invention may be implemented in software, hardware, firmware, or a combination thereof. The computer or software program described herein is not limited to any particular embodiment and may be implemented in an operating system, application, foreground or background process, driver, or any combination thereof. The computer program may execute on a single computer or server processor or multiple computers or server processors.

[0037] The processor described herein can be any central processing unit (CPU), microprocessor, microcontroller, computing or programmable device, or circuitry configured to execute computer program instructions (e.g., code). Various processors can be embodied in any suitable type of computer and / or server hardware (e.g., desktop, laptop, notebook, tablet, cellular phone, etc.) and can contain all the conventional auxiliary components required to form a functional data processing device, including, but not limited to, buses, software and data memory (such as volatile and non-volatile memory), input / output devices, graphical user interface (GUI), removable data storage, and wired and / or wireless communication interface devices including Wi-Fi, Bluetooth, LAN, etc.

[0038] Computer-executable instructions or programs (e.g., software or code) and the data described herein are programmable into and tangibly embodied in a non-transitory computer-readable medium, which can be accessed and retrieved by a corresponding processor as described herein, and the processor can be configured and directed to perform desired functions and processes by executing instructions encoded in the medium. It should be noted that the non-transitory “computer-readable medium” as described herein may include, but is not limited to, any suitable volatile or non-volatile memory that can be written to and / or read by a processor operatively connected to the medium, including random access memory (RAM) and its various types, read-only memory (ROM) and its various types, USB flash memory, and magnetic or optical data storage devices (e.g., internal / external hard disks, floppy disks, magnetic tape CD-ROMs, DVD-ROMs, optical discs, ZIP drives). TM Drives, Blu-ray discs, and other devices.

[0039] In some embodiments, the invention may be embodied in computer-implemented processes and apparatus (e.g., processor-based data processing and communication systems or computer systems for performing those processes). The invention may also be embodied in software or computer program code in a non-transitory computer-readable storage medium, which, when downloaded and executed by a data processing and communication system or computer system, configures the processor to generate specific logic circuitry configured to implement the processes.

[0040] The invention described herein relates to a device (i.e., a toothbrush), system, and method for detecting gingival bleeding (or any bleeding in the oral cavity, which may include bleeding on soft tissue in the inner cheek or elsewhere) using a sensor that measures the amount of hemoglobin in saliva / toothpaste slurry. In one aspect, the detection of gingival or other soft tissue bleeding occurs during brushing, and therefore the sensor may be described herein as being located on the toothbrush. The sensor may include a light transmitter and a light receiver. The light transmitter may emit visible and infrared light during brushing, and the intensity of the reflected light (i.e., light reflected back from the toothpaste slurry) is received by the light receiver. Since hemoglobin has a strong red color, it absorbs green light while reflecting most of the red and infrared light back. Therefore, the hemoglobin can be quantified using the ratio of the reflected light intensities (red / green and / or infrared / green) and by applying this data to a processing algorithm. The obtained information may be stored on a memory device in the toothbrush or automatically transmitted to a mobile phone (or other portable electronic device) application (software application), or both. In either case, information may be provided to the user (either as a log of all information or as an indication of the presence of blood in the toothpaste slurry) so that the user can be informed of bleeding gums.

[0041] refer to Figure 1 and 2 This illustration shows a toothbrush 100 according to an embodiment of the present invention. In an exemplary embodiment, the toothbrush 100 generally includes a body 110 and a replacement head 120 detachably coupled to the body 110. More specifically, the body 110 includes a handle portion 111 configured for gripping and manipulating by a user and a shaft 112 configured for attaching the replacement head 120 to the body 110. The replacement head 120 includes a sleeve portion 121 and a head portion 122. The sleeve portion 121 is sized and configured to fit over the shaft 112 of the body 110 for coupling the replacement head 120 to the body 110. The replacement head 120 may be coupled to the body 110 by friction / interference fit or by mechanical interaction, for example, the replacement head 120 having a protrusion or recess that matches a recess or protrusion on the body 110. Various techniques are known for attaching the replacement head 120 to the body 110 of the toothbrush 100, and these techniques (i.e., magnetic, mechanical, interference fit, threaded, raised / clamped, etc.) can be used according to the invention described herein. The replacement head 120 and body 110 are shown generally, but the invention is not limited to the shape, size, and / or geometry of these components.

[0042] The replacement head 120 also includes a cleaning element 123 extending from the head portion 122. The cleaning element 123 may be bristles, flexible fingers, a sheet, a rubber element, etc. Specifically, the cleaning element 123 may be any feature or structure known for cleaning teeth, gums, and other oral surfaces. The pattern, material, shape, stiffness, etc., of the cleaning element do not limit the invention.

[0043] In some embodiments, the precise structure, pattern, orientation, and material of the dental cleaning element 123 do not limit the invention. Therefore, the term "dental cleaning element" may be used herein to refer generally to any structure that can be used to clean, polish, or wipe teeth and / or oral soft tissues (e.g., tongue, cheeks, gums, etc.) through relative surface contact. Common examples of "dental cleaning elements" include, but are not limited to, bristle tufts, filament bristles, fiber bristles, nylon bristles, spiral bristles, rubber bristles, elastomeric protrusions, flexible polymer protrusions, combinations thereof, and / or structures comprising such materials or combinations. Suitable elastomeric materials comprise any biocompatible elastomeric material suitable for oral hygiene devices. To provide optimal comfort and cleaning benefits, the elastomeric material of the dental or soft tissue engagement element has a hardness characteristic in the Shore hardness range of A8 to A25. A suitable elastomeric material is styrene-ethylene / butene-styrene block copolymer (SEBS) manufactured by GLS Corporation. However, SEBS materials from other manufacturers or other materials within and outside the stated hardness range may also be used.

[0044] The dental cleaning element 123 of the present invention can be connected to the head portion 122 of the replacement head 120 in any manner known in the art. For example, nails / anchors, in-mold clustering (IMT), anchorless clustering (AFT), PTt anchorless clustering, etc., can be used to mount the cleaning element / dental engagement element to the head portion 122 of the replacement head 120.

[0045] In an exemplary embodiment, the cleaning element 123 defines a cleaning element region 124. Below the cleaning element 123 is an opening or cavity 125 formed in the head 120. When the replacement head 120 is attached to the body 110, the cavity 125 in the head 120 is aligned with the sensor 133 of the electronic circuitry 130. Furthermore, the head portion 120 may include an optically transparent window aligned with the sensor 133 and the cavity 125 to prevent fluids such as saliva, water, and toothpaste slurry from contacting the sensor 133. Aligning the sensor 133 with the cavity 125 in the cleaning element region 124 may be important because, as described in more detail below, in some embodiments, the sensor 133 is configured to emit and receive light. Thus, in an exemplary embodiment, there is a pathway through the cleaning element region 124 that allows light to travel from the sensor 133 to the user's mouth during brushing and then back to the sensor 133. As noted above, in an exemplary embodiment, this is achieved through a combination of the optically transparent window 126 and the cavity 125 in the cleaning element region 124.

[0046] Although in the exemplary embodiment, toothbrush 100 is a toothbrush comprising a body 110 and a replacement head 120 detachably coupled together, in other embodiments, toothbrush 100 may be an integral part comprising a handle and a head fixedly coupled together, as is the case with most conventional manual toothbrushes on the market. Having a detachable replacement head 120 may be desirable because it extends the lifespan of toothbrush 100 by allowing the user to reuse the body 120, which contains expensive circuitry and electronic components, as the replacement head 120 and therefore the bristles 123 wear out. However, it is possible to utilize the techniques and components described herein on more conventional manual toothbrushes that do not include a replaceable replacement head. Therefore, the invention is not limited to requiring toothbrushes to include a replacement head in all embodiments unless specifically required to do so.

[0047] In an exemplary embodiment, the toothbrush 100 includes electronic circuitry 130 for acquiring and / or generating signals related to the detection of the presence of hemoglobin (and therefore blood) in the oral cavity (or toothpaste slurry) during brushing. The toothbrush 100 (and the related system described below) is capable of detecting and measuring hemoglobin / blood using several wavelengths (two to three) in the visible and / or infrared regions during brushing. Therefore, reagents, assays, wet chemical preparations, and / or specialized equipment are not required to detect hemoglobin / blood using the techniques described herein.

[0048] As mentioned above, in the exemplary embodiment, the components of the electronic circuit 130 are located within the body 110 of the toothbrush 100, which is a non-replaceable part of the toothbrush. Therefore, the body 110 of the toothbrush 100 includes a cavity or hollow region where the components of the electronic circuit 130 are located. Because the electronic circuit 130 is located within the body 110 rather than within the replacement head 120, a new replacement head 120 can be attached to the body 110 to extend the lifespan of the toothbrush 100 when the cleaning element 123 on the replacement head 120 wears out. This is one reason why it is desirable to form the toothbrush 100 comprising a body 110 and a removable replacement head 120.

[0049] In an exemplary embodiment, electronic circuitry 130 includes a processor 131, a power supply 132, a sensor 133, a memory device 134 (which may, in some embodiments, be part of processor 131), a Bluetooth module 135, and an indicator 136, all operatively coupled to the processor 131. All components of electronic circuitry 130 are located within a cavity in body 110. Furthermore, in an exemplary embodiment, electronic circuitry 130 also includes a motor 137 operatively coupled to processor 131 to impart movement and / or vibration to replacement head 120 when toothbrush 100 is an electric toothbrush rather than a manual toothbrush. For example, motor 137 may include an eccentric weight to provide vibration during teeth cleaning. In some embodiments, processor 131 may be considered a microcontroller, as all peripherals can be included within the chip itself and it may not run on any operating system.

[0050] Figure 1 and 2 The diagram is schematic because it shows each component of electronic circuit 130 in boxes and uses dashed lines to indicate electrical coupling between components. These boxes are not actually visible on the exterior of the body 110, but rather represent components of electronic circuit 130 as described herein. Specifically, the boxes represent components of electronic circuit 130 housed within the cavity defined by the body 110.

[0051] In an exemplary embodiment, the motor 137 and sensor 133 are located in the lever 112 of the body 110, while the processor 131, power supply 132, memory device 134, Bluetooth module 135, and indicator 136 are located in the handle portion 111 of the body 110. In some embodiments, the processor 131 may be located together with the sensor 133 in the lever 112 instead of in the handle portion 111. The sensor 133 can be connected to the processor 131 using any desired technology, but in some embodiments a standard ADC, I... 2A C or SPI interface. In some embodiments, the Bluetooth module 135 may be coupled to the processor 131 via a standard serial interface. In other embodiments, the Bluetooth module 135 and the processor 131 may be combined into a single unit. Furthermore, as noted above, in some embodiments, the memory device 134 may be part of the processor 131, while in other embodiments, the memory device 134 may be omitted entirely.

