KR20200048288A - Method and Apparatus for measuring aging parameter based on gait speed - Google Patents

Abstract

The present invention provides a mobile terminal. The mobile terminal includes: a memory for storing at least one program; at least one communication interface for transmitting and receiving data to/from a server and a walking speed meter; and a processor for providing the degree of senility of a subject to be diagnosed by executing the at least one program. The at least one program includes commands for performing the following steps of: through the at least one communication interface, acquiring movement information of the subject to be diagnosed from the walking speed meter; determining the walking speed of the subject from the movement information of the subject; and obtaining the degree of senility of the subject based on the walking speed of the subject.

Description

{Method and Apparatus for measuring aging parameter based on gait speed}

The present invention relates to a mobile terminal for determining the degree of senility of a subject to be diagnosed with senility, and more particularly, to a mobile terminal for determining the degree of senility based on the walking speed of a subject for senility diagnosis.

With the aging of the population, an increasing number of elderly patients are undergoing surgical interventions of varying severity, from medical treatments with minor complications such as chemotherapy and minor surgery to intensive surgery after intensive surgery. In these various medical treatments, it is important to evaluate the patient's physiological function in order to prevent complications and prevent unnecessary treatment. However, according to the results of the previous studies, the chronological age of a patient is the physiological residual ability of an individual patient. It is known that (physiological reserve) is not properly predicted. On the other hand, evaluating the condition of 'frailty', defined as physiological homeostasis deteriorated by aging, is a number of complications compared to internal and surgical risks, or complications of future surgery, as compared to age or classical risk assessment tools. It is known that death and the like can be better predicted.

The classic method of evaluating such senility is a comprehensive geriatric assessment (CGA), typically accompanied by an individual's accompanying illness, medication status, activity of daily livings (ADL), and instrumental daily living performance ( instrumental activity of daily livings (IADL), cognitive function, depression, social support, and physical function. However, it is difficult to implement such a comprehensive evaluation for the elderly, which requires a professionally trained manpower, and requires a lot of time for evaluation, so it is not widely implemented except for specialized elderly medical centers. Accordingly, the demand for a method for quickly and objectively screening for aging during busy outpatient care in various specialized fields for treating the elderly is continuously increasing.

In this specification, a mobile terminal is provided that determines the degree of senility based on the walking speed of a subject diagnosed with senility. In addition, a server is provided that determines the degree of senility based on the walking speed of an senile diagnosis subject.

A memory for storing at least one program, a walking speed meter, at least one communication interface for transmitting and receiving data to and from a server, and a processor for providing the degree of senility of the subject to be diagnosed by executing the at least one program, wherein the at least One program may include, through the at least one communication interface, acquiring motion information of an elderly subject to be diagnosed from the walking speed meter, determining a walking speed of the elderly subject from the motion information of the elderly subject, And a command for performing the step of obtaining the degree of senility of the senility diagnosis subject based on the walking speed of the senility diagnosis subject.

The memory in which at least one program is stored, at least one communication interface for transmitting and receiving data to and from the server, a walking speed meter for acquiring motion information of the elderly subject, and executing the at least one program to determine the degree of senility of the elderly subject. And providing a processor, wherein the at least one program comprises: acquiring motion information of an elderly subject to be diagnosed from the walking speed meter, determining a walking speed of the elderly subject from the motion information of the elderly subject, And a command for performing the step of obtaining the degree of senility of the senility diagnosis subject based on the walking speed of the senility diagnosis subject.

Obtaining, by a communication interface, motion information of an elderly subject to be diagnosed from a walking speed meter, determining, by a processor, a walking speed of the elderly subject to be diagnosed from motion information of the elderly subject, and by the processor, A computer program product is provided that performs a step of acquiring the degree of senility of the senility diagnosis subject based on the walking speed of the senility diagnosis subject.

An elderly comprehensive evaluation data set and a memory in which at least one program is stored, at least one communication interface for transmitting and receiving data to and from a mobile terminal, and a processor that provides the degree of senility of an senile diagnosis subject by executing the at least one program, The elderly comprehensive evaluation data set includes data related to the walking speed and the degree of senility, and the at least one program, through the at least one communication interface, receives the walking speed of an aging diagnosis subject from the mobile terminal Determining, by the processor, the senility degree of the senility diagnosis subject based on the walking speed of the senility diagnosis subject, based on data relating to the walking speed and the senility level, and the at least one communication interface. through, The server according to claim, including instructions for performing the step of transmitting the aging degree of diagnosis for senile subjects based mobile terminal is provided.

A mobile terminal comprising a memory in which at least one program is stored, a walking speed meter and at least one communication interface that transmits and receives data to and from a server, and a processor that provides the degree of senility of a subject to be diagnosed by executing the at least one program, And a walking speed meter for acquiring motion information of the senility diagnosis subject, wherein the at least one program comprises: acquiring motion information of a senility diagnosis subject from the walking speed meter, and from the motion information of the senility diagnosis subject An senility diagnosis system is provided, comprising an instruction for determining a walking speed of an senile diagnosis subject and obtaining an senility degree of the senility diagnosis subject based on the walking speed of the senility diagnosis subject.

1 illustrates an embodiment of a mobile terminal, a walking speed meter and a server that determines an aging degree based on the walking speed of a subject diagnosed with senility.
2 illustrates an embodiment of a method of determining an senility degree based on a walking speed of a subject diagnosed with senility performed by a mobile terminal, a walking speed meter, and a server.
3 illustrates an embodiment of a menu selection screen shown on a display in a program executed in a mobile terminal.
FIG. 4 shows an embodiment of a walking speed measurement item shown on a display in a program executed in a mobile terminal.
5A and 5B respectively show an embodiment of a first data management item and a second data management item shown on a display in a program executed in a mobile terminal, respectively.
FIG. 6 shows an embodiment of a distance measurement item shown on a display in a program executed in a mobile terminal.
7 shows an embodiment of a setting item shown on a display in a program executed in a mobile terminal.
8A and 8B are two-dimensional graphs showing the relationship between actual age and walking speed, walking speed and senility, respectively.
9 shows a graph of survival probability of a specific walking speed group by Kaplan-Meier analysis.
Figure 10 shows the distribution of walking speed according to gender in the elderly living in the Korean community.
11 shows a graph for predicting senility by using a walking speed and other measured values together.
In the following description, unless otherwise indicated, the same reference numerals are used for the same elements, and overlapping descriptions are omitted.

