Computer program and motor function assessment system.

Abstract

To provide a system and a computer program for determining an exercise function such as sarcopenia, frailty, and falling down, the system and computer program enabling simple determination and having excellent reliability.SOLUTION: A computer program for exercise function determination makes a computer coupled to a detector for detecting a subject's upward action as a physical variable execute the following steps of: recording step of receiving a signal of data on the physical variable from the detector to record the data on the physical variable in association with subject data; predetermined value calculation step of substituting the recorded data on the physical variable into a predetermined equation to calculate a predetermined value; and discrimination step of comparing the predetermined value with a predetermined threshold to discriminate the subject's exercise function.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a system and computer program for assessing motor functions such as sarcopenia, frailty, and falls, which can be assessed simply and reliably. [Background technology]

[0002] In the health of the elderly, sarcopenia, frailty, and motor function such as falls are major problems. Sarcopenia and frailty are reversible conditions, and it has been shown that falls can be prevented through intervention. Therefore, if these conditions can be detected and addressed early, it is possible to delay the onset of a nursing care requirement. Currently, to identify frailty and sarcopenia, and to assess the risk of falling, physical function assessments such as grip strength and skeletal muscle mass, and performance tests such as walking speed and time up and go tests are used. However, these tests have issues such as the complexity of the measurements, safety, manpower, and measurement space, making it difficult to conduct them frequently in local health programs, etc. Therefore, there is a need to establish a testing tool that can be conducted more easily. Therefore, efforts are being made to develop tools that allow for easier inspection, and various proposals have been made. For example, Patent Document 1 proposes a computer-implemented method for assessing the frailty of a subject. The method proposed in Patent Document 1 is a measurement method that includes the steps of receiving a plurality of force measurements obtained by a measurement device configured to determine a weight of a subject standing on a user support surface by measuring the force experienced by a user support surface of the measurement device, the force measurements being obtained at regular time intervals over a measurement period during which the subject steps onto and subsequently stands on the user support surface; and a calculation step of calculating a frailty index indicating the degree of frailty of the subject using the received force measurements. Furthermore, Patent Document 2 proposes a frailty assessment method that aims to detect frailty early, to help prevent a state requiring nursing care through appropriate intervention, to make the concept of frailty more widely known in general, and to contribute to more effective research on frailty. Specifically, the proposed frailty assessment method involves displaying a plurality of frailty assessment items using a display means, inputting answers to the frailty assessment items displayed on the display means via an input means, determining the presence or absence of a suspicion of frailty based on the answers inputted via the input means by a determination means, and outputting the determination result by the determination means using an output means. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2017-535339 [Patent Document 2] WO2018 / 066465 publication Summary of the Invention [Problem to be solved by the invention]

[0004] However, the method proposed in the above-mentioned Patent Document 2 still requires the input of many measured values, and the complexity has not been eliminated. Also, the method proposed in Patent Document 1 requires the acquisition of data based on a certain amount of time constraints, and requires the processing of multiple pieces of data, so there are problems in that the complexity is not sufficiently eliminated and the results obtained are unreliable. Therefore, there is currently a demand for the development of a system for assessing motor functions such as sarcopenia, frailty, and falls that is both easy to assess and highly reliable.

[0005] Therefore, an object of the present invention is to provide a system and computer program for assessing motor functions such as sarcopenia, frailty, and falls, which can be easily and reliably assessed. [Means for solving the problem]

