KR101880937B1 - System and method for diagnosing companion animal - Google Patents

Abstract

The present invention relates to a companion animal diagnostic system and method. The system according to the present invention measures a body weight applied to each leg of a companion animal using a plurality of sensors, provides intrinsic characteristic information of the companion animal and the measured weight information to a diagnostic server, A measurement device for requesting diagnosis of abnormality symptom, and a device for recognizing intrinsic characteristic information and weight information of the companion animal provided from the measurement device at the request of the measurement device and analyzing abnormality symptom statistics And a diagnosis server for extracting abnormality symptom statistical data corresponding to the companion animal from the database storing the data and diagnosing an abnormal symptom according to the weight distribution of the companion animal.

Description

[0001] SYSTEM AND METHOD FOR DIAGNOSING COMPANY ANIMAL [0002]

The present invention relates to a companion animal diagnostic system and method, which measures the weight applied to a leg of a companion animal through a sensor, measures the weight of the companion animal weight To a veterinarian and / or a user, and to provide a veterinary surgeon and / or a user with an abnormality symptom detection result and related information by detecting a musculoskeletal abnormality symptom corresponding to an unbalanced state.

Companion animals are likely to suffer from musculoskeletal-related diseases as their weight is unevenly distributed because they walk or run on all four feet.

At the present veterinary clinic, there was no way to measure the weight balance of the weight on the legs of the companion animals, and the weight measurement of the companion animals and the visual evaluation of the veterinarians were carried out using a general scale.

If an anomaly of a companion animal can not be diagnosed by the first-aid provider, second- and third-level medical institutions may seek out musculoskeletal disorders through expensive medical equipment such as X-ray, CT or MRI And the diagnosis is made based on the results, so that the burden of the medical expenses is incurred to the owner of the companion animal.

Therefore, countermeasures should be prepared to measure the weight balance of companion animals for early prevention and prompt action in knee dislocation, hip joint disorder, disc disease, etc. in the musculoskeletal system of companion animals.

Korean Patent Publication No. 10-2015-0133978 (published on December 1, 2015) Korean Registered Patent No. 10-0414692 (registered on December 27, 2003)

An object of the present invention is to provide a method for measuring the weight of each animal applied to a leg of a companion animal through a sensor and measuring the weight of the companion animal on the basis of the weight information and the information of the companion animal, The present invention provides a system for managing musculoskeletal disorders of a companion animal by providing a manager and / or a user with an abnormal symptom detection result and prognostic information related thereto by detecting an abnormal symptom of a musculoskeletal system according to an unbalanced state of a body weight to be dispersed, Diagnostic system and method.

In order to accomplish the above object, the present invention provides a companion animal diagnostic system comprising: a plurality of sensors for measuring a body weight applied to each leg of a companion animal; To the diagnostic server to request diagnosis of abnormality symptoms of the companion animal, and a method of recognizing the characteristic information and the weight information of the companion animal provided from the measurement device at the request of the measurement device, And a diagnosis server for extracting abnormal symptom statistical data corresponding to the companion animal from a database storing abnormality symptom statistical data according to intrinsic characteristics of the companion animals and diagnosing an abnormal symptom according to the weight distribution of the companion animal .

The measurement device includes a measurement unit for measuring the body weight applied to the legs of the companion animal placed on each sensor using the plurality of sensors, an interface for receiving characteristic information on the species, sex and age of the companion animal Comprising: a communication unit for supporting a communication interface between the measurement device and the diagnosis server in a wireless communication manner; and a companion animal measurement unit for collecting characteristic information of the companion animal and weight information of each companion animal And transmitting the generated companion animal measurement data to the diagnosis server through the communication unit.

The weight information includes respective weight information applied to the legs of the companion animal measured by the plurality of sensors and position information of the sensor measuring each weight information.

When the legs of the companion animal are placed on each of the sensors, the plurality of sensors detect the deformation amount of the weight measuring device as an electric signal, and the legs of the companion animal And measures the body weight to be applied.

Wherein the measuring unit includes a body panel for allowing the companion animal to stand on its body for measuring body weight, and a body panel disposed in the vicinity of the body panel in a direction perpendicular to the body panel to measure the body weight of the companion animal, And a safety panel for blocking movement.

The plurality of sensors are disposed at a lower end of the body panel so as to be spaced apart from each other.