Advantages and features of the disclosed embodiments, and methods of achieving them will become apparent with reference to the embodiments described below along with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms, and only the embodiments allow the disclosure of the present invention to be complete, and common knowledge in the technical field to which the present invention pertains. It is provided only to completely inform the person who has the scope of the invention.

The terms used in the present specification will be briefly described, and the disclosed embodiments will be described in detail.

In this specification, the degree of aging (frailty index) refers to an index indicating the aging state of the elderly. The degree of senility represents the ratio of an individual's senility-related symptoms divided by the total number of senility-related symptoms. Therefore, when there are no symptoms related to senility, the degree of senility is 0, and conversely, when all symptoms related to senility appear, the degree of senility is 1. That is, a high degree of senility indicates that the aged state is serious. The number and type of symptoms used to measure the degree of senility can be controlled by the measurer.

Cohort (cohort) as used herein refers to a group that shares a certain statistical factor. By using a cohort study, the incidence of a disease under study according to a specific factor can be tracked by comparing a group exposed to a specific factor with a group not exposed. For example, a cohort study can be used to track the survival rate of a population classified according to walking speed or senility.

1 illustrates an embodiment of a mobile terminal 100, a walking speed meter 110, and a server 122 that determines the degree of senility based on the walking speed of the sensible subject to be diagnosed 130.

The mobile terminal 100 can include a display 102, a memory 104, a processor 106, and a communication interface 108. According to an embodiment, the mobile terminal 100 may additionally include a configuration required for diagnosis of senility.

The mobile terminal 100 may include a display 102 for displaying data related to walking speed measurement and senility information determination. For example, the display 102 may display values measured or calculated by the senility level diagnosis apparatus 100 such as walking speed, senility level, and the like.

Also, the display 102 may include a function of a touch screen for receiving a user's instruction. Therefore, the user is provided with information through the display 102 and can input the user's instruction to be performed by the mobile terminal 100. For example, the mobile terminal 100 may receive personal information of the elderly subject 130 such as identification information, age, gender, residence area, race, etc. from the user from the display 102. Alternatively, the mobile terminal 100 may receive setting information for measuring the walking speed of the walking speed meter 110 from the display 102.

The mobile terminal 100 may include an input interface other than the display 102. Therefore, the mobile terminal 100 may receive information for senility diagnosis from an input interface other than the display 102.

The mobile terminal 100 may include a memory 104 in which a program for driving the mobile terminal 100 is stored. The memory 104 may store at least one program that performs diagnosis and determination of aging degree. In addition, the memory 104 may store information obtained from the communication interface 108 or information processed by the processor 106. In addition, the memory 104 determines the aging degree by combining the information on the walking speed parameter, the walking speed-aging degree correlation, and the walking speed and other measurement values, which are necessary for processing the information of the processor 106 Information and so on.

The mobile terminal 100 may include a processor 106. The processor 106 may execute instructions of at least one program that performs diagnosis and determination of the degree of aging stored in the memory 104. Hereinafter, the function of the processor 106 according to a program for performing diagnosis and determination of aging degree will be described.

The processor 106 may calculate the walking speed of the elderly subject to be diagnosed from the motion information of the elderly subject to be diagnosed 130. In addition, the processor 106 may calculate the walking speed of the elderly subject 130 based on at least one of the set setting values. For example, the setting information includes at least one of a measurement direction, a measurement range, and an effective measurement range.

The measurement direction indicates a movement direction of the elderly patient to be recognized by the walking speed meter 110. The measurement direction may include a forward direction, a reverse direction, a left direction, a right direction, etc. based on the walking speed meter 110. The walking speed meter 110 may record the movement of the senility diagnosis subject 130 when the senility diagnosis target 130 moves in a set measurement direction.

The measurement range represents the range of the distance between the walking speed meter 110 and the senility diagnosis subject 130 where the movement of the senility diagnosis subject can be measured. The walking speed meter 110 may generate motion information of the senility diagnosis target 130 when it is detected that the senility diagnosis target 130 is within a measurement range. The user can input a measurement range to the mobile terminal 100. Alternatively, the measurement range may be automatically changed according to the measurement environment of the walking speed meter 110.

The effective measurement range indicates the range of the distance between the walking speed meter 110 and the senile diagnosis subject 130 necessary for determining the walking speed. Even if the senile diagnosis target 130 walks within the measurement range, if the gait is not completed within the effective measurement range, the processor 106 does not calculate the walking speed of the senility diagnosis target 130. As with the measurement range, the user can input an effective measurement range to the mobile terminal 100. Alternatively, the effective measurement range may be automatically changed according to the measurement environment of the walking speed meter 110.

The processor 106 may determine the degree of senility of the senility diagnosis subject 130 based on the walking speed of the senility diagnosis subject 130. Gait speed is a key indicator used in determining the degree of aging. Accordingly, the processor 106 may calculate the physiological age of the subject 130 diagnosed according to the walking speed according to the association between the walking speed and the degree of senility.

The processor 106 may determine a walking speed parameter indicating a walking speed. The walking speed parameter represents the walking speed of a specific section. For example, the walking speed parameter may be defined for each section having a size of 0.2 m / s. As a specific example, the walking speed parameter may be defined as 1 for a section of 0.4 to 0.6 m / s and 2 for a section of 0.6 to 0.8 m / s. In addition, a unique walking speed parameter may be defined for the remaining 0.2 m / s sections. The above example is only exemplary, and the value of the walking speed parameter and the corresponding section can be easily changed by a person skilled in the art.