[0006] The inventors conducted intensive research to resolve the above-mentioned problems, focusing on the fact that by using floor reaction force measurement results, testing can be performed safely in a small space. After much research, they discovered that the above-mentioned objective could be achieved by establishing a method for assessing motor function using floor reaction force measurement, and thus completed the present invention. That is, the present invention provides the following inventions. 1. A computer program for assessing motor function that causes a computer connected to a detection device that detects an upward movement of a subject as a physical variable to execute the following steps: a recording step of receiving a signal of data of the physical variable from the detection device and recording the data regarding the physical variable in association with subject data; A predetermined value calculation step of calculating a predetermined value by substituting the recorded data on the physical variables into a predetermined formula. and A discrimination step of comparing the predetermined value with a predetermined threshold value to discriminate the motor function of the subject. A computer program that executes the following: 2. The motor function of the subject is sarcopenic. The calculation step includes a step of obtaining a maximum floor reaction force F from the physical variables, 2. The computer program according to claim 1, wherein the predetermined formula is the following formulas (1) and (a) when the subject is male, and formulas (2) and (a) when the subject is female. ScoreA(male) = Coefficient A1 x Age - Coefficient B1 x F - Constant C1(1) ScoreB (female) = Coefficient A2 x Age - Coefficient B2 x F - Constant C2 (2) Sarcopenia score = 1 / ((1+exp(-1×ScoreA or ScoreB)) (a) (where F (kgf) is the maximum floor reaction force) 3. The subject's motor function is frail, The calculation step includes a step of obtaining a maximum floor reaction force F from the physical variables, 2. The computer program according to claim 1, wherein the predetermined formula is the following formulas (3) and (b): ScoreC = Coefficient A × Age + Coefficient B × Gender + Coefficient C × F + Coefficient D × T1 + Coefficient E × T2 + Coefficient F × W - Constant G (3) Frailty score = 1 / ((1+exp(-1×ScoreC)) (b) (In the formula, F (kgf) is the maximum floor reaction force, T1 (sec) is the time from recording the minimum floor reaction force to recording the maximum floor reaction force F, T2 (sec) is the time from recording the maximum floor reaction force F to the completion of standing, and W (kgf) is the floor reaction force at the completion of standing. The above-mentioned completion of standing is the point where the standard deviation of the floor reaction force value per 10 data (0.125 sec) falls below 50gf.) 4. The motor function of the subject is a risk of falling. The calculation step includes a step of obtaining a maximum floor reaction force F from the physical variables, 2. The computer program according to claim 1, wherein the predetermined formula is the following formula (4): Fall risk score = maximum floor reaction force F / floor reaction force at standing completion point W (4) 5. A detection device for detecting the subject's upward movement as a physical variable and a computer connected to the detection device; The computer, a recording means for receiving a signal of data relating to the physical variable from the detection device and recording the data in association with subject data; A predetermined value calculation means for calculating a predetermined value by substituting the data on the physical variables into a predetermined formula. and functioning as a discrimination means for discriminating the motor function of the subject by comparing the predetermined value with a predetermined threshold value. Motor function assessment system. Effect of the Invention

[0007] According to the motor function assessment system and computer program of the present invention, motor function assessment such as sarcopenia, frailty, and falls can be performed simply and reliably. More specifically, it can measure physical fitness indicators easily and without requiring a lot of space, and can judge motor functions such as frailty. In addition, it can be easily measured because it does not require an optimal examiner. Furthermore, it can be directly implemented in weight scales that are widely used in homes, and can also be applied to devices with built-in accelerometers such as smartphones. It is highly versatile and can be implemented in devices with built-in accelerometers, such as weighing scales and smartphones. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a schematic diagram of a computer used in the present invention. [Diagram 2] FIG. 2 is a schematic diagram showing a flow sheet of a computer program of the present invention. [Diagram 3] FIG. 3 is a chart showing an example of a graph showing changes over time that is generated by a computer based on received data in one embodiment of the present invention. [Figure 4] FIG. 4 shows one embodiment of the measurement, where (a) is a schematic diagram showing a state in which the subject is sitting, and (b) is a schematic diagram showing a state in which the subject is standing. [Diagram 5] FIG. 5 is a chart showing the ROC curve of the sarcopenia score in the examples. [Figure 6] FIG. 6 is a chart showing the ROC curve of the frailty score in an embodiment. [Figure 7] FIG. 7 is a chart showing the ROC curve of the fall risk score in the example. [Explanation of symbols]

[0009] 1: computer, 11: memory, 13: CPU, 15: storage medium, 20: input device, 30: output means, 40: detection device, 100: motor function determination system DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] The present invention will now be described in further detail. The motor function assessment system of the present invention comprises a detection device 40 that detects an upward movement of a subject as a physical variable, and a computer 1 connected to the detection device 40, as shown in FIG. First, the computer program of the present invention will be described, and then the motor function determination system of the present invention will be described. The computer program of the present invention is for making a computer 1 connected to a detection device 40 shown in FIG. 1, which detects the subject's upward movement as a physical variable, execute the following steps shown in FIG. 2 to determine the motor function of the subject. The computer 1 and the detection device 40 are connected to each other by wire or wirelessly (LAN, WIFI (registered trademark), BLUETOOTH (registered trademark)) so as to be able to transmit and receive various data. The computer program of this embodiment is a computer program for determining motor function that makes a computer connected to a detection device that detects the subject's upward movement as a physical variable execute the following steps, which are a recording step of receiving a signal of data related to the subject's physical variables from the detection device and recording the data related to the physical variables in association with the subject data, a predetermined value calculation step of substituting the recorded data related to the physical variables into a predetermined formula to calculate a predetermined value, and a determination step of comparing the predetermined value with a predetermined threshold value to determine the motor function of the subject. In the following, the present embodiment will be described first with reference to the computer, and then each step will be described.