Wherein the diagnosis server comprises: a communication unit for receiving the companion animal measurement data from the measurement device and transmitting diagnosis results of the companion animal to a predetermined terminal device; A database including a learning DB storing abnormality symptom statistics data of the musculoskeletal system, a diagnosis DB storing diagnosis results of the companion animals based on abnormality symptom statistical data extracted from the learning DB, Extracting abnormality symptom statistical data stored in the learning DB by using intrinsic characteristic information of the companion animal and analyzing information of the companion animal included in the extracted abnormality statistical data and the companion animal measurement data and weight information, The weight balance of the weight applied to the leg of the companion animal is determined It characterized by a controller for predicting and diagnosing musculoskeletal abnormalities of the group for a companion animal.

The control unit learns the physical condition of the companion animals according to the species, sex, and age through the big data mining for the companion animals, and calculates the weight of the companion animals according to the species, sex and age of the companion animals A learning module for generating an abnormal symptom statistical data by predicting a correlation and a dependence relationship between the balance and the musculoskeletal diseases, a weight balance value for the weight applied to the leg of the corresponding companion animal is derived from the abnormal symptom statistical data, An analysis module for analyzing each weight value applied to an animal's legs to determine a weight balance state with respect to a weight applied to each leg of the companion animal; and an analysis module for determining the weight balance state of the companion animal, Extraction of abnormal ranges and deviations of the variance and extraction of musculoskeletal disorders predicted due to the weight imbalance of the companion animals And in that it comprises the diagnostic module of claim.

Wherein the diagnosis module extracts prognostic information corresponding to a musculoskeletal disease predicted as a diagnosis result of the companion animal and transmits the diagnosis result and prognostic information corresponding thereto to a predetermined terminal device through the communication unit do.

The terminal device is at least one of a terminal device of an administrator previously registered corresponding to the measurement device and a terminal device of a user registered in advance in correspondence with the companion animal.

The terminal device may be configured to install a companion animal healthcare program provided by the diagnosis server in advance and to transmit diagnosis results of the companion animal received from the diagnosis server and prognostic information corresponding thereto to an execution screen of the companion animal healthcare program On the display unit.

According to another aspect of the present invention, there is provided a method for diagnosing companion animals, comprising the steps of measuring a body weight applied to each leg of a companion animal using a plurality of sensors, Providing the diagnostic server with intrinsic characteristic information of the companion animal and the measured weight information to request diagnosis of an abnormal symptom of the companion animal; Extracting abnormality symptom data corresponding to the companion animal from a database storing abnormality symptom statistical data according to intrinsic characteristics of companion animals previously learned by the diagnosis server, And the diagnosis server transmits the extracted abnormality symptom statistical data and the weight information obtained for the companion animal Use will be characterized by including the step of diagnosing the abnormality in accordance with the weight distribution of the companion animal.

According to another aspect of the present invention, there is provided a method for diagnosing companion animals, comprising the steps of: extracting prognostic information corresponding to a musculoskeletal disease predicted as a diagnosis result of the companion animal; And transmitting the prognostic information corresponding to the prognostic information to the predetermined terminal device.

The method of diagnosing companion animals according to an embodiment of the present invention may further include the steps of: executing the companion animal health care program provided in advance by the terminal device in the diagnosis server; and diagnosing the companion animal And displaying the diagnostic result of the companion animal and the corresponding prognostic information on the execution screen of the companion animal healthcare program when the result and the corresponding prognostic information are received.

According to the embodiments of the present invention, the weight of each animal applied to the legs of the companion animal is measured through the sensor, and based on the weight information and the information of the companion animal applied to the legs of the companion animal at the server, The user is able to systematically manage the musculoskeletal disorders of the companion animal by providing the administrator and / or the user with the result of the abnormality detection and the prognostic information related thereto, by detecting the abnormality of the musculoskeletal system according to the unbalanced state of the body have.

FIG. 1 is a diagram illustrating a configuration of a companion animal diagnostic system according to an embodiment of the present invention.
FIG. 2 is a view showing a detailed configuration of the measuring apparatus of FIG. 1; FIG.
3 is a diagram showing a detailed configuration of the diagnosis server of FIG.
4 is a diagram showing an embodiment to be referred to in describing the operation of the diagnosis server of FIG.
FIG. 5 is a view showing an embodiment of providing diagnostic results by the companion animal diagnostic system according to an embodiment of the present invention.
FIGS. 6 and 7 are diagrams illustrating an operation flow for a companion animal diagnostic method according to an embodiment of the present invention.