The processor 106 may determine the degree of senility from the walking speed by a correlation between the walking speed and the senility level indicating the relationship between the walking speed and the senility level. When the walking speed is expressed by the walking speed parameter, the processor 106 may determine the senility level from the walking speed parameter according to a correlation between the walking speed and the aging level. The correlation between walking speed and senility can be determined by regression analysis or machine learning of statistical data on walking speed and senility. 8A and 8B, the correlation between the walking speed and the degree of aging is specifically described.

Additionally, the processor 106 may calculate gait acceleration of the elderly subject to be diagnosed from the motion information of the elderly subject. In addition, the processor 106 may obtain the degree of senility of the senility diagnosis subject 130 by analyzing the walking speed and the acceleration of the senility diagnosis target 130.

The processor 106 derives the health status of the senile diagnosed person 130 based on physiological age according to the degree of senility, identification information of the senile diagnosed person 130, actual age, gender, residential area, race, and the like. can do. The processor 106 may calculate information such as postoperative mortality and complication rate according to information such as senility. Therefore, the processor 106 may help the user of the senility degree diagnosis apparatus 100 for the treatment method of the senility diagnosis subject 130.

The processor 106 may determine the degree of senility by using walking speed as well as other measurement values. In addition to walking speed, other factors may be used to measure the degree of senility. For example, data obtained through muscle strength evaluation, muscle mass evaluation, balance sensory evaluation, etc. may be additionally considered. In order to acquire the additional data, separate measuring devices may be installed separately from the walking speed measuring device 110. For example, a muscle strength meter may be installed for muscle strength evaluation, a muscle mass meter for muscle mass evaluation, and a balance sensor for balance evaluation.

The processor 106 may perform the calculation based on statistical data. For example, the statistical data related to the correlation between the walking speed and the aging degree presented above, the walking speed, the statistical data according to the actual age and gender of the elderly subject to be diagnosed, etc. may be used. Statistical data can also be used for other factors related to the degree of aging. The processor 106 may periodically update the statistical data and store it in the memory 104 of the mobile terminal 100 or the memory 124 of the server 122.

The processor 106 may obtain the senility degree of the senility diagnosis subject 130 calculated by the server 122 through the communication interface 108 without calculating the senility degree of the senility diagnosis subject 130. When the degree of senility of the subject to be diagnosed senility is determined in the server 122 stored in the memory 104, the size of data and programs required to determine the degree of senility is reduced, and the leakage of data necessary to determine the degree of senility Can be limited.

The processor 106 may obtain identification information of the user. In addition, when the user's identification information is valid, the processor 106 may perform a function for determining the degree of aging. The processor 106 may transmit the user's identification information to the server 122 through the communication interface 108 to determine whether the user's identification information is valid. In addition, when it is determined by the server 122 that the user's identification information is valid, the processor 106 may allow the user's access to a function for determining the degree of aging. In addition, the processor 106 may store information related to the senility diagnosis target 130 in the user's email account.

The mobile terminal 100 may include an additional processor in addition to the processor 106. In addition, the mobile terminal 100 may use a processor external to the mobile terminal 100 to perform an instruction for determining the degree of aging.

The mobile terminal 100 may include a communication interface 108 to receive and transmit data with the walking speed meter 110 and the server 122. The communication interface 108 may be implemented according to communication standards such as mobile communication, Bluetooth, Wi-Fi, infrared data association standard (IrDA), WiMAX, and the like.

The mobile terminal 100 may transmit setting information to the walking speed meter 110 through the communication interface 108. In addition, the mobile terminal 100 may obtain motion information of the elderly subject 130 from the walking speed meter 110 through the communication interface 108.

In addition, the mobile terminal 100 may transmit motion information and human information of the elderly subject 130 to the server 122 through the communication interface 108. In addition, the mobile terminal 100 may obtain medical information based on the degree of senility and senility of the senile diagnosis subject 130 from the server 122 through the communication interface 108. Also, according to an embodiment, the mobile terminal 100 may obtain the senility degree database indicating the relationship between senility degree and the walking speed from the server 122 through the communication interface 108.

The walking speed meter 110 may include a display 112, a memory 114, a sensor 116, a processor 118, and a communication interface 120. According to an embodiment, the walking speed meter 110 may include a configuration for additionally acquiring information necessary for measuring walking speed and determining senility.

The display 112 of the walking speed meter 110 may display data generated by the walking speed meter 110 and data transmitted from the mobile terminal 100. Also, the display 112 may include a function of a touch screen for receiving a user's instruction.

In addition, the memory 114 of the walking speed meter 110 may store data generated by the walking speed meter 110, data transmitted from the mobile terminal 100, and a program required to drive the walking speed meter 110.

The sensor 116 of the walking speed meter 110 detects the movement of the subject 130 to be diagnosed with age. The sensor 116 may emit a laser, infrared or ultrasonic waves, and recognize a reflected laser, infrared or ultrasonic waves. In addition, the sensor 116 may detect the movement of the subject 130 to be diagnosed based on the recognized laser, infrared, or ultrasonic signals.

The processor 118 of the walking speed meter 110 may perform a command necessary to measure the walking speed of the walking speed meter 110. The walking speed meter 110 may include one or more processors.

The walking speed meter 110 may be physically or communicatively connected to the mobile terminal 100 through the communication interface 120. The communication interface 120 of the walking speed meter 110 is connected to the communication interface 108 of the mobile terminal 100 so that the data of the walking speed meter 110 can be transmitted to the mobile terminal 100. Conversely, data of the mobile terminal 100 may be transmitted to the walking speed meter 110.

The walking speed meter 110 may transmit the detection time to the mobile terminal 100 when the movement of the senility diagnosis target 130 is detected. In addition, the walking speed meter 110 may transmit the distance to the mobile terminal 100, the senility diagnosis target 130 and the walking speed meter 110.

