KR20220097033A - Defecation pad with color code attached - Google Patents

Abstract

According to one embodiment, a defecation pad to which a color code is attached. The defecation pad includes: a color code attached to one side; and a pad accommodating a defecation object. The color code is composed of colors that are criteria for determining the state of the defecation object.

Description

DEFECATION PAD WITH COLOR CODE ATTACHED}

The following embodiments relate to a technology for providing a defecation pad to which a color code is attached for analyzing the defecation pad stool image.

The companion animal health diagnosis market is growing rapidly. As the number of people who own companion animals increases, the market related to companion animal health is rapidly increasing as interest increases.

Until now, most of the diagnostic services using sensors are. For example, in the smart defecation pad alarm service, there is a method in which the sensor of the defecation pad notifies whether urine is discharged through a smartphone application, or there is a method in which a physical sensor is directly attached to the defecation pad.

According to an embodiment, a color code attached to one side and a pad for accommodating a stool object are included, and the color code is a defecation pad with a color code attached to colors that are standards for determining the state of the stool object. It is intended to provide

Objects of the present invention are not limited to the objects mentioned above, and other objects not mentioned will be clearly understood from the description below.

According to one embodiment, a color code attached to one side; and a pad for accommodating the stool object, wherein the color code is provided with a color code as a reference color for determining the state of the stool object.

According to an embodiment, a color code attached to one side and a pad for accommodating a stool object are included, and the color code is a defecation pad with a color code attached to colors that are standards for determining the state of the stool object. can provide

On the other hand, effects according to the embodiments are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those of ordinary skill in the art from the description below.

1 is a view for explaining a method of obtaining an image for a bowel movement pad according to an embodiment.
Figure 2 is a view for explaining a method for determining the defecation pad stool image according to an embodiment.
Figure 3 is a view for explaining a bowel movement pad is attached to the color code according to an embodiment.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, since various changes may be made to the embodiments, the scope of the patent application is not limited or limited by these embodiments. It should be understood that all modifications, equivalents and substitutes for the embodiments are included in the scope of the rights.

Specific structural or functional descriptions of the embodiments are disclosed for purposes of illustration only, and may be changed and implemented in various forms. Accordingly, the embodiments are not limited to the specific disclosure form, and the scope of the present specification includes changes, equivalents, or substitutes included in the technical spirit.

Although terms such as first or second may be used to describe various elements, these terms should be interpreted only for the purpose of distinguishing one element from another. For example, a first component may be termed a second component, and similarly, a second component may also be termed a first component.

When a component is referred to as being “connected to” another component, it may be directly connected or connected to the other component, but it should be understood that another component may exist in between.

The terms used in the examples are used for the purpose of description only, and should not be construed as limiting. The singular expression includes the plural expression unless the context clearly dictates otherwise. In this specification, terms such as "comprise" or "have" are intended to designate that a feature, number, step, operation, component, part, or a combination thereof described in the specification exists, but one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiment belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

In addition, in the description with reference to the accompanying drawings, the same components are given the same reference numerals regardless of the reference numerals, and the overlapping description thereof will be omitted. In describing the embodiment, if it is determined that a detailed description of a related known technology may unnecessarily obscure the gist of the embodiment, the detailed description thereof will be omitted.

The embodiments may be implemented in various types of products, such as personal computers, laptop computers, tablet computers, smart phones, televisions, smart home appliances, intelligent cars, kiosks, wearable devices, and the like.

1 is a view for explaining a method of obtaining an image for a bowel movement pad according to an embodiment.

Referring to Figure 1, the device may acquire an image for the defecation pad. The device is a device for determining the defecation pad stool image, and may be implemented as, for example, a hardware module, a software module, or a combination thereof. The apparatus may identify a stool object and a color code from the image, preprocess the stool object based on the color code, and process the preprocessed stool object to generate a stool state determination result.