[0052] Figure 3 This is a perspective view of a replacement toothbrush 100A (with the replacement head in an attached state) according to an embodiment of the present invention. In this embodiment, the cleaning element region 124 defines an opening or cavity 125A formed by a portion of the head portion 122, which does not have any cleaning elements 123 extending therefrom. Therefore, a portion of the head portion 122 does not contain any cleaning elements 123, and this portion is surrounded by cleaning elements 123 to form a cavity 125A within the cleaning element region 124. Of course, in other embodiments, the spacing between the cleaning elements 123 in the cleaning element region 124 may differ from the spacing shown, such that there is no cavity itself, but gaps are still maintained in the cleaning element region 124.

[0053] refer to Figure 4 The sensor 133 will be described in more detail below according to embodiments of the invention. Preferably, the sensor 133 is small enough to be fitted within the handle 112 and / or head portion 122 of the toothbrush 100 as depicted. In an exemplary embodiment, the sensor 133 includes a transmitter 140 and a receiver 141. Furthermore, in an exemplary embodiment, the transmitter 140 includes a first light source 142, a second light source 143, and a third light source 144. Although three light sources are depicted in the exemplary embodiment, the invention is not so limited in all embodiments. Specifically, in some alternative embodiments, the transmitter 140 may include only the first light source 142 and the second light source 143, without the third light source 144. One example of the sensor 133 is the MAX30105 from Maxim Integrated, but the invention is not limited to this in all embodiments, and other sensors may be used. In some embodiments, the transmitter 140 may be a broadband white light emitter. In such embodiments, the receiver 141 may have multiple channels to detect reflected light of different wavelengths respectively.

[0054] In an exemplary embodiment, sensor 133 is a single structure comprising all the features / components marked herein. However, the invention is not limited thereto, and in some other embodiments, the sensor may comprise multiple sensors that are independent of and distinct from each other. For example, the sensor may comprise discrete light sources separate from and remote from the receiver. Thus, as used herein, the term sensor includes both the use of a single sensor having all the necessary components and the use of multiple sensors having all the necessary components in a combined manner.

[0055] A first light source 142 is configured to emit light of a first wavelength, a second light source 143 is configured to emit light of a second wavelength different from the first wavelength, and a third light source is configured to emit light of a third wavelength different from the first and second wavelengths. For example, in one embodiment, the first light source 142 is configured to emit red light with a wavelength range of 625 to 740 nm, more specifically 640 to 680 nm. Furthermore, in one embodiment, the second light source 143 is configured to emit green light with a wavelength range of 520 to 560 nm, more specifically 520 to 540 nm. Furthermore, in one embodiment, the third light source 144 is configured to emit infrared light with a wavelength range of 700 nm to 1 micrometer, more specifically 830 to 930 nm, and more specifically 860 to 900 nm. In an exemplary embodiment, each of the first light source 142, the second light source 143, and the third light source 144 is a light-emitting diode (LED), but other types of light sources may be used in alternative embodiments. Therefore, the transmitter 140 of the sensor 131 includes multiple light sources, such that each light source emits light of a different wavelength. Receiver 141 may be a broad-spectrum photodetector, enabling it to detect reflected light in all wavelengths mentioned herein (i.e., it can detect at least red, green and infrared light).

[0056] In an exemplary embodiment, sensor 133 is operatively coupled to processor 131 such that measurements or other information detected by sensor 133 can be sent as signals to processor 131 for processing. Furthermore, processor 131 is pre-programmed with algorithms, or works associated with software applications containing algorithms, such that processor 131 can use the information acquired by sensor 133 to perform various calculations to determine whether sensor 133 has detected hemoglobin and therefore blood. Specifically, processor 131 can perform calculations and then use the pre-programmed algorithms to determine whether the result of these calculations indicates the presence or absence of hemoglobin / blood, and if present, the quantity.

[0057] Specifically, reference Figure 5A and 5B The operation of sensor 133 will be described. Figure 5ASensor 133 is schematically depicted, located inside the oral cavity such that light emitted by sensor 133 can contact and be reflected by toothpaste slurry 150 in the oral cavity, which contains no blood. Figure 5B Sensor 133 is schematically depicted within the oral cavity such that light emitted by sensor 133 can contact and be reflected by toothpaste paste 151 containing blood in the oral cavity. The toothpaste paste is a liquid formulation containing toothpaste and saliva. Furthermore, if blood is present in the mouth, this blood will mix with the liquid formulation and also form part of the toothpaste paste. Therefore, sensor 133 is configured to detect the presence of blood in the toothpaste paste, which in turn indicates bleeding within the oral cavity (i.e., gingival bleeding, etc.).

[0058] First refer to Figure 5A Sensor 133 is located inside the oral cavity, which contains toothpaste slurry 150 free of any blood. Therefore, toothpaste slurry 150 contains toothpaste and saliva, but no blood. In this embodiment, a first light source 142 emits a first light 145 (e.g., red light) at a first wavelength into the oral cavity and toward the toothpaste slurry 150, a second light source 143 emits a second light 146 (e.g., green light) at a second wavelength into the oral cavity and toward the toothpaste slurry 150, and a third light source 144 emits a third light 147 (e.g., infrared light) at a third wavelength into the oral cavity and toward the toothpaste slurry 150. In complex matrices, such as saliva / toothpaste slurry, abrasive particles and bubbles in the toothpaste slurry reflect light of different wavelengths with similar efficiency. Therefore, as... Figure 5A As shown, the first light 145, the second light 146, and the third light 147 are all reflected from the toothpaste liquid 150, becoming the reflective portion of the first light 145, the reflective portion of the second light 146, and the reflective portion of the third light 147.

[0059] refer to Figure 5B In this embodiment, sensor 133 is located inside the oral cavity, which contains toothpaste slurry 151 containing blood. Therefore, toothpaste slurry 151 contains toothpaste, saliva, and blood resulting from bleeding from the gums or other oral tissue surfaces within the oral cavity. In this embodiment, a first light source 142 emits a first light 145 (e.g., red light) at a first wavelength into the oral cavity and toward the toothpaste slurry 151, a second light source 143 emits a second light 146 (e.g., green light) at a second wavelength into the oral cavity and toward the toothpaste slurry 151, and a third light source 144 emits a third light 147 (e.g., infrared light) at a third wavelength into the oral cavity and toward the toothpaste slurry 151. Due to the strong red color of hemoglobin in red blood cells, hemoglobin strongly absorbs green light while reflecting most of the red and infrared light back.

[0060] Therefore, as Figure 5BAs shown, the first light 145 and the third light 147 are reflected from the toothpaste slurry 151 as reflected portions of the first light 145 and the third light 147, respectively. However, the second light 146 (green light in the exemplary embodiment) is absorbed by the toothpaste slurry 151. Figure 5B In this diagram, it is shown as a receiver 142 such that no second light 146 is reflected back to the sensor 133. However, in actual operation, some of the second light 146 will be reflected back, but this is less than the amount reflected from the sensor 133. Figure 5A The amount of second light 146 reflected back from the bloodless toothpaste slurry 150 has a reduced intensity because hemoglobin absorbs some of the second light 146. Therefore, the intensity of the second light 146 reflected from the bloodless toothpaste slurry 150 is greater than that reflected from the blood-containing toothpaste slurry 151, because the hemoglobin in the blood absorbs some of the second light 146.

[0061] Therefore, during brushing using the cleaning element 123 of the toothbrush 100, the sensor 133 sends a first light 145, a second light 146, and a third light 147 into the oral cavity. The first light 145, the second light 146, and the third light 147 contact the toothpaste slurry 150 and 151 in the oral cavity, and the reflected portions of the first light 145, the second light 146, and the third light 147 are received by the receiver 141 of the sensor 133. Regardless of whether the toothpaste slurry contains blood, the intensity of the reflected portions (red and infrared light) of the first light 145 and the third light 147 remains relatively constant. However, the intensity of the reflected portion (green light) of the second light 146 is greater when the toothpaste slurry does not contain blood than when it does. Therefore, the sensor 133 generates a first signal indicating the first intensity of the reflected portion of the first light 145, a second signal indicating the second intensity of the reflected portion of the second light 146, and a third signal indicating the third intensity of the reflected portion of the third light 147.

[0062] Because the intensity of the reflected portion of the second light 146 decreases when blood is present in the toothpaste slurry, while the intensity of the reflected portions of the first light 145 and the third light 147 remains substantially the same regardless of the presence of blood in the toothpaste slurry, the ratio of reflected light intensities can be used to identify and quantify hemoglobin / blood. Therefore, the processor 131 may have an algorithm capable of calculating said ratio and determining the presence (and amount) of hemoglobin and blood.

[0063] Due to its operative coupling, the first, second, and third signals (but the third signal can be omitted, as the system can also operate with sensor 133 emitting only red or infrared and green light) are transmitted from sensor 133 to processor 131. Processor 131 is equipped with an algorithm that instructs it to perform calculations using the first, second, and third signals to help determine whether hemoglobin / blood is present in the toothpaste slurry. Specifically, processor 131 is configured to calculate the ratio of a first intensity of first light 145 to a second intensity of second light 146 and / or the ratio of a third intensity of third light 147 to a second intensity of second light 146. It should be understood that if hemoglobin / blood is present in the toothpaste slurry, the intensity of the reflected portion of the second light 146 is less than the intensity when hemoglobin is not present in the toothpaste slurry. Therefore, compared to the case where there is no hemoglobin / blood in the toothpaste slurry, if hemoglobin / blood is present in the toothpaste slurry, the ratio of the first intensity of the first light 145 to the second intensity of the second light 146, and the ratio of the third intensity of the third light 147 to the second intensity of the second light 146, increase (due to a decrease in the denominator in the ratio calculation). Using this understanding and the developed algorithm, the processor 131 can determine whether hemoglobin / blood is present in the toothpaste slurry, and if so, how much.

[0064] For example, the processor 131 or algorithm may be configured with predetermined thresholds for various ratios, said predetermined thresholds being calculated such that the processor 131 knows that hemoglobin / blood has been detected once the ratio exceeds the predetermined threshold. Therefore, the processor 131 may be programmed such that hemoglobin / blood is present if the ratio of a first intensity of a first light 145 to a second intensity of a second light 146 exceeds a first predetermined threshold and / or the ratio of a third intensity of a third light 147 to a second intensity of a second light 146 exceeds a second predetermined threshold.

[0065] These predetermined thresholds can be determined based on testing using baseline samples of toothpaste slurry that do not contain hemoglobin / blood and test samples using toothpaste slurry containing varying amounts of toothpaste slurry, as referenced below. Figure 6 Further discussion. Therefore, a predetermined threshold can be determined by testing toothpaste slurry without any hemoglobin using a toothbrush 100, such that if the ratio increases relative to the test data, it can be determined that blood is present in the toothpaste slurry.