The walking speed meter 110 may obtain setting information from the mobile terminal 100. In addition, the walking speed meter 110 may acquire motion information of the elderly subject 130 according to the setting information.

The walking speed meter 110 may transmit identification information of the walking speed meter 110 to the mobile terminal 100. In addition, the mobile terminal 100 may determine whether the identification information of the walking speed meter 110 is valid. In addition, when the identification information is valid, the mobile terminal 100 may be set to process data transmitted from the walking speed meter 110. The mobile terminal 100 records the identification information of the walking speed meter 110 together with the motion information of the aged diagnosis subject 130 in order to record whether the movement of the elderly patient 130 is measured by which walking speed meter. Can be.

The walking speed meter 110 may transmit motion information of the elderly subject 130 to the mobile terminal 100. Specifically, the walking speed meter 110 may derive motion information, such as the speed and acceleration of the senility diagnosis target 130, from the motion of the senility diagnosis target 130, and transmit the motion information to the mobile terminal 100. .

According to an embodiment, the walking speed meter 110 may calculate the walking speed or the walking acceleration of the elderly subject to be diagnosed based on the movement of the elderly subject to be diagnosed 130. In addition, the walking speed meter 110 may transmit the walking speed or the walking acceleration of the elderly subject 130 to the mobile terminal 100.

According to FIG. 1, the walking speed meter 110 may be physically separated from the mobile terminal 100. However, the walking speed meter 110 may be physically connected to the mobile terminal 100.

Alternatively, a walking speed meter 110 may be built in the mobile terminal 100. Accordingly, the mobile terminal 100 may acquire motion information of the subject sensitized to diagnose 130 from the walking speed meter 110 embedded in the mobile terminal 100 without passing through the communication interface 108.

The server 122 can include a memory 124, a processor 126, and a communication interface 128. According to an embodiment, the server 122 may additionally include a configuration required for diagnosis of senility.

The server 122 may include a memory 124 for storing a program necessary for driving the server 122. The memory 124 may store an elderly comprehensive evaluation data set including statistical data for determining the degree of aging, and at least one program for performing diagnosis and determination of the aging degree. In addition, the memory 1220 may store motion information, the degree of senility, human information, and health information on the subject 130 to be diagnosed.

Server 122 may include a processor 126. The processor 126 may execute instructions of at least one program that performs diagnosis and determination of aging degree stored in the memory 124. Hereinafter, the function of the processor 126 according to a program for performing diagnosis and determination of aging degree will be described.

The processor 126 may determine the degree of senility of the senility diagnosis target 130 from the walking speed of the senility diagnosis target 130 received from the mobile terminal 100 through the communication interface 128. In addition, the processor 126 may transmit the degree of senility of the subject to diagnosis of senility to the mobile terminal 100 through the communication interface 128.

The processor 126 may generate medical information regarding the health status of the senile diagnostic target 130 based on human information and the senility of the senile diagnostic target 130. In addition, the processor 126 may determine the degree of senility of the senility diagnosis subject 130 by additionally considering the walking acceleration of the senility diagnosis subject 130.

The processor 126 may determine the degree of senility of the senility diagnosis subject 130 from the walking speed of the senility diagnosis subject 130 according to the elderly comprehensive evaluation data set stored in the memory 124. Specifically, the processor 126 may determine the degree of senility of the subject 130 to be diagnosed by using the correlation of the rate-sensitivity of the elderly comprehensive evaluation data set. Also, the processor 126 may determine the degree of senility of the subject to be diagnosed according to the walking speed parameter indicating the walking speed.

The processor 126 may determine the degree of senility of the senility diagnosis subject 130 according to the identification information of the walking speed meter 110. Specifically, only when the identification information of the walking speed meter 110 is valid, the processor 126 may determine the degree of senility of the subject to be diagnosed senility 130. In addition, the processor 126 records the identification information of the walking speed meter 110 together with the motion information of the aged diagnosis subject 130 in order to record whether the movement of the elderly patient 130 is measured by which walking speed meter. Can be.

The processor 126 may update the elderly comprehensive evaluation data set stored in the memory 124. Accordingly, the processor 126 may determine the degree of senility of the senile diagnosis subject 130 based on the updated and updated elderly comprehensive evaluation data set.

The server 122 may include a communication interface 128 to receive and transmit data with the mobile terminal 100. The communication interface 128 may be implemented according to communication standards such as mobile communication, Bluetooth, Wi-Fi, infrared data association standard (IrDA), WiMAX, and the like.

The server 122 may receive walking speed and human information of the elderly subject 130 from the mobile terminal 100 through the communication interface 128. In addition, the server 122 may transmit medical information based on the degree of senility and senility of the senile diagnosis subject 130 to the mobile terminal 100 through the communication interface 128. In addition, the server 122 may transmit the elderly comprehensive evaluation data set to the mobile terminal 100 through the communication interface 128.

The server 122 may include an additional processor in addition to the processor 126. In addition, the server 122 may use a processor external to the server 122 to perform an instruction for determining the degree of aging.

FIG. 2 illustrates an embodiment of a method 20 for determining the degree of senility based on the walking speed of the elderly subject to be diagnosed by the mobile terminal 100, the walking speed meter 110, and the server 122. City.

In step S21, the identification information of the walking speed meter is transmitted from the walking speed meter 110 to the mobile terminal 100.

In step S22, it is determined whether the identification information of the walking speed meter is valid by the mobile terminal 100. If the identification information of the walking speed meter is valid, the mobile terminal 100 and the walking speed meter 110 are communicatively connected.

In step S23, setting information regarding motion detection of the elderly subject to be diagnosed 130 is transmitted from the mobile terminal 100 to the walking speed meter 110.

In step S24, the walking speed meter 110 detects the movement of the senile diagnosis subject 130 according to the transmitted setting information. The setting information may include a measurement direction, a measurement range, and an effective measurement range.