According to an embodiment, the device may be an electronic device. The electronic device may be a smart home appliance having a communication function. Smart home appliances include, for example, a television, a digital video disk (DVD) player, an audio device, a refrigerator, an air conditioner, a vacuum cleaner, an oven, a microwave oven, a washing machine, an air purifier, a set-top box, and a TV. It may include at least one of a box (eg, Samsung HomeSync™, Apple TV™, or Google TV™), game consoles, an electronic dictionary, an electronic key, a camcorder, or an electronic picture frame.

According to an embodiment, the electronic device includes various medical devices (eg, magnetic resonance angiography (MRA), magnetic resonance imaging (MRI), computed tomography (CT), imagers, ultrasound machines, etc.), navigation devices, and GPS receivers ( global positioning system receiver), EDR (event data recorder), FDR (flight data recorder), automotive infotainment device, marine electronic equipment (e.g. marine navigation system and gyro compass, etc.), avionics, security It may include at least one of a device, a head unit for a vehicle, an industrial or household robot, an automatic teller's machine (ATM) of a financial institution, or a point of sales (POS) of a store.

According to an embodiment, the electronic device is a piece of furniture or a building/structure including a communication function, an electronic board, an electronic signature receiving device, a projector, or various measurement devices. It may include at least one of devices (eg, water, electricity, gas, or radio wave measuring devices, etc.). The electronic device according to an embodiment may be a combination of one or more of the various devices described above. Also, the electronic device according to an embodiment may be a flexible device. Also, it is apparent to those skilled in the art that the electronic device according to an embodiment is not limited to the above-described devices. The term user used in various embodiments may refer to a person who uses an electronic device or a device (eg, an artificial intelligence electronic device) using the electronic device.

An electronic device according to an embodiment includes a processor, a memory, a user interface, and a communication interface, and may be connected to another electronic device through a network. The communication interface may transmit/receive data to and from another electronic device within a predetermined distance through a wired or wireless network or wired serial communication. The network enables wired and wireless communication between the electronic device and various entities according to an embodiment. The electronic device may communicate with various entities over a network, and the network may use standard communication technologies and/or protocols. At this time, the network includes, but is not limited to, the Internet, a local area network (LAN), a wireless local area network (Wireless LAN), a wide area network (WAN), a personal area network (PAN), and the like, A person skilled in the art of communication technology can recognize that it may be another type of network capable of transmitting and receiving information.

The portable terminal according to an embodiment may be an electronic device including a communication function. For example, the electronic device includes a smart phone, a tablet personal computer (PC), a mobile phone, a video phone, an e-book reader, a desktop personal computer (PC), and a laptop computer. PC (laptop personal computer), netbook computer (netbook computer), PDA (personal digital assistant), PMP (portable multimedia player), MP3 player, mobile medical device, camera, or wearable device (eg: at least one of a head-mounted-device (HMD) such as electronic glasses, electronic apparel, electronic bracelets, electronic necklaces, electronic accessories, electronic tattoos, smart cars, or smartwatches. can

Figure 2 is a view for explaining a method for determining the defecation pad stool image according to an embodiment.

Referring to FIG. 2 , the device may include a solution for providing health status information according to color and shape from the stool of a companion animal by analyzing the defecation pad image when the defecation pad is photographed using a smartphone application.

For example, if the owner inputs basic information such as the date of birth, gender, and breastfeeding of the companion animal through the application, the condition of the stool analyzed based on the image taken from the toilet pad, the health diagnosis result and cause according to the condition of the stool , the need for a visit to the veterinary hospital, and customized stool condition guide information according to the number of days after birth.

It is possible to standardize the image that changes according to the shooting environment and camera specifications, attach a “color code” to one side of the toilet pad to prevent analysis distortion, and analyze the image with “color code” based on the learned model. have.

From the point of view of the consumer group, defecation pad consumers, companion animal feces are a measure of their health, but owners who check their pet's feces every day while grinding the toilet pad take pictures of their pet's feces to improve the health of companion animals who have difficulty communicating. Relevant information may be provided.

From the point of view of the owner who is raising children, which is the place of use, the health status of companion animals, child care information, and information about nearby hospitals can be provided from the stool image of the toilet pad.