It is noted that the technical terms used in the present invention are used only to describe specific embodiments and are not intended to limit the present invention. In addition, the technical terms used in the present invention should be construed in a sense generally understood by a person having ordinary skill in the art to which the present invention belongs, unless otherwise defined in the present invention, and an overly comprehensive It should not be construed as meaning or overly reduced. In addition, when a technical term used in the present invention is an erroneous technical term that does not accurately express the concept of the present invention, it should be understood that technical terms that can be understood by a person skilled in the art can be properly understood. In addition, the general terms used in the present invention should be interpreted according to a predefined or context, and should not be construed as being excessively reduced.

Furthermore, the singular expressions used in the present invention include plural expressions unless the context clearly dictates otherwise. The term "comprising" or "comprising" or the like in the present invention should not be construed as necessarily including the various elements or steps described in the invention, Or may include additional components or steps.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description, a detailed description of related arts will be omitted. do. It is to be noted that the accompanying drawings are only for the purpose of facilitating understanding of the present invention and should not be construed as limiting the scope of the present invention.

A companion animal with four legs, such as a dog or cat, is divided into four legs. Depending on the companion animal, the weight dispersed to the forelegs and the hind legs may be different, but when the center of gravity of the companion animal is disturbed, a large amount of weight may be applied to a particular leg, resulting in an abnormality in the musculoskeletal system of the companion animal .

Accordingly, the present invention provides a companion animal diagnostic system for measuring the body weight applied to each leg of a companion animal and analyzing the weight to diagnose a musculoskeletal abnormality symptom of a companion animal.

FIG. 1 is a diagram illustrating a configuration of a companion animal diagnostic system according to an embodiment of the present invention. Referring to FIG. 1, the companion animal diagnostic system of the present invention may include a measurement device 100 and a diagnostic server.

First, the measuring apparatus 100 includes a measuring unit 110 having a plurality of sensors for measuring the body weight applied to each leg of the companion animal.

Here, the number of sensors is not limited to any one, but an example in which four sensors are provided on the basis of a companion animal having four legs, such as a dog or a cat, in which a musculoskeletal system abnormality may frequently occur will be described.

Companion animals can stand on four sensors. At this time, each sensor measures the weight applied to the leg of the companion animal placed on the sensor.

The measuring device 100 converts the weight value applied to each leg of the companion animal measured by the four sensors into a digital signal and outputs the weight information including the converted weight value and the position value of the sensor measuring the weight value And the companion animal measurement data including the information of the companion animal input by the administrator, for example, the veterinary surgeon, to the diagnosis server 200. The measurement apparatus 100 may transmit the companion animal measurement data to the terminal apparatus 310 of the administrator registered in advance.

Here, the information of the companion animal input by the administrator may include information such as the species, sex, and age of the companion animal, and may include the physical condition information observed by the companion animal.

The diagnosis server 200 learns the physical condition according to the species, sex, age, etc. of the companion animal, and uses a decision algorithm that predicts the correlation between the balance of the body weight dispersed in each leg of the companion animal and the relationship and dependence of the musculoskeletal diseases A decision element, a decision tree pattern, and the like can be extracted. Also, the diagnostic server 200 generates abnormal symptom statistical data according to the species, sex, age, etc. of each companion animal through the learning result.

The diagnosis server 200 stores data on the physical condition learning result of the companion animals according to the species, sex, age, and the like, and abnormality symptom statistical data according to the learning results in the database (DB). The data stored in the database can be used to analyze and diagnose abnormal musculoskeletal symptoms in companion animals.

On the other hand, when the diagnostic server 200 receives the companion animal measurement data from the measurement apparatus 100, the diagnostic server 200 grasps the companion animal information through the received companion animal measurement data. At this time, the diagnostic server 200 calls the DB storing the abnormality symptom data of the musculoskeletal system according to the species, sex, age and the like of the companion animal and outputs the companion animal measurement data And information corresponding to the species, sex, and age of the companion animal identified through the search.

In addition, the diagnosis server 200 grasps the weight applied to each leg of the companion animal based on the weight information included in the companion animal measurement data. At this time, the diagnostic server 200 analyzes information extracted from the DB in accordance with the species, sex, and age of the companion animal from the body weight applied to each leg of the companion animal obtained from the companion animal measurement data, Abnormal symptoms can be predicted and diagnosed.