In step S25, motion information of the elderly subject to be diagnosed 130 is transmitted from the walking speed meter 110 to the mobile terminal 100.

In step S26, the walking speed of the elderly subject to be diagnosed 130 is calculated from the motion information of the elderly subject to be diagnosed by the mobile terminal 100. Additionally, the walking acceleration of the elderly subject 130 may be calculated by the mobile terminal 100. In addition, personal information of the elderly subject to be diagnosed 130 may be input by the mobile terminal 100.

In step S27, the walking speed and human information of the elderly subject to be diagnosed 130 are transmitted from the mobile terminal 100 to the server 122. Additionally, information necessary for calculating the aging degree, such as walking acceleration, may be transmitted from the mobile terminal 100 to the server 122.

In step S28, the senility degree of the senility diagnosis subject 130 is calculated from the walking speed and human information of the senility diagnosis subject 130 by the server 122.

In step S29, the senility degree of the senility diagnosis subject 130 is transmitted from the server 122 to the mobile terminal 100.

In step S30, the senility degree of the senility diagnosis subject 130 is displayed by the display 102 of the mobile terminal 100.

The aging degree determination method 20 of FIG. 2 may be modified according to functions performed by the mobile terminal 100 of FIG. 1, the walking speed meter 110 and the server 122. For example, when the walking speed meter 110 is included in the mobile terminal 100, S21 to S23 and S25 may be excluded from the aging degree determination method 20. As another example, when the senility degree of the senility diagnosis target 130 is calculated in the mobile terminal 100, S27 to S29 may be excluded from the senility degree determination method 20.

3 shows an embodiment of the menu selection screen 300 shown in the display 102 in the program executed in the mobile terminal 100.

The menu selection screen 300 is displayed on the left side of the display 102. However, according to an embodiment, the menu selection screen 300 may be displayed on another part of the display 102. The menu selection screen 300 is a walking speed measurement (Gaitspeedometer) item 310. A data manager item 320, a distance measurement mode item 330, and a setting item 340 may be included. The menu selection screen 300 may include other items in addition to the items, or some of the items may be excluded. 4 to 7 for each item. Also, the menu selection screen 300 may display the user's identification information 350.

4 shows an embodiment of a walking speed measurement item 400 shown in the display 102 in a program executed in the mobile terminal 100.

The walking speed measurement item 400 displays a current walking speedometer 402 indicating the current speed of the subject 130 to be diagnosed with age. In addition, the walking speed measurement item 400 may include a walking speed meter connection lamp 404 and a walking speed meter connection button 406 indicating whether the mobile terminal 100 is connected to the walking speed meter 110. The user may connect or disconnect the mobile terminal 100 and the walking speed meter 110 by clicking the walking speed meter connection button 406. The walking speed measurement item 400 may include a walking speed measurement situation 408. When the walking speed meter 110 records the movement of the sensible diagnosis subject 130, the walking speed measurement situation light 408 may be activated. In addition, when the walking speed meter 110 completes the motion recording of the elderly subject 130, the walking speed measurement situation 408 may be deactivated. The walking speed measurement item 400 may include a walking speed meter battery indicator 410 indicating the amount of power of the battery of the walking speed meter.

When the walking speed measuring device 110 measures the distance between the subject 130 and the walking speed measuring device 110, the distance recording table 414, the speed recording table 416, and the acceleration recording table 418 of the walking speed measurement item 400 ), A distance-time graph, a speed-time graph, and an acceleration-time graph are respectively recorded based on the results measured by the walking speed meter 110. When the measurement of the walking speed meter 110 is completed, the average speed 412 may be displayed on the walking speed measurement item 400.

The walking speed measurement item 400 may include a personal information table 420. In Figure 4, the personal information table 420 includes only the name, patient number (identification number), age, and gender of the senile diagnosed person 130, but medical information regarding the sensible diagnosed person 130 may be additionally included. .

The walking speed measurement item 400 may include an automatic storage option 422, an automatic start option 424, and a sensor option 426. When the automatic storage option 422 is activated, when the generation of motion information of the elderly subject to be diagnosed 130 is completed, the motion information of the elderly subject to be diagnosed 130 is the mobile terminal 100, the server 122, or the email of the user It is automatically saved to your account. When the automatic start option 424 is activated, when the senility diagnosis target 130 is detected in the measurement range of the walking speed meter 110, the mobile terminal 100 automatically responds to the movement of the senility diagnosis target 130. Motion information of the senile subject 130 is generated. When the sensor option 426 is activated, the walking speed meter 110 may detect the movement of an object in front of the walking speed meter 110.

The walking speed measurement item 400 may include a setting initialization button 428, a start button 430, and a storage button 432. When the setting initialization button 428 is clicked, all existing setting information is initialized. When the automatic start option 424 is deactivated, when the start button 430 is clicked, the mobile terminal 100 generates motion information of the senility diagnosis target 130 according to the movement of the senility diagnosis target 130. When the auto-save option 422 is deactivated, when the save button 432 is clicked, the motion information of the elderly subject 130 is stored in the mobile terminal 100, the server 122, or the user's email account.

Unlike FIG. 4, according to an embodiment, a new element may be added to the walking speed measurement item 400 or the element illustrated in FIG. 4 may be excluded.

5A and 5B respectively show an embodiment of the first data management item 500 and the second data management item 520 shown in the display 102 in a program performed on the mobile terminal 100, respectively.

The first data management item 500 may include a data table 502. The data table 502 lists senile diagnostic data sets stored in the mobile terminal 100 or the server 122. The senility diagnosis data set includes personal information including the name and gender of the senility diagnosis target 130 and motion information including walking speed. The first data management item 500 may include the number of items per page 504. Data table 502 lists aging diagnostic data sets of number of items per page 504.