[0066] Specifically, Figure 6This is a scatter plot showing the results of an experiment involving the in vitro detection of hemoglobin in blood using a prototype device with the same technology present in the toothbrush 100 described herein. In the experiment, lyophilized human hemoglobin (Sigma) was reconstituted in deionized water to a concentration of 4.2% and combined with a slurry of 1 part:3 parts w / w Colgate toothpaste (regular flavor) and deionized water to form a solution of hemoglobin at the following final w / w concentrations:

[0067] 0.285714 0.259259 0.230769 0.2 0.166667 0.130435 0.090909 0.047619

[0068] It should be understood that solutions with higher concentrations of hemoglobin will have a deeper red color and will therefore absorb more green light emitted therefrom. A single 50-microliter droplet of each solution was measured using the prototype apparatus described above. Figure 6 This is a scatter plot showing the linear relationship (expressed as the ratio IR / G) between the measured values ​​of reflected infrared and green light and the hemoglobin concentration. As can be seen, the IR / G ratio increases with increasing wt.% of hemoglobin (and the same applies if infrared light is replaced with red light). This is because with more hemoglobin in the solution, more green light is absorbed, and the intensity of the reflected green light decreases. Therefore, using this information, algorithms can be created to determine the presence of hemoglobin in toothpaste slurry, and the amount of hemoglobin (and therefore blood) in the toothpaste slurry. In this example, if the IR / G ratio is greater than approximately 4.5, blood is likely present in the tested solution (i.e., the toothpaste slurry). Therefore, in one embodiment, a predetermined threshold of 4.5 may be used when the light source emits infrared and green light respectively.

[0069] Refer again Figure 1 and 2As noted above, electronic circuitry 130 also includes an indicator 136. In an exemplary embodiment, indicator 136 is located on the body 110 of toothbrush 100. Indicator 136 is operatively coupled to processor 131 such that processor 131 can activate indicator 136 after determining that blood is present in the mouth or toothpaste slurry. In one embodiment, indicator 136 may be a light, such as a light-emitting diode (LED). In such embodiments, after processor 131 determines the presence of hemoglobin / blood in the mouth (based on one of the ratios mentioned above being calculated to be above its corresponding predetermined threshold or using some other determination method as stated in the algorithm), processor 131 will activate indicator 136 to illuminate / glow, thereby indicating to the user that blood is present in the mouth (i.e., the user's gums, etc., are bleeding). Of course, in all embodiments, indicator 136 is not limited to a light source, and in other embodiments, the indicator may be an audio source that emits a sound audible to the user when activated. In other embodiments, the indicator 136 may take other forms, such as a mechanical feature that a user can feel by touch, an aromatic feature that emits a fragrance when activated, a display screen that displays various texts, etc.

[0070] In some embodiments, indicator 136 may illuminate in different colors depending on the state of toothbrush 100 or sensor 133. For example, indicator 136 may light up blue when sensor 133 is operatively coupled to a portable electronic device described in more detail below; indicator 136 may light up red when toothbrush 100 or its power source is charging; and indicator 136 may light up green when toothbrush 100 is used during brushing. In other embodiments, as described herein, indicator 136 may light up red (or orange or any other color) when the presence of toothpaste slurry / blood in the mouth is detected.

[0071] In some embodiments, a button or other type of actuator (slide switch, button, capacitive sensor, etc.) may be present on the toothbrush 100 to activate the sensor 133. Thus, before a brushing session, the user can press (or otherwise actuate) the button to activate the sensor 133. Pressing the button (or otherwise actuating the actuator) may also activate the motor 137, for example, when the toothbrush 100 is an electric toothbrush and includes a motor 137. Alternatively, separate buttons / actuators may be present for the motor 137 and for the sensor 133. In some embodiments, no motor is present, and the toothbrush 100 is a manual toothbrush.

[0072] refer to Figure 7This provides a graphical representation of the results of experimental tests performed using a prototype device including sensor 133 and processor 131. To demonstrate the capabilities of toothbrush 100, two samples were measured. Approximately 2 grams of toothpaste were mixed with approximately 5 mL of saliva to produce a toothpaste / saliva slurry, which was the “baseline sample.” The same procedure was repeated, and one drop of human blood was added to the slurry, which was then thoroughly mixed to produce a “test sample”—a toothpaste / saliva slurry containing blood. A drop of the baseline sample was deposited on a glass slide, and sensor 133 was placed under the slide to measure the reflected light. At least 100 data points for each of the three wavelengths of light were recorded, and the average was used in later processing. The procedure was repeated three times to obtain baseline data for the toothpaste / saliva slurry. The same procedure was also repeated three times for the test sample.

[0073] Figure 7 The results of the signals measured by the prototype device are shown. The x-axis represents the signal intensity ratio of red to green light, while the y-axis represents the signal intensity ratio of infrared to green light. A clear separation between the "baseline sample" and the "test sample" is observed. Different data processing algorithms can be used to identify and quantify hemoglobin in toothpaste slurry, such as KNN (k-nearest neighbor algorithm) for identification and regression for quantification.

[0074] Using this example, if the ratio of the intensity of the reflected portion of the first (i.e., red) light to the intensity of the reflected portion of the second (i.e., green) light is greater than 5.6, then it can be determined that hemoglobin / blood is present in the oral cavity (or in the toothpaste slurry and therefore also in the oral cavity). Similarly, if the ratio of the intensity of the reflected portion of the third (i.e., infrared) light to the intensity of the reflected portion of the second (i.e., green) light is greater than 4.8, then it can be determined that hemoglobin / blood is present in the oral cavity (or in the toothpaste slurry and therefore also in the oral cavity).

[0075] In some embodiments, sensor 133 is configured to continuously collect data upon activation. For example, once powered on, sensor 133 may collect data over a predetermined time period, such as 120, 130, 140, or 150 seconds, to ensure that it collects data for the duration of the brushing session (ideally 120 seconds, but more commonly shorter time periods). In some embodiments, sensor 133 may collect two data points per second, allowing it to collect 240 data points during a two-minute brushing session. In other embodiments, sensor 133 may collect data intermittently. For example, sensor 133 may collect data for ten seconds, then thirty seconds, then one minute, then one minute and fifteen seconds, then one minute and thirty seconds, then one minute and forty-five seconds, then two minutes. In all embodiments, the precise frequency at which sensor 133 collects data regarding the presence of hemoglobin does not limit the invention.

[0076] refer to Figure 8 and9 This illustrates a system 1000 for detecting blood in the oral cavity during brushing. The system 1000 includes a toothbrush 200 and a portable electronic device 300 that are operatively in communication with each other. The toothbrush 200 is structurally similar to that described above. Figures 1 to 3 The toothbrush 100 described is identical. Therefore, in an exemplary embodiment, the toothbrush 200 includes a body 210 having a handle portion 211 and a shaft (not shown), and a replacement head 220 detachably attached to the body 210. Further details regarding the structure of the toothbrush 200 can be found in the toothbrush 100 described above.

[0077] Similar to toothbrush 100, toothbrush 200 includes electronic circuitry 230, which may include a processor 231, a power supply 232, a sensor 233, a memory device 234 (or, in some embodiments, may be part of processor 231), a Bluetooth module 235, and an indicator 236. However, in some embodiments, the processor 231, memory device 234, and indicator 236 may be omitted. Therefore, in some embodiments, the electronic circuitry 230 of toothbrush 200 may only include sensor 233 (which includes transmitter 240 and receiver 241), power supply 232, and Bluetooth module 235. If toothbrush 200 is an electric toothbrush, it may also include a motor 237.

[0078] The toothbrush 200 does not need to include a processor 231, a memory device 234, and an indicator 236 (although the toothbrush may include one or more of these components in some embodiments) because these components are included as part of a portable electronic device 300 that communicates with the toothbrush 200. Specifically, the portable electronic device 300 may be a smartphone, tablet, computer, or similar device that includes a processor 301, a memory 302, a user interface 303, a blood testing software application 304, and a Bluetooth module 305. The portable electronic device 300 may also include a display 306 (which may be the same as or different from the user interface 303). In an exemplary embodiment, because the Bluetooth module 235 is incorporated into both the toothbrush 200 and the portable electronic device 300 (when the toothbrush 200 and the portable electronic device 300 are close enough to allow such Bluetooth connectivity), the processor 301 of the portable electronic device 300 operatively communicates with the sensor 233 of the toothbrush 200 via Bluetooth. Of course, Bluetooth is just one exemplary way for the toothbrush 200 and the portable electronic device 300 to communicate. In other embodiments, a wired connection may exist between the toothbrush 200 and the portable electronic device 300, or they may communicate using other wireless protocols (infrared wireless communication, satellite communication, radio, microwave, Zigbee, Z-wave, etc.). In some embodiments, the sensor 233 may have a built-in microcontroller.

[0079] In this embodiment, sensor 233 will operate in the same manner as sensor 133 described above. Therefore, the transmitter 240 of sensor 233 includes multiple light sources emitting light of different wavelengths, and the receiver 241 of sensor 233 receives the reflected light. Sensor 233 then generates signals indicating the intensity of the various reflected light. However, in this embodiment, the signals are then transmitted from sensor 233 of toothbrush 200 to processor 301 of portable electronics 300 via Bluetooth or otherwise. This transmission of signals from sensor 233 of toothbrush 200 to processor 301 of portable electronics 300 can occur as long as toothbrush 200 and portable electronics 300 are operatively communicating (via Bluetooth or other wireless technologies or via a wired connection).

[0080] In some embodiments, information associated with signals and information detected by sensor 133 may be initially stored in the memory 234 and / or processor 231 of toothbrush 200, and then transmitted in batches to the processor 301 of portable electronics 300. Thus, data or information corresponding to multiple different brushing sessions may be initially stored in the memory 234 and / or processor of toothbrush 231. This can be applied when a user brushes their teeth while toothbrush 200 and portable electronics 300 are not in operative communication. In this way, toothbrush 200 initially stores all data, and then once toothbrush 200 is operatively coupled to portable electronics 300, the data may be sent to portable electronics 300 for further processing as described herein (automatically or in response to manual user input). In such embodiments, processor 231 is capable of processing data like processor 131 of toothbrush 100, such that processor 231 can activate indicator 236 when it determines the presence of hemoglobin / blood in the oral cavity or toothpaste slurry.