The diagnostic server 200 transmits the diagnostic result of the abnormal symptom of the companion animal based on the companion animal measurement data to the measurement apparatus 100. [ Here, the diagnostic server 200 can transmit and receive signals to and from the measurement apparatus 100 using a wireless communication method such as WiFi and Bluetooth.

1, the diagnostic server 200 is communicatively coupled to one measurement device 100, but it is to be understood that the diagnostic server 200 may be connected to a plurality of the measurement devices 100. FIG.

On the other hand, the diagnosis server 200 may transmit the diagnosis result and / or the prognosis information according to the diagnosis result to the terminal device 310 of the administrator registered in advance in correspondence with the measuring apparatus 100. Of course, if the user information is registered in advance with respect to the corresponding companion animal, the diagnostic server 200 transmits the diagnosis result and / or the prognosis information for the companion animal to the terminal device 350 of the registered user in advance It is possible.

The terminal 300 of the administrator and / or the user can receive and display the diagnostic result of the companion animal and the prognostic information therefrom from the diagnostic server 200.

The terminal device 300 can be installed with a program provided by the diagnostic server 200 and can display the diagnostic result and / or the prognostic information provided from the diagnostic server 200 through the execution screen of the preinstalled program have.

Here, the terminal device 300 may be a device including a communication function. For example, the terminal device may be a smartphone, a tablet personal computer, a mobile phone, a videophone, an e-book reader, a desktop PC, a laptop PC a laptop PC, a netbook computer, a personal digital assistant (PDA), a portable multimedia player (PMP), and a smart watch.

FIG. 2 is a view showing a detailed configuration of the measuring apparatus of FIG. 1; FIG. 2, the measuring apparatus 100 according to an embodiment may include a measuring unit 110, an interface unit 120, a storage unit 130, a communication unit 140, and a signal processing unit 150 . Here, the signal processing unit 150 may process signals transmitted between the respective units of the measurement apparatus 100.

The measurement unit 110 includes four sensors 111, 112, 113, and 114 for measuring the body weight applied to each leg of the companion animal, for example, a first sensor 111, a second sensor 112, (114).

Here, the first to fourth sensors 111 to 114 may include a load cell as a weight measuring device. When the weight of the load cell is received, a weight is measured by detecting an amount of deformation of a coil or a spring, do.

The first to fourth sensors 111 to 114 may be disposed apart from each other at the lower end of the body panel 115 where the companion animal can stand and stand. Here, the first sensor to the fourth sensor 111 to 114 may be arranged based on the four foot positions of the companion animal. The second sensor 112 is the right forefoot of the companion animal, the third sensor 113 is the left hind leg of the companion animal, and the fourth sensor 114 is the left front leg of the companion animal, The right hind paw of the companion animal can be placed. Here, it is assumed that the first to fourth sensors 111 to 114 simultaneously measure the body weight applied to each leg in a state in which the companion animal does not stand and move.

In addition, a safety panel 116 is disposed around the body panel 115 to prevent the companion animal from moving or falling out on the body panel 115 while measuring the weight of each animal applied to the legs of the companion animal. . Here, the safety panel 116 may be positioned around the body panel 115 so as to be perpendicular to the body panel 115.

When the body weight applied to each leg of the companion animal is measured by the first to fourth sensors 111 to 114, the measuring unit 110 measures the four weight values measured by the respective sensors to the signal processing unit 150 . Here, the measuring unit 110 may be implemented outside the measuring apparatus 100. In this case, the measuring unit 110 may transmit the four weight values measured by the respective sensors to the signal processing unit 150 using a wired or wireless communication system.

The signal processing unit 150 stores the four weight values transmitted from the measuring unit 110 in the storage unit 130. At this time, the signal processor 150 may store the four weight values in the storage unit 130 so that the position values of the sensors measuring the respective weight values correspond to each other.

The interface unit 120 may include input means for receiving a predetermined signal from an administrator. The input means receives the information of the companion animal from the manager. For example, the input means may receive information such as the species, sex, and age of the companion animal from the manager and transmit the information to the signal processing unit 150. Further, the input means may receive the body condition information, for example, the walking state, the obstacle state, etc., observed by the companion animal, and may transmit the input to the signal processing unit 150. The physical condition information of the companion animal may be information in a text format input by an administrator, but may be information in an image or a moving picture format. At this time, the signal processing unit 150 may store the companion animal information transmitted from the input means in the storage unit 130.

Here, the input means may be a keypad having a plurality of key buttons, or may be a soft key implemented on the screen of the touch screen. The input means may be a mouse, a joystick, a jog shuttle, a stylus pen, or the like.