The first data management item 500 may include an extract button 506 and a delete button 508. When the extraction button 506 is clicked while the selection item 514 of the senility diagnosis data set is checked, the senility diagnosis data set is transmitted from the mobile terminal 100 or the server 122 to an external device. When the delete button 508 is clicked while the selection item 514 of the senility diagnosis data set is checked, the senility diagnosis data set is deleted from the mobile terminal 100 or the server 122.

The first data management item 500 may include a previous button 510 and a next button 512. When the previous button 510 is clicked, the aging diagnostic data set of the previous page is displayed in the data table 502, and when the next button 512 is clicked, the aging diagnostic data set of the next page is displayed in the data table 502. do.

The user can view detailed information of the senility diagnosis data set by clicking the specific senility diagnosis data set 516 in the first data management item 500. The second data management item 520 displays detailed information of the aged diagnosis data set 516.

The second data management item 520 may include a previous button 522, a list button 524, a next button 526, a storage button 528, and a delete button 530. When the previous button 522 is clicked, the data of the previous senility diagnostic data set is displayed in the data area 532, and when the next button 526 is clicked, the data of the next senility diagnostic data set is displayed in the data area 532 do. When the list button 524 is clicked, the first data management item 500 is displayed on the display 102. When the save button 528 is clicked, the senile diagnostic data set modified by the user is stored. Then, when the delete button 530 is clicked, the current senility diagnosis data set is deleted from the mobile terminal 100 or the server 122.

The second data management item 520 includes a data area 532 that displays data of the aged diagnostic data set. The data area 532 may include a data identification information area 534, a data personal information area 536, and a data motion information area 538. In the data identification information area 534, an identification number and a creation time of data may be displayed. In the data personal information area 536, personal information of the elderly subject 130 is displayed. Data in the data personal information area 536 may be modified by the user. In the data motion information area 538, motion information of the elderly subject to be diagnosed 130 is displayed. When the user clicks a specific graph in the data motion information area 538, the graph may be enlarged and displayed on the display 102.

5A and 5B, new elements may be added to the first data management item 500 and the second data management item 520 or elements shown in FIGS. 5A and 5B may be excluded according to embodiments.

6 shows an embodiment of a distance measurement item 600 shown on the display 102 in a program executed in the mobile terminal 100. The distance measurement item 600 provides an interface for determining a measurement range and an effective measurement range based on the distance between the walking speed meter 110 and the object.

The distance measurement item 600 may include a measurement range setting item 602, an effective measurement range setting item 604, and a current distance item 606. The measurement range setting item 602 indicates the maximum and minimum values of the current measurement range. And the effective measurement range setting item 604 indicates the maximum and minimum values of the current effective measurement range. The current distance 606 represents the distance between the walking speed meter 110 and the object.

The distance measurement item 600 may include a maximum value setting button 608 and a minimum value setting button 610. When the maximum value setting button 608 is clicked, the value displayed at the current distance 606 is determined as the maximum value of the measurement range. When the minimum value setting button 610 is clicked, the value displayed at the current distance 606 is determined as the minimum value of the measurement range. Then, when the maximum value setting button 608 is clicked, a value smaller than the value displayed on the current distance 606 may be determined as the maximum value of the effective measurement range. For example, a value 0.5 m smaller than the value displayed at the current distance 606 may be determined as the maximum value of the effective measurement range. When the minimum value setting button 610 is clicked, a value greater than the value displayed on the current distance 606 may be determined as the minimum value of the effective measurement range. For example, a value 0.5m larger than the value displayed at the current distance 606 may be determined as the minimum value of the effective measurement range.

Unlike FIG. 6, according to an embodiment, a new element may be added to the distance measurement item 600 or the element illustrated in FIG. 6 may be excluded.

7 shows an embodiment of a setting item 700 shown in the display 102 in a program executed in the mobile terminal 100. The setting item 700 provides an interface for determining setting information of the walking speed meter 110.

The setting item 700 may include a connection item 702. When the connection button 702 is clicked, the mobile terminal 100 and the walking speed meter 110 may be connected. If the connection button 702 is clicked when the mobile terminal 100 and the walking speed meter 110 are connected, the connection between the mobile terminal 100 and the walking speed meter 110 may be released.

The setting item 700 includes a measurement direction item 704, a measurement range maximum value item 706, a measurement range minimum value item 708, an effective measurement range maximum value item 710, and an effective measurement range minimum value item 712. can do. The measurement direction item 704 may be determined in the forward direction or the backward direction. When the measurement direction item 704 indicates the forward direction, when the senility diagnosis subject 130 advances to the walking speed meter 110, the walking speed meter 110 measures the movement of the senility diagnosis target 130. Conversely, when the measurement direction 704 indicates the backward direction, when the senility diagnosis subject 130 retracts from the walking speed meter 110, the walking speed meter 110 measures the motion of the senility diagnosis target 130.

The measurement range maximum value, the measurement range minimum value, according to the values entered in the measurement range maximum value item 706, the measurement range minimum value item 708, the effective measurement range maximum value item 710, and the effective measurement range minimum value item 712, The effective measurement range maximum value and the effective measurement range minimum value can be determined. Also, a maximum measurement range, a minimum measurement range, a maximum effective measurement range, and a minimum effective measurement range may be determined according to the interface provided in the distance measurement item 600.

The setting item 700 may include all data deletion items 714 and the number of items per page setting 716. When all data deletion items 714 are clicked, all the aging diagnostic data sets stored in the mobile terminal 100 or the server 122 are deleted. Then, the number of items per page 504 listed in the data table 502 of the first data management item 500 is determined according to the number of items per page setting 716.

The setting item 700 may include all data extraction items 718 and data extraction items 720 for each day. When all the data extraction items 718 are clicked, all the aging diagnostic data sets stored in the mobile terminal 100 or the server 122 are transmitted from the mobile terminal 100 or the server 122 to an external device. When the data extraction item 720 for each day is clicked, the aging diagnostic data set stored in the mobile terminal 100 or the server 122 on the selected date is transmitted from the mobile terminal 100 or the server 122 to an external device.