From the point of view of a defecation pad company, if a business alliance is promoted with a defecation pad company based on a defecation pad stool image analysis solution and "color code", the demand for a "smart defecation pad solution" may increase.

From the point of view of a veterinary hospital, since the defecation pad stool image can be used as an auxiliary for diagnosis, there may be inquiries for partnership with the companion animal stool analysis platform. You can connect patients with nearby hospitals.

The device may provide health status information according to color and shape from the stool of the companion animal by analyzing the defecation pad image.

If basic information such as date of birth, gender, and whether breastfeeding is entered through the application, the condition of the stool analyzed based on the image taken from the stool pad, the medical examination results and causes according to the condition of the stool, the need to visit a veterinary hospital, the number of days after birth You can receive customized stool condition guide information according to the

A “color code” is attached to one side of the toilet pad, and the image containing the “color code” can be analyzed based on the learned model.

Veterinary hospitals are already diagnosing health conditions from companion animal feces, and it is recommended to bring a bowel pad to a specialist in veterinary hospital diagnosis. If you use image processing technology based on machine learning, machine learning, you can train a specialist in the diagnosis of defecation pad stool photos.

It is a service that notifies whether urine is discharged from a sensor in the defecation pad. It is a "color code" based defecation pad stool diagnosis solution, which can attract investment from defecation pad companies and create a business model through collaboration with veterinary hospitals.

In order to correct image distortion, a “color code” is attached to one side of a defecation pad, and an image with “color code” is applied to the pre-trained SegNet model and ResNet model to classify stool status, and rapid diagnosis of veterinary hospitals In a way that provides preliminary information for

Auggi, a startup founded by MIT/Harvard researchers in 2019, is writing a thesis that classifies stool images as constipation/normal/diarrhea, and is preparing a service based on this.

auggi simply provides results of stool image analysis. In contrast to this, according to an embodiment of the present invention, labeling and training are performed according to the birth date of the companion animal to analyze the stool image on the toilet pad of the companion animal, which is difficult to express its condition in language, so that standardized A more accurate diagnosis result may be determined from the background image. In addition, compared to auggi, this founding item is technically differentiated in that it performs image pre-processing using "color code".

The patent for “A diaper sensor for detecting and differentiating feces and urine”, which was applied by Google in 2016, is a method of directly attaching a physical sensor to a defecation pad. Although only collecting information by mounting a sensor on the pad, according to an embodiment of the present invention, there is a distinctive feature in that the color and shape of feces containing important health condition information are analyzed.

After developing a defecation pad stool image diagnosis solution, we presented a voucher to purchase a defecation pad as an incentive for filming to secure users. It is possible to increase the accuracy of the solution by using the obtained stool image additionally for training.

Currently, a toilet pad sensor is used to provide an alarm for defecation, but as an additional service, a companion animal health diagnosis solution can be provided to secure users and increase sales. 3) + By presenting as a companion animal health condition diagnosis, you can expand the subscription service using the toilet pad as an item.

Based on the preliminary results of diagnosing the health condition of companion animals, a nearby veterinary hospital can be recommended, and a profit model can be created by using the feces image for veterinary hospital diagnosis. It is possible to establish an advertising business related to childcare.

It is the companion animal's "feces status", which is a measure of health abnormalities, and the health status of companion animals with communication limitations can be diagnosed from the color and shape of the stool. It is necessary to seek medical attention and make an accurate diagnosis. For an accurate diagnosis, the owner shows a picture of the pet's feces to a veterinary hospital specialist or takes a defecation pad to the doctor. For example, during the first week of life, the condition of the stool changes every day, and after 5 days after birth, golden stool is excreted from breast milk, and after a week, the condition of the stool changes to yellow or brown depending on whether the child is breastfed, black stool or black stool. If you have gray stools, you should bring a stool pad with the stool to your doctor. However, it is difficult to determine whether the owner should visit the hospital by looking at the state of the stool containing a lot of health information, and it is also inconvenient to bring a bowel movement pad to the hospital.