In addition, the interface may include output means for outputting the operation state and result of the measurement apparatus 100, and the like. The outputting means may include a display for displaying a weight value measured by the measuring unit 110, information of the companion animal inputted by the manager, a diagnosis result received from the diagnosis server 200, and the like.

Here, the display may be implemented by integrating the input means and the output means when operated with a touch screen when a sensor for sensing the touch operation is provided.

The display may be a liquid crystal display (LCD), a thin film transistor liquid crystal display (TFT LCD), an organic light-emitting diode (OLED), a flexible display, , A field emission display (FED), and a 3D display (3D display).

If there is a diagnosis request by the administrator, the signal processing unit 150 stores weight information including four weight values stored in the storage unit 130 and a position value of the sensor measuring the weight value, And transmits the generated companion animal measurement data to the diagnosis server 200 through the communication unit 140. [0050]

When the diagnosis result and the prognostic information are received from the diagnostic server 200 through the communication unit 140, the signal processor 150 stores the received diagnosis result and the prognostic information in the storage unit 130, Display can be made to be displayed.

Here, the communication unit 140 may include a communication module (not shown) supporting a communication interface for wireless communication with the diagnostic server 200 and the terminal unit 310 of the administrator.

The communication module may include a module for wireless Internet communication or a module for short range communication. Wireless Internet communication technologies may include a wireless LAN (WLAN), a wireless broadband, a wi-fi, and a wi-fi. The short range communication technology may include Bluetooth, ZigBee, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), and the like.

The measuring apparatus 100 according to the present embodiment may correspond to at least one processor or may include at least one or more processors. Accordingly, the measurement apparatus 100 can be implemented as an independent hardware device. Alternatively, the measurement device 100 may be implemented in a form embedded in other hardware devices such as a microprocessor or a general purpose computer system. For example, the measurement apparatus 100 may be implemented as a processor included in the terminal device 310 of the administrator.

3 is a diagram showing a detailed configuration of the diagnosis server of FIG. Referring to FIG. 3, the diagnostic server 200 may include a communication unit 210, a database (DB) 220, and a controller 230.

The communication unit 210 may include a communication module that supports a communication interface for wireless communication with the measurement device 100, an administrator, and / or a terminal device of a user.

The communication module may include a module for wireless Internet communication or a module for short range communication. Wireless Internet communication technologies may include a wireless LAN (WLAN), a wireless broadband, a wi-fi, and a wi-fi. The short range communication technology may include Bluetooth, ZigBee, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), and the like.

The DB 220 may store data and algorithms necessary for the diagnostic server 200 to operate. Also, the DB 220 may store learning data and diagnostic result data of the diagnosis server 200 and the like.

Here, the DB 220 may include a learning DB 221 and a diagnostic DB 225. The learning DB 221 may store a decision algorithm for the diagnosis server 200 to learn and determine the physical condition according to the species, sex, age, etc. of the companion animal. Also, the learning DB 221 can store abnormal symptom statistical data extracted as a learning result on the physical condition according to species, sex, age, etc. of the companion animal. In addition, the learning DB 221 may store decision factors and decision tree pattern information extracted as a learning result on the physical condition according to species, sex, age, etc. of the companion animal.

Diagnostic DB 225 may store diagnostic algorithms for analyzing and diagnosing abnormalities of the musculoskeletal system due to the species, sex, age, and weight applied to each leg of the companion animal.

In addition, the diagnostic DB 225 stores the companion animal measurement data received from the measurement apparatus 100, and the diagnostic result data on the musculoskeletal abnormality indications of the companion animal can be stored based on the companion animal measurement data.

The control unit 230 may include a learning module 231, an analysis module 233, and a diagnostic module 235.

The learning module 231 collects information on the companion animal and performs a decision algorithm based on the collected information to learn the physical condition of the companion animal according to the species, sex, and age.

For example, the learning module 231 learns the physical condition of the companion animals according to the species, sex, and age through the big data mining of the companion animals. Based on the results, And the relationship between weight balance and musculoskeletal disorders. At this time, the learning module 231 may extract a decision factor and a decision tree pattern based on the prediction result, and apply it to the decision algorithm.

For example, the decision tree for the 'Dachshund' varieties can be represented as in FIG. In the decision tree shown in FIG. 4, A_1, A_2, ..., A_M corresponding to the reference value may correspond to anomalous indications depending on the sex and age of the 'Dachshund' variety, and B_1 , B_2, ..., B_N may be musculoskeletal disorders that can occur due to abnormal symptoms.