[0081] As noted above, the portable electronic device 300 may have a blood testing software application 304 downloaded thereon. Therefore, during or just before brushing, the user can open the blood testing software application 304 and put the toothbrush 200 into operative (wireless or wired) communication with the portable electronic device 300. Alternatively, operative coupling between the toothbrush 200 and the portable electronic device 300 allows the blood testing software application 304 to be automatically launched on the portable electronic device 300. In such cases, when the sensor 233 of the toothbrush 200 collects information / data related to the intensity of reflected light, the sensor sends this data / information to the processor 301 of the portable electronic device 300. In some embodiments, this transmission of data / information from the sensor 233 to the processor 301 can occur automatically as long as the toothbrush 200 and the portable electronic device 300 are operatively in communication with each other. Of course, as noted above, this data / information may alternatively (or additionally) be stored locally on the memory device 234 of the toothbrush 200 and then sent in batches to the portable electronic device 300. The processor 301 of the portable electronic device 300 may use the blood detection software application 304 to provide this data / information to the user on the portable electronic device 300 in various ways.

[0082] Specifically, first refer to Figure 10A and 10BAn embodiment of the blood detection software application 304 is shown displayed on the display 306 of a portable electronic device 300. In this suitably simple embodiment of the blood detection software application 304, the application only notifies the user whether blood has been detected in the mouth (or toothpaste slurry) during brushing. Therefore, when the processor 301 receives a signal from the sensor 233 and processes the signal according to the algorithm described herein, the processor 301 causes the blood detection software application 304 to indicate the presence of blood. Figure 10A Since there is no blood in the sample, the display 306 on the portable electronic device 300 is blank. Figure 10B Since blood is present in the toothpaste, the display 306 on the portable electronic device 300 is depicted with a shaded area 307. This shaded area 307 can be red as an indication of the presence of blood, but other colors, designs, etc., can be used, including displayed text to indicate the presence of blood. Therefore, in this embodiment, the shaded area 307 on the display 306 of the portable electronic device 300 acts as a user indicator to let the user know whether blood is present. In other words, the shaded area 307 is the output of the system 1000, which is used to indicate to the user whether blood is present in the toothpaste slurry. The processor 301 can also track this information over multiple uses in the blood detection software application 304, allowing the user to view a daily data log indicating whether blood was present during brushing during multiple brushing sessions occurring within a given day.

[0083] In some embodiments, if blood is detected at any time during the brushing session, the display 306 on the portable electronic device 300 will indicate this throughout the brushing session. In some embodiments, the display 306 on the portable electronic device 300 will update during the brushing session based on whether blood is detected at a given time during the brushing session. In some embodiments, the output on the display 306 may be an indication of blood detection, and / or an indication of the amount of blood detected, and / or an indication of whether blood is detected, and if detected, an indication of the time when blood was detected during the brushing session (e.g., the display 306 may indicate that blood was first detected 18 seconds into the brushing session).

[0084] For example, refer to Figure 11According to one embodiment, a display 306 of a portable electronic device 300 is depicted, wherein a blood detection software application 304 is opened to display data logs from previous brushing sessions. Thus, a user can open the blood detection software application 304 and navigate to the blood detection application log. In an exemplary embodiment, the log includes the date, a short yes or no answer regarding whether blood was detected on that particular date, and the blood concentration detected as a daily weight percentage. Various modifications can be made to the blood detection software application 304 to provide the user with any desired information or data regarding blood detected or not detected during various brushing sessions. In some embodiments, the blood detection software application 304 may be programmed with an algorithm that analyzes the sensor data logs and provides a warning signal to the user if continuous bleeding is detected, for example, bleeding for seven consecutive days. Therefore, Figure 11 The depiction in the text is merely illustrative and is not intended to illustrate the full range of possibilities available through the blood detection software application 304. Information provided in this format may include the highest amount of blood detected by sensors 133, 233 during a brushing session, the average amount of blood detected by sensors 133, 233 during a brushing session, etc.

[0085] Therefore, utilizing Figure 11 The data provided can inform users how many times they have experienced bleeding during brushing within the past week, two weeks, three weeks, one month, and so on (in some embodiments, this time range can be adjustable). Typically, when a person bleeds while brushing, they notice it when spitting out toothpaste or taste it during brushing, but they forget about the bleeding shortly after finishing. Therefore, even if a person bleeds every day, they don't think much of it. By providing users with a log of information from past brushing sessions, this allows them to better understand the frequency of bleeding during brushing, enabling them to seek treatment if necessary. Figure 11 The data provided may be displayed to the user in tabular form, such as a bar chart, line graph, etc., on the display of the portable electronic device 300 or elsewhere (i.e., on a computer or anywhere the data can be displayed).

[0086] In some embodiments, sensor data may be uploaded to a remote cloud server for further analysis. Toothbrushes 100 and 200 may include a WiFi chip, enabling them to send data to the cloud or a remote server, or they may send data to a portable electronic device 300, which in turn can send the data to the cloud / server. Users can use their computers (with larger screens) to access their long-term data logs to view trends (on software applications or programs, websites, etc.) and choose to share this data with their oral care service providers for better care. Oral care service providers can review this data to monitor their patients between their scheduled visits. Researchers can use this data for oral health research or efficacy evaluations of existing or experimental oral care products or programs, as well as for epidemiological studies in oral care. Insurance companies can reduce costs by requesting early or preventative treatment for high-risk individuals.

[0087] In some embodiments, the system 1000 or toothbrush 100 is able to detect how much blood (i.e., the amount) a user loses during a single brushing session. However, this information may not be as useful as it seems, as it can depend on when the user brushes particularly bleeding areas of the mouth during the brushing session. Therefore, if a user is prone to bleeding at the gum line above the first molar in the upper left quadrant of the mouth, then if the user brushes the upper left quadrant first during the brushing session, there will be more blood during the brushing session compared to if the user brushes the upper left quadrant last during the brushing session. That said, obtaining a value for the amount of blood lost during a brushing session can still be of some value to the user or a healthcare professional.

[0088] Refer again Figure 1 In some embodiments, toothbrush 100 (or toothbrush 200) may be configured to track its position in the mouth in addition to tracking blood / hemoglobin in the oral cavity or toothpaste slurry during brushing. Therefore, toothbrush 100 may include one or more position tracking sensors (or position sensors) 139 configured to track the position of toothbrush 100, 200 in the oral cavity. In an exemplary embodiment, the tracking sensor 139 is located within the handle 112 of the body 110, but the tracking sensor can be located in any position as long as it is configured to operate as described herein. The tracking sensor 139 is operatively coupled to processor 131 such that processor 131 can receive signals detected / generated by the tracking sensor 139 and process these signals to determine the position of the head 120 of toothbrush 100 in the mouth at a given time during brushing. For example, in some embodiments, position sensor 139 may be located in the handle portion 111 of the body 110.

[0089] An example of such a toothbrush configured to track position in the oral cavity is described in U.S. Patent No. 10,349,733, published July 16, 2019, the entire contents of which are incorporated herein by reference. Therefore, the one or more position tracking sensors may be accelerometers, motion sensors, inertial sensors, gyroscopes, magnetometers, and other sensors capable of detecting position, movement, and acceleration. The position tracking sensors may send signals to processors 131, 231, such that processors 131, 231 may be configured to determine where the head of the toothbrush is located in the oral cavity at a given time during a brushing session. Tracking sensor 139 may be a single sensor or may be multiple sensors, and it may include different types of sensors (accelerometers, gyroscopes, proximity sensors, etc.).

[0090] Therefore, by combining this position tracking with blood tracking, processors 131 and 231 can log the position of the toothbrush in the mouth when blood is first detected. Because sensors 133 and 233 can measure / collect data per second in some embodiments, sensors 133 and 233 will detect blood almost instantaneously. Therefore, if the head of toothbrush 100 or 200 is located in the upper right quadrant of the mouth and bleeding begins in that area of ​​the gums, system 1000 will be able to track this information and provide it to the user (e.g., via blood detection software application 304, etc.). Specifically, system 1000 will know where toothbrush 100 or 200 was located when blood was first detected, which is a good indication of where the blood came from in the oral cavity area where toothbrush 100 or 200 was located at that time. System 1000 can track the location of bleeding based on which of the four quadrants of the oral cavity (upper left, upper right, lower left, lower right) is bleeding, or the system can provide more specific information, such as bleeding gums above the first molars in the upper left quadrant of the mouth. Furthermore, the system does not need to be based on four quadrants; instead, it can simply track whether blood is coming from the top or bottom of the mouth. In other embodiments, the mouth can be divided into more than four quadrants to provide a more precise indication of where the blood is coming from. In this way, system 1000 (or toothbrush 100) will be able to track which part of the mouth is bleeding and provide this information to the user or a medical professional. This can be useful information provided by the user to a medical professional or kept solely by the user, allowing the user to treat that area of ​​the mouth as needed.

[0091] Therefore, system 1000 (or toothbrush 100, 200) can determine that blood is first detected 45 seconds into the brushing session. System 1000 can then determine where toothbrush 100, 200 (or its head or cleaning element) is in the mouth / oral cavity at 45 seconds into the brushing session. In this way, system 1000 can determine the position of toothbrush 100, 200 in the oral cavity when blood is first detected, which is likely the location of bleeding. This information can be provided to the user on a graphic display. For example, display 306 on portable electronic device 300 can show a visual representation of a set of teeth or oral cavity, and the display can indicate which area of ​​the oral cavity was first detected with blood (e.g., by highlighting the area or coloring it red, etc.).

[0092] Following the same logic, system 1000 (or toothbrush 100, 200 itself) can also determine when a second bleeding site exists in the oral cavity. For example, system 1000 can record the amount / content of blood in the oral cavity during the brushing period. If the amount of blood detected at any time increases significantly, system 1000 can determine that a second bleeding site exists in the oral cavity. Therefore, for example, if 0.1 ml of blood is detected at ten seconds into the brushing period, and then 0.3 ml of blood is detected at forty-five seconds into the brushing period, system 1000 can interpret this as indicating the presence of a second bleeding site. Therefore, system 1000 can determine the position of the toothbrush head at the moment when the amount of blood increases to determine the second bleeding site in the oral cavity.

[0093] The operation of system 1000 will now be briefly described based on a method for detecting blood in toothpaste slurry during brushing. The method involves having a user brush their teeth and gums using the cleaning element 123 of a toothbrush 100 during a brushing session. During such brushing, if toothpaste has been pre-applied to the cleaning element 123, a toothpaste slurry will form in the oral cavity during the brushing session. Next, a signal containing information related to the presence of hemoglobin in the toothpaste slurry is generated. According to an exemplary embodiment, these signals are generated by a sensor 133 coupled to the toothbrush 100. More specifically, the sensor 133 sends a first wavelength of light and a second wavelength of light into the oral cavity where the toothpaste slurry is located. A portion of the first and second light is then reflected from the toothpaste slurry. The receiver 141 of the sensor 133 receives the reflected portions of the first and second light.