Unlike FIG. 7, new elements may be added to the setting item 700 or elements shown in FIG. 7 may be excluded according to an embodiment.

The interface of the program displayed on the display 102 according to FIGS. 3 to 7 may be changed according to the function of the mobile terminal 100.

8A and 8B are two-dimensional graphs showing the relationship between actual age and walking speed, walking speed and senility, respectively. The graphs of FIGS. 8A and 8B are obtained through linear regression analysis of statistical data, and the relationship between the walking speed and the physiological age and degree of senility of the elderly subject is expressed in the form of a linear function.

The x-axis of FIG. 8A represents the average walking speed in m / s. And the y-axis of Figure 3a represents the actual age. According to Figure 8a, it can be seen that the average walking speed decreases as the actual age increases. Therefore, it can be seen that walking speed is related to senility.

The x-axis of FIG. 8B represents the average walking speed in m / s. And the y-axis of Figure 8b represents the degree of senility. According to Figure 8b, it can be seen that as the degree of senescence increases, the average walking speed decreases. Therefore, it can be seen that walking speed is related to senility.

Therefore, referring to FIGS. 8A and 8B, it is possible to estimate the physiological age and degree of senility of a subject diagnosed with senility through measurement of walking speed.

9 shows a graph of survival probability of a specific walking speed group by Kaplan-Meier analysis. Kaplan-Meier analysis represents the probability of survival of people with certain conditions over time, and can be obtained by observing a sufficiently large sample sized population for a long time.

The x-axis in FIG. 9 represents the proportion of survivors among the total cohort participants, and the y-axis represents the measurement period. According to FIG. 4, Koch participants are divided into four groups (410,420,430,440) according to the walking speed, and the results of observing deaths according to the period for each group are displayed. The lowest drop rate of the survivor ratio of the lowest walking speed group 440 is the lowest, and the smallest drop rate of the survivor rate of the highest walking speed group 410. That is, it can be seen that the faster the walking speed, the higher the survival rate in time series observation.

Therefore, through the measurement of the walking speed, the mobile terminal 100 or the server 122 of FIG. 1 can predict the survival probability of the elderly subject.

According to Table 1 below, items having a strong association with the walking speed are listed. When divided into participants who walk faster than the median (high-speed pedestrians) and participants who walk slower than the median (low-speed pedestrians) across the population, statistically significant multimorbidity, grip strength, and physical function (SPPB), Differences were observed in the degree of senility (K-FRAIL and CHS frailty score), daily and instrumental daily performance (ADL, IADL), depression, cognition, and polypharmacy falls. That is, it is possible to infer the health status of the senile diagnosis subject by measuring the walking speed of the senile diagnosis subject.

Item Low speed pedestrian High speed pedestrian P value multimorbidity (n) 310.00 221.00 <0.001 Dominant grip strength (mean, sd) 19.92 24.90 <0.001 SPPB score (mean, sd) 6.61 9.37 <0.001 K-FRAIL score (mean, sd) 1.63 0.93 <0.001 CHS score (mean, sd) 2.39 1.25 <0.001 ADL disability (n,%) 125.00 56.00 <0.001 IADL disability (n,%) 294.00 150.00 <0.001 Depression (n,%) 102.00 34.00 <0.001 Cognitive dysfunction (n,%) 270.00 125.00 <0.001 Polypharmacy (n,%) 193.00 113.00 <0.001 Fall history for previous 1 year (mean, sd) 0.33 0.16 0.001

Figure 10 shows the distribution of walking speed according to gender in the elderly living in the Korean community. The graph on the left of FIG. 10 shows a male walking speed distribution chart. And the graph on the right side of Figure 10 shows the walking speed distribution of women. Since there is a difference in the distribution of walking speed between men and women, in measuring the physiological age of elderly subjects, it is necessary to consider the walking speed and gender of elderly subjects.

11 shows a graph for predicting the degree of senescence by using the walking speed and other measured values together. In Fig. 11, the walking speed and the humerus circumference are measured to show the association between the walking speed parameter and the humerus circumference parameter and the degree of senility. The brachial girth circumference parameter is closely related to the degree of senility because it is related to the muscle mass of the subject diagnosed with senility, and is an important factor in predicting walking speed and senility senility.

The graph on the left side of Fig. 11 shows the relationship between the walking speed parameter and the degree of senility. According to the graph on the left, it can be seen that as the walking speed parameter decreases, the degree of senility increases.

In the middle graph of Fig. 11, the relationship between the parameter of the upper arm muscle and the degree of senility is shown. According to the intermediate graph, it can be seen that the degree of senility increases as the parameter of the upper arm muscles decreases.

In the right graph of FIG. 11, according to the results of the left graph and the middle graph of FIG. 11, the relationship between the evaluation value and the senility degree obtained based on the walking speed parameter and the brachial circumference parameter is shown. According to the graph on the right, it can be seen that the degree of senility increases as the evaluation value increases. When predicting the degree of senescence by combining two or more factors, prediction accuracy may increase. In FIG. 11, the evaluation value obtained by combining the walking speed and the humerus circumference was used, but the degree of senescence can be predicted by using other factors instead of the humerus circumference or by adding more.

Hereinafter, exemplary embodiments will be described in detail with reference to the accompanying drawings so that those skilled in the art to which the present invention pertains may easily practice. In addition, in order to clearly describe the present invention in the drawings, parts irrelevant to the description are omitted.

Meanwhile, the above-described embodiments of the present invention can be written in a program executable on a computer and can be implemented in a general-purpose digital computer that operates the program using a computer-readable recording medium.

The terms used in the present specification have selected general terms that are currently widely used as possible while considering the functions in the present invention, but this may be changed according to intentions or precedents of a person skilled in the relevant field or the appearance of new technologies. In addition, in certain cases, some terms are arbitrarily selected by the applicant, and in this case, their meanings will be described in detail in the description of the applicable invention. Therefore, the terms used in the present invention should be defined based on the meanings of the terms and the contents of the present invention, not simply the names of the terms.