Also, the learning module 231 generates abnormal musculoskeletal symptom data according to the species, sex, age, etc. of the companion animals from the learning results of the physical condition according to the species, sex, and age of the companion animals. The generated abnormality symptom statistical data is stored in the learning DB 221. Here, the abnormal symptom statistical data may include weight balance information distributed to each leg according to the species, sex, and age of the companion animal, musculoskeletal diseases caused by weight unbalance distributed to each leg, and corresponding prognostic information .

Analysis module 233 can receive the companion animal information and the weight information of the companion animal from the received companion animal measurement data when the companion animal measurement data from the measuring device 100 is received through the communication unit 210. [

In addition, the analysis module 233 extracts anomalous symptom statistical data corresponding to the information of the corresponding companion animal from the learning DB 221 based on companion animal information obtained from the companion animal measurement data, for example, species, sex, .

At this time, the analysis module 233 analyzes the anomaly statistics data extracted from the learning DB 221 and the body weight information of the companion animal, for example, the weight value applied to each leg of the companion animal, The weight balance state with respect to the weight applied to each leg of the companion animal can be determined.

For example, the analysis module 233 may analyze the anomalous symptom statistical data extracted from the learning DB 221 and derive a weight balance value with respect to the weight applied to the four legs of the companion animal. In addition, the analysis module 233 compares the weight information included in the companion animal measurement data, that is, the weight value applied to each leg of the actual companion animal with the weight balance value derived from the previous companion animal, The weight balance state can be determined.

The analysis module 233 may store the result of the determination of the balance state of the companion animal in the diagnosis DB 225 and provide the result to the diagnostic module 235. [

The diagnosis module 235 can predict and diagnose an abnormality of the musculoskeletal system for the companion animal based on the determination result of the analysis module 233. [

In other words, if the analysis module 233 determines that the weight applied to each leg of the companion animal by the analysis module 233 is a weight unbalance state, the weight balance value for the weight applied to the four legs of the companion animal The abnormal range and deviation of the weight distribution of the corresponding companion animal can be extracted. In addition, the diagnostic module 235 can diagnose the musculoskeletal diseases predicted due to the weight unbalance of the companion animals from the abnormal symptom statistical data extracted based on the species, sex, and age of the companion animals.

When the diagnosis of the companion animal is completed, the diagnostic module 235 obtains prognostic information corresponding to the musculoskeletal disease predicted for the companion animal from the abnormal symptom statistical data extracted based on the species, sex and age of the companion animal Can be extracted.

The diagnostic module 235 may send the diagnosis result and / or the prognostic information corresponding to the abnormal symptom of the musculoskeletal system to the corresponding companion animal to the measurement device 100, the terminal device of the registered manager corresponding to the measurement device 100 310 and the terminal device 350 of the registered user corresponding to the companion animal.

Accordingly, the measurement apparatus 100, the administrator or the user's terminal device 300 provides the diagnosis result and / or the prognostic information received from the diagnosis server 200 through the display.

FIG. 5 is a view showing an embodiment for providing diagnostic results by the companion animal diagnostic system according to an embodiment of the present invention.

The terminal 300 of the administrator or the user can install the companion animal healthcare program provided by the diagnosis server 200. At this time, the terminal device 300 can access the diagnostic server 200 while the companion animal healthcare program is running, receives the healthcare information of the companion animal provided from the diagnostic server 200, Can be displayed.

As an example, the terminal device 300 of the administrator or the user receives the diagnosis result and / or the corresponding prognosis information provided from the diagnosis server 200 based on the weight applied to each leg of the companion animal, As shown, it can be displayed on the execution screen of the companion animal healthcare program.

The operation flow of the companion animal diagnostic system configured as above will be described in more detail as follows.

FIGS. 6 and 7 are diagrams illustrating an operation flow for a companion animal diagnostic method according to an embodiment of the present invention.

6 illustrates a method of operation of a measurement apparatus according to an embodiment of the present invention. Referring to FIG. 6, the measuring apparatus 100 measures the weight applied to each leg of the companion animal using four sensors (S110). When the information of the corresponding companion animal, for example, species, sex, age, and the like, is input, the measuring apparatus 100 compares the companion animal measurement data including the input companion animal information and the weight information applied to each leg And transmits it to the diagnosis server (S130).