Diagnosis technology using machine learning technology is developing, and the companion animal health diagnosis market is rapidly growing due to the development of artificial intelligence technology. Until now, most of the services that diagnose using the information collected using sensors are (ECG, oxygen level, nearby fine dust, body temperature, etc.). As the use of artificial neural networks such as CNNs increases, the technology for analyzing medical information through images is also advancing. The number of use cases for radiologists to diagnose through machine learning-based MRI/CT analysis technology is increasing, and the popularization of medical diagnostic services is accelerating.

It is possible to diagnose a companion animal's health condition by "analyzing the feces image", and according to an embodiment of the present invention, a feces containing companion animal health diagnosis information is photographed, and the photographed image is analyzed with deep learning technology to enable a specialist Preliminary and supportive pet health-related information may be provided prior to judgment. In a situation in which the smart defecation pad market is also expanding, and services that combine creative IT technology with traditional defecation pads are being launched one after another, if a diagnostic service is launched without a separate sensor from feces directly related to companion animal health, it is the right time for treatment. You can connect the owner and the veterinary hospital.

A classification system for diagnosing defecation pad stool can be established. There is a medical classification system called the Bristol stool scale that diagnoses health conditions such as chronic gastrointestinal disease through the shape and color of adult stool. The shape and color of the stool of companion animals changes depending on the number of days of birth and whether or not breastfeeding, and the digestive ability is incomplete during the formation of teeth and digestive organs. It is important to provide information to the owner. In the initial implementation stage, it is necessary to start by providing simple information such as whether there is an abnormality, but as the solution perfection increases, it is possible to build a classification system suitable for deep learning-based image processing technology by securing a large amount of images.

It is possible to provide an advanced solution from 'Monit''s smart toilet pad alarm. In 2016, Monit, a startup affiliated with Samsung Electronics' in-house venture program 'C-LAB', launched a service that alerts you to defecation using a 'sensor that observes the inside of a toilet pad in real time' as a result of research and development for about a year. It achieved sales of 1.2 billion won by launching a joint product with Kimberly. A service such as monit is currently a method of attaching a sensor to a defecation pad, but there is no service that utilizes health information obtained from the stool state so far, and according to an embodiment of the present invention, It is judged that it will be possible to secure a new market in the companion animal health market by implementing a solution for preliminary diagnosis.

It can provide a health information guide that can be checked through the feces of companion animals, and based on information about companion animals such as the number of months after birth, as well as analysis of the stool image of the defecation pad, information necessary for parenting is provided in a form suitable for the companion animal. can provide For example, it can provide information such as food suitable for the number of months, how to train a toilet habit, and how to learn the senses. It is possible to continuously monitor the health status of companion animals by acquiring an image of companion animal feces and tracking the history.

The veterinary hospital treatment process can be streamlined according to the circumstances and needs. By analyzing the image of companion animal feces, the owner can identify whether the animal hospital is in a condition that requires treatment, and if treatment is needed, it can be connected to a nearby hospital reservation service to promote prompt treatment. It is possible to provide the information necessary for an accurate diagnosis by providing the results of stool pad stool imaging during hospital diagnosis.

It is possible to implement an application for securing the defecation pad stool image. A defecation pad stool imaging application can be provided to secure sample images for training, and as a step before upgrading the diagnostic result solution, an application for pre-processing to a trainingable standard can be implemented if the stool on the defecation pad is photographed. have. According to a 2019 paper on classification of stool images (Augmenting Gastrointestinal Health: A Deep Learning Approach to Human Stool Recognition and Characterization in Macroscopic Images, https://arxiv.org/ftp/arxiv/papers/1903/1903.10578.pdf), 650 When training several images, the accuracy of the identification and classification model is about 70% or more, and when training 25200 images, an accuracy of 99.4% can be secured. According to an embodiment of the present invention, it is possible to implement an application for securing a training sample.

The secured defecation pad stool image can be labeled. Labeling of images obtained by recruiting two veterinary hospital specialists can be performed, and three classification models of constipation/normal/diarrhea can be constructed preferentially.