In the present specification, a singular expression includes a plural expression unless the context clearly indicates that it is singular. When a part of the specification "includes" a certain component, this means that other components may be further included instead of excluding other components, unless specifically stated to the contrary.

Although the present invention has been described in connection with certain best embodiments, in addition, inventions to which the invention has been replaced, modified and modified will be apparent to those skilled in the art in light of the foregoing description. That is, the claims are to be interpreted to cover all such alternatives, modifications and modified inventions. Therefore, all contents described in this specification and drawings should be interpreted in an illustrative and non-limiting sense.

Claims (13)

A memory in which at least one program is stored;
A walking speed meter and at least one communication interface for transmitting and receiving data to and from the server; And
And a processor that provides a degree of senility of the subject to senility diagnosis by executing the at least one program,
The at least one program,
Acquiring motion information of an aging diagnosis subject from the walking speed meter through the at least one communication interface;
Determining a walking speed of the elderly patient from the motion information of the elderly patient; And
And a command for performing a step of acquiring a degree of senility of the senility diagnosis subject based on a walking speed of the senility diagnosis subject.
According to claim 1,
The at least one program,
Acquiring human information of the subject to be diagnosed with age; And,
And acquiring medical information regarding a health condition of the senile diagnosis subject based on human information and the degree of senility of the senile diagnosis subject.
According to claim 2,
The personal information of the subject of senility diagnosis,
Mobile terminal characterized in that it comprises at least one of the identification information, age, gender, residential area, race of the elderly subject.
According to claim 1,
The at least one program,
The step of determining the walking acceleration of the senility diagnosis subject from the motion information of the senility diagnosis subject,
The step of acquiring the degree of senility in the subject of senility diagnosis,
A mobile terminal characterized by acquiring a degree of senility of the senility diagnosis subject based on a walking speed and an acceleration of walking.
According to claim 1,
The at least one program,
And transmitting, to the server, a walking speed of the elderly subject through the at least one communication interface.
The step of acquiring the degree of senility in the subject of senility diagnosis,
And through the at least one communication interface, obtaining a degree of senility of the senility diagnosis subject determined based on the walking speed of the senility diagnosis subject, from the server.
According to claim 1,
The at least one program,
And acquiring, through the at least one communication interface, the senility degree database indicating the relationship between the senility degree and the walking speed,
The step of acquiring the degree of senility in the subject of senility diagnosis,
And determining the senility degree of the senility diagnosis subject based on the walking speed of the senility diagnosis subject based on the senility degree database.
According to claim 1,
The at least one program,
Determining setting information for obtaining motion information of the elderly subject; And
And transmitting the setting information to the walking speed meter through the at least one communication interface.
The step of acquiring the motion information of the subject to be diagnosed with senility,
A mobile terminal characterized in that, through the at least one communication interface, acquires motion information of the senile diagnosis subject acquired by the walking speed meter according to the setting information.
The method of claim 8,
The setting information includes at least one of a measurement direction, a measurement range, and an effective measurement range,
The measurement direction represents a movement direction of the elderly patient to be recognized by the walking speed meter,
The measurement range represents a range of the walking speed meter and the distance of the subject to be diagnosed with senility where the movement of the subject to be diagnosed can be measured,
The effective measurement range is a mobile terminal characterized in that it indicates a range of the distance of the walking speed meter and the subject of senility diagnosis necessary for the determination of the walking speed.
According to claim 1,
The at least one program,
Acquiring identification information of the walking speed meter from the walking speed meter through the at least one communication interface; And
And determining whether the walking speed meter is valid according to the identification information.
A memory in which at least one program is stored;
At least one communication interface for transmitting and receiving data to and from the server;
A walking speed measuring device for acquiring motion information of an elderly subject; And
And a processor that provides a degree of senility of the subject to senility diagnosis by executing the at least one program,
The at least one program,
Obtaining motion information of an senile diagnosis subject from the walking speed meter;
Determining a walking speed of the elderly patient from the motion information of the elderly patient; And
And a command for performing a step of acquiring a degree of senility of the senility diagnosis subject based on a walking speed of the senility diagnosis subject.
Obtaining, by a communication interface, motion information of an aging diagnosis subject from a walking speed meter;
Determining, by a processor, a walking speed of the elderly subject to be diagnosed from motion information of the elderly subject; And
A computer program product performing, by the processor, obtaining an senility degree of the senility diagnosis subject based on a walking speed of the senility diagnosis subject.
A memory in which the elderly comprehensive evaluation data set and at least one program are stored;
At least one communication interface for transmitting and receiving data to and from the mobile terminal;
And a processor that provides a degree of senility of the subject to senility diagnosis by executing the at least one program,
The elderly comprehensive evaluation data set includes data related to the walking speed and the degree of senility,
The at least one program,
Receiving, through the at least one communication interface, a walking speed of an aging diagnosis subject from the mobile terminal;
Determining, by the processor, the senility degree of the senility diagnosis subject based on the walking speed of the senility diagnosis subject based on data relating to the walking speed and the senility level; And
And a command for performing, through the at least one communication interface, a step of transmitting an senility degree of an senile diagnosis subject to the mobile terminal.
A mobile terminal including a memory in which at least one program is stored, a walking speed meter, at least one communication interface for transmitting and receiving data to and from a server, and a processor that provides the degree of senility of a subject to be diagnosed by executing the at least one program; And
It includes a walking speed measuring device for obtaining the motion information of the subject of the senility diagnosis,
The at least one program,
Obtaining motion information of an senile diagnosis subject from the walking speed meter;
Determining a walking speed of the elderly patient from the motion information of the elderly patient; And
And an instruction for performing a step of acquiring a degree of senility of the senility diagnosis subject based on a walking speed of the senility diagnosis subject.

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