[0094] Next, processors 131 and 301 receive signals corresponding to the intensities of the reflected portions of the first and second light. Processors 131 and 301 process these signals to determine the presence of hemoglobin (and therefore blood) in the toothpaste slurry. This is achieved by the processor calculating the ratio of a first intensity of the reflected portion of the first light to a second intensity of the reflected portion of the second light. Using the result of this calculation, processors 131 and 301 can determine the presence of hemoglobin / blood in the toothpaste slurry. In some cases, when processors 131 and 301 determine the presence of hemoglobin in the toothpaste slurry, the method may include providing an indication to the user that blood is present in the toothpaste slurry. This may involve displaying such an indication on a display 306 of the portable electronic device 300 or activating an indicator 136 located on the toothbrush 100.

[0095] The above-described system and method are "reagent-free" systems and methods for measuring hemoglobin using only a few wavelengths (two to three) of light in the visible and infrared regions during brushing. Since the surfactant sodium lauryl sulfate ("SLS") in most toothpaste compositions acts as a stabilizer for hemoglobin, the method does not require additional reagents specifically for hemoglobin detection.

[0096] It should be noted that although the description provided herein relates to using toothbrushes 100, 200, and / or system 1000 to detect hemoglobin in order to determine the presence of blood in the oral cavity and / or toothpaste slurry, the invention is not limited to this in all embodiments. For example, in some embodiments, toothbrushes 100, 200, and / or system 1000 can be used to detect serum albumin, which is also abundant in blood. However, serum albumin does not have strong spectral characteristics. Therefore, when toothbrushes 100, 200, and / or system 1000 are used to detect serum albumin, a dye such as bromocresol green may be added first. As described herein, serum albumin bound to the dye will absorb red light, so sensors 133, 233 described herein can be used to detect this serum albumin / dye in the same manner as described above to determine the presence of blood, but the algorithm must be modified so that red light is the denominator in the equation.

[0097] Detect the peak of the reflectance ratio

[0098] The aforementioned hardware components and collected reflectance data can be used to detect hemoglobin through alternative methods. Three models are discussed below. An exemplary model uses a time series of the signal, i.e., a single peak in the reflectance spectrum throughout the entire brushing cycle, rather than the total average reflectance of the brushing slurry. This method more effectively overcomes background effects from colored foods, beverages, or toothpaste. In these cases, the net baseline reflectance will be higher, but the bleeding point will still appear as a peak. Detecting an increase in the average reflectance of the brushing slurry cannot be used to detect the location of bleeding points and can only detect higher concentrations of hemoglobin, which can generate a detectable increase in average signal even after dilution by the brushing slurry. Furthermore, the method disclosed herein is reagent-free and has minimal disruption to user habits. This will help raise user awareness of gingival bleeding at the right time, which will help them better care for their gums.

[0099] In one embodiment (sometimes referred to as "Model 1"), the reflectance ratios of red to green (R / G) and infrared to green (IR / G) are plotted against time, as shown in the figures below. Figure 12A To B and Figure 13A As shown in B. Figure 12A Figures B through B are graphs of the R / G ratio and IR / G ratio over time in typical bleeding patients, while... Figure 13A Figures B to B are plots of the R / G and IR / G ratios for typical non-bleeding subjects, respectively. It was observed that for bleeding subjects, these curves (R / G and IR / G versus time) had a significantly higher number of peaks149 compared to non-bleeding subjects. These peaks149 are attributed to the increased reflectance ratios R / G and IR / G when the sensor detects hemoglobin (blood) in bleeding subjects. For non-bleeding subjects, these ratios remain consistently near the baseline due to the absence of any blood, and therefore typically have no peaks. Using the model discussed in this paper, it was possible to confidently group bleeding and non-bleeding subjects separately with AUROC values ​​ranging from 0.75 to 0.8. AUROC is the area under the receiver operating characteristic curve, a standard method used in data science to determine model robustness.

[0100] The method of tracking peaks also allows the system to detect the location of individual bleeding points by equipping the toothbrush with a position sensor to identify the location of the bleeding point. For example, the toothbrush may include the aforementioned tracking sensor configured to generate a position signal associated with the position of the toothbrush head to determine the position of the toothbrush head. In one embodiment, for each peak, the system can determine the corresponding position of the head at that time, thereby identifying the specific bleeding point.

[0101] For the data collection described below, five subjects with bleeding and six subjects without bleeding were used. They fasted overnight and brushed their teeth in the morning using a toothbrush with an optical sensor (e.g., the toothbrush 100, 100A, or 200 discussed above) and Colgate toothpaste. An LED in the toothbrush was turned on during brushing, and the sensor in the toothbrush collected reflection data of the toothpaste slurry and transmitted it directly to a smartphone. During a brushing cycle of approximately two minutes, reflection data was collected per second at wavelengths of 527 nm (green), 660 nm (red), and 880 nm (infrared) (approximately 120 to 130 data points in total). It should be understood that other wavelengths can be used. It should also be understood that the frequency of reflection data collection can be varied, making data collection more frequent or less frequent. For example, collecting reflection data more frequently will generate more data points. Furthermore, reflection data can be collected at different times. For example, instead of collecting reflection data at a consistent frequency (e.g., every 1 second) throughout the entire brushing session, data can be collected only at the beginning or end of the brushing session, or at some other time during the brushing session. Furthermore, the frequency of data collection can vary during the brushing session. Additionally, the data can be stored in the toothbrush and collected later, or stored in the toothbrush and simultaneously transmitted to a smartphone. In this current example, data collection is repeated for all objects for five consecutive days and used for further analysis and modeling.

[0102] Back Figure 12A From B and 13A to B, the number of peaks 149 can be calculated. There are multiple methods to identify such peaks. In an exemplary embodiment, the "find_peaks" function in the Python programming language is used to find local maxima, where a predetermined threshold ratio is set to 8, and the minimum distance between two peaks (a predetermined time value) is set to 5 seconds. However, the invention is not limited to this. A peak can be understood as any one or more data points representing a brief and noticeable increase in the ratio over time before the ratio returns to the baseline range of the value. When a peak is considered part of a waveform, it will form the shape of a peak or spike, as in... Figure 12APeak 149 is shown in B. In one embodiment, a peak can be understood as a local maximum of the ratio over time, such that the signal at the peak is significantly greater than the noise value relative to the baseline (e.g., the peak is 2 times or more the noise value relative to the baseline). However, the invention is not limited thereto. As described above, in the described embodiments, other criteria can be used, such as setting a minimum threshold (e.g., 8) for the peak signal and a minimum time interval (e.g., 5 seconds) between two peaks. In other embodiments, the minimum threshold and / or minimum time interval can be ignored. In other embodiments, the presence of a peak can be based entirely on the minimum threshold and / or minimum time interval. In other embodiments, any other standard method can be used to calculate the number of peaks. See, for example, Yang, Comparison of Public Peak Detection Algorithms for MALDI Mass Spectrometry Data Analysis, BMC Bioinformatics (published online 2009), which is incorporated herein by reference in its entirety. Peaks can be identified using any programming language (such as C, C++, or Java) or computer mathematics software (such as Origin or Matlab).

[0103] Furthermore, although the invention is not limited thereto, the number of peaks (A) can be normalized (A') as follows:

[0104] A' = A / Q * 100

[0105] A' is the normalized number of peaks, A is the number of peaks, and Q is the total number of data points included in the analysis after quality check. In this example, an R or IR signal greater than or equal to 6000 was used, but this value can be changed. For each group member, the average A' of the IR / G curve and R / G curve was calculated over five brushing cycles.

[0106] Figure 14 This is a plot of the average number of normalized peaks per group member using the R / G ratio, and Figure 15 This is a plot of the average number of normalized peaks for each group member using the IR / G ratio. For Figure 14 and Figure 15 For each of the individuals in the equation, if a line is drawn parallel to the x-axis at y=4, the system will correctly predict four hemorrhage cases (P2, P4, P10, and P11) because they have a normalized peak count above the threshold. The system will also correctly predict five non-hemorrhage cases (P3, P5, P6, P8, and P9) as non-hemorrhage cases. There is one false positive (P7, a non-hemorrhage case predicted as hemorrhage) and one false negative (P1, a hemorrhage case predicted as non-hemorrhage).

[0107] For all models discussed in this paper, sensitivity and specificity are calculated using the following formula:

[0108] Sensitivity = TP / (TP + FN)

[0109] Specificity = TN / (TN+FP)

[0110] Among them, as predicted by the model, TP is the number of true positives, FN is the number of false negatives, TN is the number of true negatives, and FP is the number of false positives.

[0111] For both R / G and IR / G, the model's sensitivity and specificity are 0.8 and 0.83, respectively. The AUROCs for R / G and IR / G are 0.75 and 0.77, respectively. It is worth noting that in some other embodiments, other predetermined numbers (besides 4) can be used as a reference to determine whether the number of spikes indicates bleeding.

[0112] Because the grouping of bleeding and non-bleeding individuals is based on the number of peaks rather than the overall average signal, background interference caused by external factors (such as residual colored food or beverages like red wine or colored toothpaste) can be avoided. In the presence of such external interference, the average signal or baseline will rise, but bleeding points can still be identified by monitoring the spikes or peaks.

[0113] It is worth noting that, in another embodiment, the system may consider both the number of R / G peaks and the number of IR / G peaks to determine the presence of blood. For example, blood is considered absent unless both ratios meet a minimum number of peaks (which may be the same or different for each ratio).

[0114] Determine the vector length of data points outside the predetermined boundary.

[0115] In some alternative embodiments, the presence of hemoglobin can be determined based on a comparison ratio and by identifying characteristics (e.g., mathematical features) of data points within or outside predetermined boundaries. Two such embodiments are discussed below, sometimes referred to as Model 2 (vector length) and Model 3 (distribution range of clusters).

[0116] Figure 16A This is a graph showing the R / G ratio versus IR / G ratio for patients experiencing bleeding during a single brushing session. Figure 16BThis is a graph of the R / G ratio versus IR / G ratio for non-bleeding individuals during a brushing session. In an exemplary embodiment, a box 148 with the following four corners is created for each of these graphs: [0, 0], [8, 0], [8, 8], and [0, 8]. This box 148 defines a predetermined boundary with a predetermined region. Any data point within the box 148 is considered part of a cluster, and any data point outside the box is considered an outlier. While in this embodiment the predetermined boundary forms a 2D box, in other embodiments the predetermined boundary may simply be defined by two points (e.g., a minimum and a maximum value), which will be described in more detail below. In other embodiments, the box (predetermined region) may have different sizes or locations. Furthermore, the predetermined region may have different shapes. For example, the box may be circular, elliptical, or rhomboid instead.