SegNet and ResNet can be trained based on labeled images. First, 500 training images can be labeled, and based on the labeled training images, a model to identify stool shapes can be trained with SegNet. <SegNet architecture, SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation> It is possible to train a model that performs color-based classification using ResNet on stools identified based on SegNet. <Network architectures for ImageNet, Deep Residual Learning for Image Recognition>

A defecation pad stool image-based diagnostic solution can be implemented. By utilizing SegNet and ResNet that have learned the labeled image, a defecation pad stool image analysis solution can be implemented.

By utilizing a toilet pad with "color code" attached, an application with image distortion correction function can be implemented. Distortion problems may occur due to image conditions that change depending on the shooting environment or the specifications of the image sensor. This can increase the accuracy of diagnosis. When the learning of SegNet and ResNet is completed, it is possible to attract investment while developing a business model using "color code" through collaboration with a toilet pad company. In this process, VC investment can also be attracted.

Business models can be upgraded through VC investment attraction and cloud funding. By attracting seed investment, you can increase capital, perform team building, and link accelerating. Cloud funding can promote service and generate revenue.

Figure 3 is a view for explaining a bowel movement pad is attached to the color code according to an embodiment.

First, referring to Figure 3 (a), the design and manufacture of a patch for the stool image analysis of the defecation pad can be made. A material and a printing method for making a patch may be selected.

Referring to (b) of Figure 3, a model design and production for securing a bowel movement pad stool image can be made. Classification and production of basic cases for model production can be requested.

In securing and labeling patch-applied stool image, setting for securing image including patch and labeling for each image may be performed.

Upon completion of securing images of defecation pad stool images and securing images in the stool classification app, an image processing app may be provided for selecting a patch with high processing performance by testing the images, and extracting features based on the selected patch.

According to an embodiment, transformation using CCM is made, and the A matrix in the following equation is called CCM. The CCM conversion formula is as follows.

The transformation method using CCM is a method using a filter that performs matrix operation, which is the core of digital image processing techniques. A filter may be provided according to each purpose, for example, mosaic, blur, noise removal, and the like. The algorithm can provide a filter that recognizes the difference between patches and minimizes the difference.

Referring to Figure 3 (c), the color code is attached to the original image and the resulting image of the toilet pad.

According to an embodiment, the transformation is performed using a Linear Regressor. The Linear Regressor formula is as follows.

Among machine learning, supervised learning consists of classification and regression. Regression returns predicted results for input data. In this algorithm, if a photographed patch color is input, a result close to the original patch color is returned. The formula for applying the algorithm is as follows.

The cost function of the machine learning Linear Regressor model is MSE (refer to the formula below) to obtain b0, b1, b2, and b3, and then applies it to all pixels.

Referring to Figure 3 (d), the color code is attached to the original image and the resulting image of the toilet pad.

The formula used in the MSE evaluation method is as follows.

MSE is an abbreviation for mean square error, and is an expression of the distance (difference) between the two data numerically by using the RGB data between the original image patch and the patch image as a result of a specific algorithm.

When comparing the original image and the converted image with MSE, the patch with 4 colors obtained the best result according to the MSE evaluation criteria, but it can be seen that the actual application results in ruining the surrounding image, and in the case of other patches, the 3x5 patch ( Patch 1) showed good performance in CCM, and patch 3x4 (Patch 2) showed good performance in linear regressor.

The embodiments described above may be implemented by a hardware component, a software component, and/or a combination of a hardware component and a software component. For example, the apparatus, methods, and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate (FPGA) array), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions, may be implemented using one or more general purpose or special purpose computers. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. A processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that can include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and available to those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic such as floppy disks. - includes magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

Software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be any kind of machine, component, physical device, virtual equipment, computer storage medium or apparatus, to be interpreted by or to provide instructions or data to the processing device. , or may be permanently or temporarily embody in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

As described above, although the embodiments have been described with reference to the limited drawings, those skilled in the art may apply various technical modifications and variations based on the above. For example, the described techniques are performed in an order different from the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (1)

color code affixed to one side; and
a pad for receiving the stool object;
The color code is characterized in that it consists of colors that are a standard for judging the state of the stool object,
Color-coded toilet pad.

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