Meanwhile, FIG. 7 illustrates a method of operating a diagnostic server according to an embodiment of the present invention. Referring to FIG. 7, the diagnostic server 200 learns the physical condition of the companion animals according to the species, sex, and age (S210). Based on the learning result of the 'S210' (S220). ≪ / RTI >

Thereafter, when the companion animal measurement data is received from the measurement apparatus 100 (S230), the diagnostic server 200 determines the species, sex, and age of the companion animal to be diagnosed from the information contained in the received companion animal measurement data , The weight information of the corresponding companion animal, that is, the weight value applied to each leg is determined (S240).

The diagnostic server 200 extracts abnormal symptom statistical data generated in step S220 based on the species, sex, and age of the companion animal identified in step S240 (S250).

The diagnostic server 200 analyzes the weight value applied to each leg of the companion animal identified in the process of 'S240' based on the anomalous symptom statistical data extracted in the process of 'S250' (S260).

If it is determined in step S260 that the weight applied to each leg of the companion animal is in a weight unbalance state, the diagnostic server 200 extracts the musculoskeletal disease predicted by the weight unbalance of the companion animal from the anomaly data previously extracted (S270).

When the diagnosis of the companion animal is completed, the diagnosis server 200 may extract the diagnosis result and the prognostic information corresponding thereto and transmit the diagnosis result and the prognostic information to the measurement apparatus 100, the administrator, or the terminal device 300 of the user (S280).

The above processes may be implemented directly in hardware, software modules executed by a processor, or a combination of the two. The software modules may reside in storage media, such as memory and / or storage, such as RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs. An exemplary storage medium is coupled to the processor, which is capable of reading information from, and writing information to, the storage medium. Alternatively, the storage medium may be integral with the processor. The processor and the storage medium may reside within an application specific integrated circuit (ASIC). The ASIC may reside within the user terminal. Alternatively, the processor and the storage medium may reside as discrete components in a user terminal.

As described above, the present invention has been described with reference to particular embodiments, such as specific elements, and specific embodiments and drawings. However, it should be understood that the present invention is not limited to the above- Those skilled in the art will appreciate that various modifications, additions and substitutions are possible, without departing from the essential characteristics of the invention. Therefore, the spirit of the present invention should not be construed as being limited to the embodiments described, and all technical ideas which are equivalent to or equivalent to the claims of the present invention are included in the scope of the present invention .

100: measuring device 110: measuring part
111: first sensor 112: second sensor
113: third sensor 114: fourth sensor
115: body panel 116: safety panel
120: interface unit 130: storage unit
140: communication unit 150: signal processing unit
200: Diagnosis server 210:
220: Database (DB) 221: Learning DB
225: diagnosis DB 230:
231: learning module 233: analysis module
235: Diagnostic module 300: Terminal device
310: administrator terminal device 350: user terminal device

Claims (14)