[0117] Back Figure 16A To cluster B, the x and y coordinates of the cluster center are located as follows:

[0118] Cx = Sum of IR / G values ​​of all points in the frame / M

[0119] Cy = Sum of R / G values ​​of all points in the frame / M

[0120] Where M is the number of points within the frame after quality inspection. In this embodiment, the ratio R / G is plotted against IR / G for each brushing cycle of all participants.

[0121] Back Figure 16A and 16B It can be seen that for those who bleed ( Figure 16A ), clusters that are more tightly clustered than the unblemished individuals within them ( Figure 16B The peaks are much more dispersed. This is partly because the number of peaks in the reflex data of bleeding individuals is much larger compared to those of non-bleeding individuals, whose proportion remains relatively constant over time (see above).

[0122] As a quality check, a minimum reflected signal value was set for the R and IR channels of all models, for example, 6000 in this case. Further quality checks were included when analyzing using all three R, G, and IR wavelengths; the upper and lower limits of the IR / R ratio were set to 1.2 and 0.8, respectively. Therefore, any points where the total R and IR signals were less than 6000 (signal quality check) were eliminated. Furthermore, when analyzing using all three wavelengths (e.g., in models 2 and 3), any points where the IR / R ratio was less than 0.8 or greater than 1.2 (red quality check) were eliminated. However, the invention is not limited to this specific type of quality check.

[0123] In an exemplary embodiment of Model 2 (vector length), the system calculates the representative vector length, which is the sum of the distances from points outside the bounding box to the cluster center (Cx, Cy). For a given outlier P, the x and y distances from the cluster center are calculated as follows:

[0124] Px = (IR / G value of P) - Cx

[0125] Py = (R / G value of P) - Cy

[0126] The representative vector length V of outliers can be calculated using the following two methods:

[0127] Method 1

[0128] V = sqrt[(∑Px)^2 + (∑Py)^2]

[0129] Method 2

[0130] Vmod = ∑[sqrt(PX^2 + Py^2)]

[0131] In addition, the vector length is normalized relative to the number of data points used for analysis as follows:

[0132] V'=(V*100) / N

[0133] Vmod'=(Vmod*100) / N

[0134] Where N is the total number of points included in the analysis after the quality check. In this exemplary embodiment, for each group member, the average V' and Vmod' of five brushing cycles were calculated.

[0135] The sum of the vector lengths of the data points outside the frame and the cluster centers is calculated using two methods. The average normalized vector length for each group member is calculated over five brushing cycles. Figure 17 This is a graph of the average normalized vector lengths of the R, G, and IR channels for each of the 11 participants and for data points outside the predetermined bounding box. The results are very similar regardless of whether Method 1 or Method 2 is used. Figure 17 The results show that if 20 is used as the bleeding threshold, the system correctly identifies four bleeding patients (P2, P4, P10, and P11) and five non-bleeding patients (P3, P5, P6, P8, and P9). There is one false positive (P7, a non-bleeding patient was predicted as a bleeding patient) and one false negative (P1, a bleeding patient was predicted as a non-bleeding patient). The model's sensitivity and specificity are 0.8 and 0.83, respectively. The AUROC is 0.75, indicating model robustness. This model performs similarly to Model 1 in terms of sensitivity and specificity.

[0136] In some alternative embodiments, only two channels can be used at a time; for example, only the R / G ratio or the IR / G ratio can be used, and not both simultaneously. In this case, instead of using... Figure 16A and 16B Instead of using box 148 to define the predetermined boundaries of clusters, two points or values, namely the minimum and maximum values, are used to define the predetermined boundaries. According to Method 3, only the IR and G channels are used. The following formula is utilized:

[0137] Method 3

[0138] Px = (IR / G value of P) - Cx

[0139] Where Cx is the average IR / G data of points where the IR / G value is less than 8 after quality checking (similar to the box above, in some embodiments, the boundary values ​​0 and 8 can be replaced with other values). In this embodiment, the representative vector length Vir / g is calculated as follows:

[0140] Vir / g=∑Px

[0141] The vector length is normalized as follows:

[0142] Vir / g'=(Vir / g*100) / Nx

[0143] Where Nx is the total number of points included in the analysis after quality inspection. Figure 18 This is a graph showing the average normalized vector length of each of the 11 participants over 5 brushing cycles for a model using only the IR and G channels.

[0144] According to method 4, only the R and G channels are used. The following formula is utilized:

[0145] Method 4

[0146] Py = (R / G value of P) - Cy

[0147] Where Cy is the average R / G value of points with an R / G value less than 8 after quality checks. The representative vector length of outliers is calculated as follows:

[0148] Vr / g=∑Py

[0149] The vector length is normalized as follows:

[0150] Vr / g'=(Vr / g*100) / Ny

[0151] Where Ny is the total number of points included in the analysis after quality inspection. Figure 19This is a plot showing the average normalized vector length for each of the 11 participants over five brushing cycles in a model using only the R and G channels. The sensitivity, specificity, and AUROC using these 2-channel methods range from 0.8, 0.83, and 0.74 to 0.75, respectively. The plot shows that the 2-channel method yields similar results to the 3-channel method.

[0152] Determine the distribution range of data points within the predetermined boundary.

[0153] In the third model, hemoglobin is detected based on the distribution range of data points within a bounding box (see above) defined by coordinates [0, 0], [8, 0], [8, 8], and [0, 8]. In other embodiments, the bounding box (predetermined region) may have different sizes or locations. The distribution range of points within the bounding box is sometimes referred to herein as the "cluster distribution range". In an exemplary embodiment, the cluster distribution range is calculated as follows. Using the center of the cluster (as determined above), the distance to the cluster center can be determined as follows:

[0154] Dx = Absolute value (IR / G value at a given point - Cx)

[0155] Dy = Absolute value (R / G value at a given point - Cy)

[0156] For example, the distribution range (S) can be determined using one of the following two methods:

[0157] Method 1

[0158] Ex=∑Dx / M

[0159] Ey=∑Dy / M

[0160] S = sqrt(Ex^2 + Ey^2)

[0161] Method 2

[0162] Smod=[∑[sqrt(Dx^2+Dy^2)]] / M

[0163] Where M is the number of points within the box after quality inspection. This distribution range can be normalized relative to the number of data points used for analysis as follows:

[0164] S'=(S*100) / N

[0165] Smod'=(Smod*100) / N

[0166] Where N is the total number of points after quality checks. For each group member, calculate the average normalized distribution range over five brushing cycles.

[0167] Figure 20A and20B These are graphs showing the average normalized distribution range of data points in the frame for each group member over five brushing cycles, based on the first and second methods, respectively. If a distribution range threshold of 0.37 is used for method 1 ( Figure 20A ), and a distribution range threshold of 0.4 is used for method 2 ( Figure 20B If the system can effectively and correctly identify all bleeding patients (P1, P2, P4, P10, and P11), it can also correctly identify P3, P5, P6, P8, and P9 as non-bleeding patients. One false positive (P7) was observed using this model. The sensitivity and specificity for this method were 1 and 0.83, respectively. The AUROC was 0.8, indicating model robustness.

[0168] In some alternative embodiments, only two channels can be used at a time; for example, only the R / G ratio or the IR / G ratio can be used, and not both simultaneously. According to method 3, only the IR and G channels are used. This utilizes the following formula:

[0169] Method 3

[0170] Dx = Absolute value (IR / G value at a given point - Cx)

[0171] Sir / g=∑Dx / Mx

[0172] Where Cx is the average IR / G data of points with IR / G values ​​less than 8 after quality check, and Mx is the number of points with IR / G values ​​less than 8 after quality check.

[0173] The distribution range is normalized as follows:

[0174] sir / g'=(Sir / g*100) / Nx

[0175] Where Nx is the number of points after quality inspection. Figure 21 This is a graph showing the average normalized cluster distribution range of 11 participants over five brushing cycles for a model using only IR and G channels.

[0176] According to method 4, only the R and G channels are used. The following formula is utilized:

[0177] Method 4 (using only R and G channels)

[0178] Dy = Absolute value (R / G value at a given point - Cy)

[0179] Sr / g=∑Dy / My

[0180] Where Cy is the average R / G value of points with an R / G value less than 8 after quality check, and My is the number of points with an R / G value less than 8 after quality check.

[0181] The distribution range is normalized as follows:

[0182] Sr / g'=(Sr / g*100) / Ny

[0183] Where Ny is the number of points after quality inspection. Figure 22 This is a plot showing the average normalized cluster distribution of 11 participants over five brushing cycles for a model using only the R and G channels. Using two methods, the sensitivity, specificity, and AUROC ranged from 1 to 0.77 and 0.78, respectively. The specificity and AUROC are slightly lower than in the case where we used three channels for analysis, as shown above, but sensitivity is generally more critical, and lower specificity (larger number of false positives) is less concerning.

[0184] It is worth noting that bleeding data identified and collected (through any means discussed herein) can be used to determine cumulative bleeding data. This cumulative bleeding data can be any representative bleeding data from one or more previous brushing sessions, such as an indication of the percentage of previous brushing sessions in which bleeding was detected (and / or in which bleeding was detected at a certain location). The data can be displayed (and / or determined) by a separate electronic device, such as a smartphone or computer communicating with the toothbrush (as described above). In other embodiments, the cumulative data is displayed (and / or determined) by the toothbrush itself.

[0185] In one example where the cumulative data is displayed by the toothbrush itself, the toothbrush has an LED. The LED flashes rapidly for 2 seconds to indicate the result of a single brushing session, where flashing green indicates no bleeding and flashing red indicates bleeding was detected. The LED then settles for 2 seconds to present the cumulative result of previous brushing sessions, where a stable green indicates bleeding in less than 10% of previous brushing sessions, a stable yellow-green indicates bleeding in 10% to 50% of previous brushing sessions, and a stable red indicates bleeding in more than 50% of previous sessions. In this embodiment, using a stable LED, the toothbrush requires at least 5 valid brushing sessions before it can display the cumulative result. The toothbrush stores raw data from the last 28 brushing sessions in its memory (using a cyclic format) to calculate the cumulative result. Furthermore, if the user wants to view their cumulative result, the user can quickly press the button twice. In response, the LED will settle for 2 seconds to display the result using the color scheme described above. Of course, the described embodiment is just one of many ways to determine and / or display cumulative brushing data. For example, different LEDs, colors, timing schemes, percentages, number of brushing sessions, and button press schemes can be utilized or omitted. This invention is not limited to any particular embodiment.

[0186] It should also be noted that in the above embodiments, certain steps of equations for normalization and other calculations were used. Such steps are not necessary, and the specific equations provided are merely non-limiting examples.

[0187] While the invention has been described with reference to specific examples (including the currently preferred mode for carrying out the invention), those skilled in the art will understand that numerous variations and substitutions exist for the systems and techniques described above. It should be understood that other embodiments and structural and functional modifications can be utilized without departing from the scope of the invention. Therefore, the spirit and scope of the invention should be broadly interpreted as set forth in the appended claims.

[0188] Exemplary claims

[0189] The following are exemplary claims of the above invention:

[0190] 1. A system for detecting blood in the oral cavity during brushing teeth, the system comprising: a toothbrush including a sensor configured to: emit a first light of a first wavelength and a second light of a second wavelength; receive reflected portions of the first light and the second light; and for each of a plurality of different times, generate a first signal indicating a first intensity of the reflected portion of the first light and a second signal indicating a second intensity of the reflected portion of the second light; and a processor operatively coupled to the sensor and configured to: for each of the plurality of different times, receive the first signal and the second signal and calculate a ratio of the first intensity to the second intensity; identify peaks of the ratio corresponding to the different times; and determine the presence of hemoglobin in the oral cavity based on the number of peaks of the ratio corresponding to the different times.

[0191] 2. The system of claim 1, wherein the plurality of different times are separated by a predetermined time period.

[0192] 3. The system of any of the preceding claims, wherein determining the presence of hemoglobin is based on the number of peaks that meet or exceed a predetermined non-zero number during brushing.

[0193] 4. The system of any one of the preceding claims, wherein each of the peaks has a peak ratio value that satisfies or exceeds a predetermined threshold.

[0194] 5. The system of any one of the preceding claims, wherein each of the peaks is separated from each other peak by a predetermined time value.

[0195] 6. The system of any one of the preceding claims, wherein the processor is configured to calculate the amount of blood detected in the oral cavity during the brushing period based on the number of the peaks.

[0196] 7. The system of any one of the preceding claims, wherein the toothbrush further comprises a tracking sensor configured to generate a position signal relating to the position of the head of the toothbrush in the oral cavity during brushing, and wherein the processor is operatively coupled to the tracking sensor and configured to receive the position signal to determine the position of the head of the toothbrush in the oral cavity at each peak detected.

[0197] 8. The system of any one of the preceding claims, wherein the sensor is further configured to emit a third light of a third wavelength, receive a reflected portion of the third light, and generate a third signal indicating a third intensity of the reflected portion of the third light; and wherein the processor is further configured to: receive the third signal at the plurality of different times, calculate a second ratio of the third intensity to the second intensity; and identify peaks of the second ratio corresponding to the different times; wherein the determination of the presence of hemoglobin is also based on the number of peaks of the second ratio corresponding to the different times.

[0198] 9. The system of the preceding claims, wherein the first light is red light, the second light is green light, and the third light is infrared light.

[0199] 10. The system of any one of the preceding claims, further comprising an indicator configured to provide a user with an indication of the presence of blood in the oral cavity.

[0200] 11. The system of any one of the preceding claims, wherein the toothbrush includes the processor.

[0201] 12. The system of the preceding claim, wherein the toothbrush further comprises an indicator configured to provide the user with an indication of the presence of blood in the oral cavity.

[0202] 13. The system of any one of the preceding claims, further comprising a portable electronic device containing the processor.

[0203] 14. The system of the preceding claims, further comprising a software application stored on the portable electronic device, wherein the software application is configured to cause the display screen of the portable electronic device to provide a user with an indication of the presence of blood in the mouth.

[0204] 15. The system of any of the preceding claims, wherein the software application is configured to store information related to blood detection in the oral cavity for each of a plurality of different brushing times, and wherein the information is displayed on the display screen of the portable electronic device.

[0205] 16. The system of any one of the preceding claims, wherein the toothbrush further comprises: a handle; a head coupled to the handle, wherein the sensor is located in the head; and a plurality of cleaning elements extending from the head in a cleaning element region, the cleaning element region having an opening forming a light path for the first light and the second light to be emitted from and received by the sensor.

[0206] 17. The system of any one of the preceding claims, wherein the toothbrush comprises: a body including a handle portion and a rod extending from the handle portion, the sensor being located in the rod; and a replacement head including a sleeve portion fitted onto the rod to connect the replacement head to the body, a head portion aligned with the sensor in the rod, and a plurality of cleaning elements extending from the head portion.

[0207] 18. A method for detecting blood in an oral cavity during brushing of teeth, the method comprising: during a brushing period of brushing the oral cavity with a toothbrush: emitting a first light of a first wavelength and a second light of a second wavelength into the oral cavity via a sensor of the toothbrush; receiving reflected portions of the first light and the second light via the sensor of the toothbrush; and for each of a plurality of different times during the brushing period, sending from the sensor to a processor a first signal indicating a first intensity of the reflected portion of the first light and a second signal indicating a second intensity of the reflected portion of the second light; for each of the plurality of different times, calculating by the processor a ratio of the first intensity to the second intensity; identifying peaks of the ratio corresponding to the different times by the processor; and determining, by the processor, the presence of hemoglobin in the oral cavity based on the number of peaks of the ratio corresponding to the different times.

[0208] 19. The method of claim 18, wherein the plurality of different times are separated by a predetermined time period.

[0209] 20. The method of any one of claims 18 to 19, wherein determining the presence of hemoglobin is based on the number of peaks that meet or exceed a predetermined non-zero number during brushing.

[0210] 21. The method of any one of claims 18 to 20, wherein each of the peaks has a peak ratio value that satisfies or exceeds a predetermined threshold.

[0211] 22. The method of any one of claims 18 to 21, wherein each of the peaks is spaced apart from each other peak by a predetermined time value.

[0212] 23. The method of any one of claims 18 to 22, further comprising the processor calculating, based on the number of peaks, the amount of blood detected in the oral cavity during the brushing period.

[0213] 24. The method of any one of claims 18 to 23, further comprising: a tracking sensor of the toothbrush generating a position signal relating to the position of the head of the toothbrush within the oral cavity during brushing; and the processor receiving the position signal to determine the position of the head of the toothbrush within the oral cavity at each peak detected.

[0214] 25. The method of any one of claims 18 to 24, further comprising: the sensor emitting third light of a third wavelength, receiving a reflected portion of the third light, and generating a third signal indicating a third intensity of the reflected portion of the third light; and the processor receiving the third signal at the plurality of different times and calculating a second ratio of the third intensity to the second intensity; and the processor identifying peaks of the second ratio corresponding to the different times; wherein the determination of the presence of hemoglobin is also based on the number of peaks of the second ratio corresponding to the different times.

[0215] 26. The method of the preceding claim, wherein the first light is red light, the second light is green light, and the third light is infrared light.

[0216] 27. The method of any one of claims 18 to 26, further comprising an indicator providing the user with an indication of the presence of blood in the oral cavity.

[0217] 28. The method of any one of claims 18 to 27, wherein the toothbrush comprises the processor.

[0218] 29. The method according to the preceding claim, wherein the toothbrush further comprises an indicator that provides the user with an indication of the presence of blood in the oral cavity.

[0219] 30. The method of any one of claims 18 to 29, wherein the processor forms part of a portable electronic device.

[0220] 31. The method of the preceding claim, further comprising a software application stored on the portable electronic device that causes the display screen of the portable electronic device to provide a user with an indication of the presence of blood in the mouth.

[0221] 32. The method of the preceding claim, further comprising the software application storing information related to blood detection in the oral cavity for each of a plurality of different brushing times, and displaying the information on the display screen of the portable electronic device.

[0222] 33. The method of claims 18 to 32, wherein the toothbrush further comprises: a handle; a head coupled to the handle, wherein the sensor is located in the head; and a plurality of cleaning elements extending from the head in a cleaning element region, the cleaning element region having an opening forming a light path for the first light and the second light to be emitted from and received by the sensor.

[0223] 34. The method of claims 18 to 33, wherein the toothbrush comprises: a body including a handle portion and a rod extending from the handle portion, the sensor being located in the rod; and a replacement head including a sleeve portion fitted onto the rod to connect the replacement head to the body, a head portion aligned with the sensor in the rod, and a plurality of cleaning elements extending from the head portion.

[0224] 35. A system for detecting blood in a mouth during brushing teeth, the system comprising: a toothbrush including a sensor configured to: emit a first light of a first wavelength and emit a second light of a second wavelength; receive reflected portions of the first light and the second light; and generate a first signal indicating a first intensity of the reflected portion of the first light and a second signal indicating a second intensity of the reflected portion of the second light; and a processor operatively coupled to the sensor and configured to: receive the first signal and the second signal for a plurality of different times; and calculate a ratio of the first intensity to the second intensity; wherein the ratio at the different times forms data points; identify which of the data points are within a predetermined boundary and which of the data points are outside the predetermined boundary; and determine the presence of hemoglobin in the mouth based on characteristics of the data points within the predetermined boundary or the data points outside the predetermined boundary.

[0225] 36. The system of claim 35, wherein the predetermined boundary is formed by a minimum value and a maximum value.

[0226] 37. The system of any one of claims 35 to 36, wherein the sensor is further configured to emit a third light of a third wavelength, receive a reflected portion of the third light, and generate a third signal indicating a third intensity of the reflected portion of the third light; wherein the processor is further configured to receive the third signal for the plurality of different times and calculate a second ratio of the third intensity to the second intensity; wherein each data point includes the ratio as a first coordinate and includes the second ratio as a second coordinate; and wherein the predetermined boundary forms a predetermined region within or outside each data point.

[0227] 38. The system of any one of claims 35 to 37, wherein the feature upon which the determination of the presence or absence of hemoglobin is based is the vector length of each of the data points outside the predetermined boundary; and wherein the vector length is measured from the center of the data point within the predetermined boundary to the data point outside the predetermined boundary.

[0228] 39. The system of the preceding claim, wherein the determination of the presence or absence of hemoglobin is based on whether the sum of the vector lengths exceeds a predetermined number; or whether the average value of the vector lengths exceeds a predetermined number.

[0229] 40. The system of any one of claims 35 to 39, wherein the feature upon which the determination of the presence or absence of hemoglobin is based is the distribution range of the data points within the predetermined boundary.

[0230] 41. The system of the preceding claim, wherein for each data point within the predetermined boundary, the distribution range is based on the distance between the data point within the predetermined boundary and the center of the data point.

[0231] 42. The system of any one of claims 35 to 41, wherein the processor is configured to calculate the amount of blood detected in the oral cavity during a brushing period based on the characteristics of the data points within or outside the predetermined boundary.

[0232] 43. The system of any one of claims 35 to 42, wherein the toothbrush further comprises a tracking sensor configured to generate a position signal relating to the position of the head of the toothbrush within the oral cavity during brushing, and wherein the processor is operatively coupled to the tracking sensor and configured to receive the position signal to determine the position of the head when the presence of hemoglobin is determined.