Measuring a body weight applied to each leg of the companion animal by using a plurality of sensors and providing the diagnostic server with intrinsic characteristic information of the companion animal and the measured weight information to request diagnosis of the abnormality symptom of the companion animal Device; And
Wherein the measuring device is adapted to receive information on the intrinsic characteristics and weight information of the companion animal provided from the measuring device and to receive information on the companion animal from a database storing abnormality symptom statistical data according to intrinsic characteristics of the companion animals learned in advance And a diagnosis server for extracting abnormality symptom statistical data and diagnosing an abnormal symptom according to the weight distribution of the companion animal,
The diagnostic server,
A communication unit for receiving the companion animal measurement data from the measurement device and transmitting the diagnosis result to the terminal device;
A learning DB storing statistical data of an anomalous musculoskeletal symptom according to a characteristic of a species of a companion animal learned beforehand and a sex specific age and a diagnosis result for the companion animal based on anomalous symptom statistical data extracted from the learning database A database containing diagnostic DBs; And
Extracting abnormal symptom statistical data stored in the learning DB using the intrinsic characteristic information of the companion animal obtained from the companion animal measurement data and extracting the abnormal symptom statistical data from the extracted animal symptom statistical data and the companion animal data included in the companion animal measurement data And a controller for analyzing information and weight information to determine a weight balance state of the weight applied to the legs of the companion animal to predict and diagnose an abnormality of the musculoskeletal system with respect to the companion animal,
Wherein,
The data of the companion animals were analyzed by big data mining on the animal species, sex and age. The results showed that the balance of body weight distributed to each leg according to species, sex and age of companion animals and musculoskeletal diseases A learning module for predicting a correlation and a dependence relationship between the prediction error and the prediction error, extracting a decision factor and a decision tree pattern based on the prediction result, and applying the decision factor to a decision algorithm to generate anomaly statistics data;
From the abnormal symptom statistical data, a weight balance value with respect to the weight applied to the legs of the companion animals is derived, and the weight values applied to the legs of the companion animals are analyzed to determine the body weight An analysis module for determining a balance state of the weight of the object; And
And a diagnosis module for extracting an ideal range and a deviation of body weight dispersion of the companion animal when the companion animal is in a weight unbalanced state and diagnosing a musculoskeletal disease predicted due to a weight unbalance of the companion animal,
The diagnostic module includes:
Wherein the prognostic information corresponding to a musculoskeletal disease predicted as a diagnosis result of the companion animal is extracted and the diagnosis result and the prognostic information corresponding thereto are transmitted to the predetermined terminal device through the communication unit .
The method according to claim 1,
The measuring device includes:
A measuring unit for measuring the body weight applied to the legs of the companion animals placed on the respective sensors using the plurality of sensors,
An interface unit for receiving intrinsic characteristic information on the species, sex and age of the companion animal;
A communication unit for supporting a communication interface of a wireless communication method between the measurement apparatus and the diagnosis server; And
Generating companion animal measurement data including intrinsic characteristic information of the input companion animal and each weight information added to the legs of the companion animal and transmitting the generated companion animal measurement data to the diagnosis server through the communication unit And a signal processor for processing the animal signal. The method according to claim 1,
The weight information may include,
Wherein the weight information includes weight information of each of the legs of the companion animal measured by the plurality of sensors and position information of the sensor that measures each weight information. The method of claim 2,
Wherein the plurality of sensors comprise:
When a leg of a companion animal is placed on each sensor, a deformation amount of the weighing device is detected as an electric signal and the weight applied to the leg of the companion animal placed on the sensor is measured Wherein the animal diagnostic system comprises: The method of claim 2,
Wherein the measuring unit comprises:
A body panel for supporting said companion animal for weight measurement; And
Further comprising a safety panel disposed at a periphery of the body panel in a direction perpendicular to the body panel to block movement of the companion animal while measuring the body weight of the companion animal. The method of claim 5,
Wherein the plurality of sensors comprise:
Wherein the body panel is disposed at a lower end of the body panel so as to be spaced apart from each other. delete delete delete The method according to claim 1,
The terminal apparatus comprises:
Wherein the terminal is at least one of a terminal device of an administrator previously registered corresponding to the measurement device and a terminal device of a user registered in advance in correspondence with the companion animal. The method according to claim 1,
The terminal apparatus comprises:
And displaying the diagnosis result of the companion animal received from the diagnosis server and the prognostic information corresponding to the companion animal received from the diagnosis server on the execution screen of the companion animal healthcare program Features a companion animal diagnostic system. Measuring a body weight applied to each leg of the companion animal using a plurality of sensors, respectively;
Providing the diagnostic server with the intrinsic characteristic information of the companion animal and the measured weight information to request diagnosis of the abnormal symptom of the companion animal;
The diagnosis server recognizing the intrinsic characteristic information and the weight information of the companion animal provided from the measurement device at the request of the measurement device;
The learning module included in the diagnosis server generates the big data mining for the companion animals. The companion animal learns the physical condition according to the species, sex, and age of the companion animals. Based on the result, the species, sex, Based on the predicted result, a decision element and a decision tree pattern are extracted, and a decision algorithm is applied to each of the legs. Extracting anomalous symptom statistical data corresponding to the companion animal from a DB storing the abnormal symptom statistical data generated by applying the abnormal symptom statistical data;
Diagnosing an abnormal symptom according to a weight distribution of the companion animal using the extracted abnormal symptom statistical data and weight information grasped about the companion animal;
Extracting prognostic information corresponding to a musculoskeletal disease predicted as a diagnosis result on the companion animal; And
And transmitting the diagnostic result to the terminal device and the prognostic information corresponding to the diagnosis result to the predetermined terminal device. delete The method of claim 12,
The terminal device executing a companion animal healthcare program provided in advance by the diagnostic server; And
And displaying the diagnostic result of the companion animal and the corresponding prognostic information on the execution screen of the companion animal health care program when the diagnostic result of the companion animal and the corresponding prognostic information are received from the diagnosis server Wherein said method comprises the steps of:

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