[0233] 44. The system of any one of claims 35 to 43, further comprising an indicator configured to provide a user with an indication of the presence of blood in the oral cavity.

[0234] 45. The system of any one of claims 35 to 44, wherein the toothbrush comprises the processor.

[0235] 46. ​​The system of the preceding claim, wherein the toothbrush further comprises an indicator configured to provide a user with an indication of the presence of blood in the oral cavity.

[0236] 47. The system of any one of claims 35 to 46, further comprising a portable electronic device containing the processor.

[0237] 48. The system of the preceding claims, further comprising a software application stored on the portable electronic device, wherein the software application is configured to cause the display screen of the portable electronic device to provide a user with an indication of the presence of blood in the mouth.

[0238] 49. The system of any one of the preceding claims, wherein the software application is configured to store information related to blood detection in the oral cavity for each of a plurality of different brushing times, and wherein the information is displayed on the display screen of the portable electronic device.

[0239] 50. The system of any one of claims 35 to 49, wherein the toothbrush further comprises: a handle; a head coupled to the handle, wherein the sensor is located in the head; and a plurality of cleaning elements extending from the head in a cleaning element region, the cleaning element region having an opening forming a light path for the first light and the second light to be emitted from and received by the sensor.

[0240] 51. The system of any one of claims 35 to 50, wherein the toothbrush comprises: a body including a handle portion and a rod extending from the handle portion, the sensor being located in the rod; and a replacement head including a sleeve portion fitted onto the rod to connect the replacement head to the body, a head portion aligned with the sensor in the rod, and a plurality of cleaning elements extending from the head portion.

[0241] 52. A method for detecting blood in an oral cavity during brushing of teeth, the system comprising: during a brushing period of brushing the oral cavity with a toothbrush: emitting a first light of a first wavelength and a second light of a second wavelength into the oral cavity via a sensor of the toothbrush; receiving reflected portions of the first light and the second light via the sensor of the toothbrush; and, for a plurality of different times during the brushing period, sending from the sensor to a processor a first signal indicating a first intensity of the reflected portion of the first light and a second signal indicating a second intensity of the reflected portion of the second light; for each of the plurality of different times, calculating by the processor a ratio of the first intensity to the second intensity, wherein the ratio of the different times forms data points; identifying by the processor which of the data points are within a predetermined boundary and which of the data points are outside the predetermined boundary; and determining by the processor, based on characteristics of the data points within the predetermined boundary or the data points outside the predetermined boundary, whether hemoglobin is present in the oral cavity.

[0242] 53. The method of claim 52, wherein the predetermined boundary is formed by a minimum value and a maximum value.

[0243] 54. The method of any one of claims 52 to 53, further comprising: the sensor emitting a third light of a third wavelength, receiving a reflected portion of the third light, and generating a third signal indicating a third intensity of the reflected portion of the third light; and the processor receiving the third signal for the plurality of different times and calculating a second ratio of the third intensity to the second intensity; wherein each data point includes the ratio as a first coordinate and includes the second ratio as a second coordinate; and wherein the predetermined boundary forms a predetermined region within or outside each data point.

[0244] 55. The method of any one of claims 52 to 54, wherein the feature upon which the determination of the presence or absence of hemoglobin is based is the vector length of each of the data points outside the predetermined boundary; and wherein the vector length is measured from the center of the data point within the predetermined boundary to the data point outside the predetermined boundary.

[0245] 56. The method of the preceding claim, wherein the determination of the presence or absence of hemoglobin is based on whether the sum of the vector lengths exceeds a predetermined number, or whether the average value of the vector lengths exceeds a predetermined number.

[0246] 57. The method of any one of claims 52 to 56, wherein the characteristic upon which the determination of the presence or absence of hemoglobin is based is the distribution range of the data points within the predetermined boundary.

[0247] 58. The method of the preceding claim, wherein for each data point within the predetermined boundary, the distribution range is based on the distance between the data point within the predetermined boundary and the center of the data point.

[0248] 59. The method of any one of claims 52 to 58, further comprising the processor calculating the amount of blood detected in the oral cavity during the brushing period based on the characteristics of the data points within or outside the predetermined boundary.

[0249] 60. The method of any one of claims 52 to 59, wherein the toothbrush further comprises a tracking sensor that generates a position signal relating to the position of the head of the toothbrush within the oral cavity during brushing, and the processor receives the position signal to determine the position of the head when the presence of hemoglobin is determined.

[0250] 61. The method of any one of claims 52 to 60, further comprising an indicator providing the user with an indication of the presence of blood in the oral cavity.

[0251] 62. The method of any one of claims 52 to 61, wherein the toothbrush comprises the processor.

[0252] 63. The method of the preceding claim, wherein the toothbrush further comprises an indicator that provides the user with an indication of the presence of blood in the oral cavity.

[0253] 64. The method of any one of claims 52 to 63, wherein the processor forms part of a portable electronic device.

[0254] 65. The method of the preceding claim, further comprising a software application stored on the portable electronic device that causes the display screen of the portable electronic device to provide a user with an indication of the presence of blood in the mouth.

[0255] 66. The method of the preceding claim, further comprising the software application storing information related to blood detection in the oral cavity for each of a plurality of different brushing times, and displaying the information on the display screen of the portable electronic device.

[0256] 67. The method of claims 52 to 66, wherein the toothbrush further comprises: a handle; a head coupled to the handle, wherein the sensor is located in the head; and a plurality of cleaning elements extending from the head in a cleaning element region, the cleaning element region having an opening forming a light path for the first light and the second light to be emitted from and received by the sensor.

[0257] 68. The method of claims 52 to 67, wherein the toothbrush comprises: a body including a handle portion and a rod extending from the handle portion, the sensor being located in the rod; and a replacement head including a sleeve portion fitted onto the rod to connect the replacement head to the body, a head portion aligned with the sensor in the rod, and a plurality of cleaning elements extending from the head portion.

Claims

1. A system for detecting blood in the oral cavity during brushing teeth, the system comprising: A toothbrush, the toothbrush including a sensor, the sensor being configured to: Emit a first wavelength of light and a second wavelength of light; Receives the reflected portions of the first light and the second light; and For each of a plurality of different times, a first signal indicating a first intensity of the reflected portion of the first light and a second signal indicating a second intensity of the reflected portion of the second light are generated; and A processor, operably coupled to the sensor and configured to: For each of the plurality of different times, the first signal and the second signal are received, and the ratio of the first intensity to the second intensity is calculated; Identify the peaks of the ratios corresponding to the different times; and The presence of hemoglobin in the oral cavity is determined based on the number of peaks at the corresponding ratios at different times.

2. The system of claim 1, wherein the plurality of different times are separated by a predetermined time period.

3. The system of claim 1, wherein determining the presence of hemoglobin is based on whether the number of peaks during the brushing period meets or exceeds a predetermined non-zero number.

4. The system of claim 3, wherein each of the peaks has a peak ratio value that satisfies or exceeds a predetermined threshold.

5. The system of claim 1, wherein each of the peaks is separated from each other peak by a predetermined time value.

6. The system of claim 1, wherein the processor is configured to calculate the amount of blood detected in the oral cavity during the brushing period based on the number of peaks.

7. The system of claim 1, wherein the toothbrush further comprises a tracking sensor configured to generate a position signal relating to the position of the head of the toothbrush in the oral cavity during brushing, and wherein the processor is operatively coupled to the tracking sensor and configured to receive the position signal to determine the position of the head of the toothbrush in the oral cavity at each peak detected.

8. The system according to claim 1: The sensor is further configured to emit a third wavelength of light, receive a reflected portion of the third light, and generate a third signal indicating the third intensity of the reflected portion of the third light; and The processor is further configured to: The third signal is received at the multiple different times, and a second ratio of the third intensity to the second intensity is calculated; and Identify the peaks of the second ratio corresponding to the different times; The determination of the presence of hemoglobin is also based on the number of peaks at the corresponding second ratio at different times.

9. The system of claim 8, wherein the first light is red light, the second light is green light, and the third light is infrared light.

10. The system of claim 1, further comprising an indicator configured to provide a user with an indication of the presence of blood in the oral cavity.

11. A system for detecting blood in the oral cavity during brushing teeth, the system comprising: A toothbrush, the toothbrush including a sensor, the sensor being configured to: Emit a first light of a first wavelength and emit a second light of a second wavelength; Receives the reflected portions of the first light and the second light; and A first signal indicating the first intensity of the reflected portion of the first light is generated, and a second signal indicating the second intensity of the reflected portion of the second light is generated; as well as A processor, operably coupled to the sensor and configured to: For multiple different times: Receive the first signal and the second signal; and Calculate the ratio of the first strength to the second strength; The ratios at different times form data points; Identify which data points are within the predetermined boundary and which data points are outside the predetermined boundary; and The presence of hemoglobin in the oral cavity is determined based on the characteristics of the data points within or outside the predetermined boundary.

12. The system of claim 11, wherein the predetermined boundary is formed by a minimum value and a maximum value.

13. The system according to any one of claims 11: The sensor is further configured to emit a third light of a third wavelength, receive a reflected portion of the third light, and generate a third signal indicating a third intensity of the reflected portion of the third light. The processor is further configured to receive the third signal at the plurality of different times and calculate a second ratio of the third intensity to the second intensity; Each of the data points includes the ratio as a first coordinate and the second ratio as a second coordinate; and The predetermined boundary forms a predetermined region, and each data point is located within or outside the predetermined region.

14. The system of claim 13: The feature is based on the vector length of each data point outside the predetermined boundary; and The vector length is measured from the center of the data point within the predetermined boundary to the data point outside the predetermined boundary.

15. The system of claim 14, wherein the feature is one of: whether the sum of the vector lengths exceeds a predetermined number; or whether the average value of the vector lengths exceeds a predetermined number.

16. The system of claim 11, wherein the feature is the distribution range of the data points within the predetermined boundary.

17. The system of claim 16, wherein for each data point within the predetermined boundary, the distribution range is based on the distance between the data point within the predetermined boundary and the center of the data point.

18. The system of claim 11, wherein the processor is configured to calculate the amount of blood detected in the oral cavity during a brushing period based on the characteristics of the data points within or outside the predetermined boundary.

19. The system of claim 11, wherein the toothbrush further comprises a tracking sensor configured to generate a position signal relating to the position of the toothbrush head within the oral cavity during brushing, and wherein the processor is operatively coupled to the tracking sensor and configured to receive the position signal to determine the position of the head when the presence of hemoglobin is determined.

20. The system of claim 11, further comprising an indicator configured to provide a user with an indication of the presence of blood in the oral cavity.

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