[0011] 〔computer〕 Specifically, as shown in FIG. 1, the computer 1 used in this embodiment may be a normal personal computer including a central processing unit (CPU) 13, a memory 11 as a temporary storage area, and a non-volatile storage medium 15 such as a hard disk or a solid state device, without any particular restrictions. Also, a mobile terminal such as a smartphone or a tablet terminal may also be used, and these are also included in the "computer" in the present invention. In addition, although not shown in particular, the computer in this embodiment preferably has a communication device and is capable of communication via a network. It is also possible to set the computer to connect to a server having a database placed on a network by performing communication, and to obtain updated data from the database at any time. In addition, the computer is provided with input devices 20 such as an image input device such as a keyboard, mouse, or camera, a voice input device such as a microphone, or a communication input device using a communication device such as Bluetooth (registered trademark), and is set to input necessary data and information as appropriate. In addition, the computer is provided with an output means 30 such as a display for displaying the evaluation results or a printer for printing, and the results are output in a desired form as appropriate. In this embodiment, the program of this embodiment is stored in this computer, and the computer functions as a part of a system that performs each of the means described below. In addition to the above-mentioned devices, other devices may be added to the computer as necessary. [Detection device] As the detection device used in this embodiment, a known motor function analysis device can be used, and an acceleration measurement device capable of measuring acceleration can also be used. As the acceleration measurement device, a device equipped with a normal accelerometer, such as a smartphone, can be used. When using such a device capable of measuring acceleration, it is necessary to have a computer execute an operation of calculating a floor reaction force from the acceleration in a calculation step described later. The motor function analysis device may be one that can directly measure floor reaction force. Specifically, it is necessary to be able to measure the maximum floor reaction force F (kgf), the time T1 (sec) from recording the minimum floor reaction force to recording the maximum floor reaction force F, the time T2 (sec) from recording the maximum floor reaction force F to standing up completion, and the floor reaction force W (kgf) at the standing up completion point. Here, in the present invention, the standing up completion point is set as the point where the standard deviation of the floor reaction force value per 10 data (0.125 sec) falls below 50 gf. Specifically, commercially available products can be used, for example, a motor function analyzer product name "zaRitz BM-220" (manufactured by Tanita Corporation) can be used. [Other components (devices)] In this embodiment, in addition to the above-mentioned computer and detection device, various other devices may be included as necessary.

[0012] [Preparation step (S0)] In the present invention, first, as a preparatory step, a database is constructed in the computer 1 . This database is constructed by storing the personal data of each subject and the motor function-related data on sarcopenia, frailty, and fall risk, which will be described later, in a mutually associated manner. The data stored in this database is used to calculate cut-point values ​​as thresholds, which will be described later. The personal data may include name, age, date of birth, sex, medical history, etc. These constructions are carried out by having the subject's personal data and motor function-related data entered using the input device be applied and stored in a database file created by a spreadsheet software or the like stored in the computer's storage medium by the computer's CPU. When executing this program, the latest data can be input. In that case, the measurement data described later, the values ​​calculated in each step described later, and the assessment results regarding motor function are appropriately incorporated into the database (addition of data to the database as indicated by the arrows in Figure 2), and the database is updated. By including this step, it becomes possible to perform the determination in each step described later. The database can be constructed not in a recording medium inside the computer but in a recording medium such as a server, and multiple motor function discrimination systems can access the server to construct a database with a larger amount of accumulated data. In this case, the subject data can be updated with more data at any time, thereby further improving the reliability of discrimination.

[0013] [Recording step S1] This step is a step of receiving a signal of data relating to the physical variable detected by the detection device, and recording the data relating to the physical variable in association with subject data. Here, the data on the detected physical reaction force varies depending on the type of detection device used, but ultimately becomes data on the floor reaction force and data on the time of the movement. To be more specific, when the acceleration measurement device is used, the physical variables sent from the acceleration measurement device, which is the detection device, are the acceleration corresponding to the movement measured over time and the time from the start of the movement when the acceleration is measured. Also, when a motor function analysis device is used, the physical variables are the floor reaction force corresponding to the movement and the time from the start of the movement when the floor reaction force is measured. Here, "acceleration" in this specification means acceleration obtained by extracting only the upward (vertical) acceleration from the subject's movement. "Floor reaction force" means the force exerted by the subject against the floor when he or she tries to stand up from a lying position. The method of measuring floor reaction force using the above-mentioned motor function analysis device will be described later. Data regarding these physical variables are associated with the subject data and stored in the database.

[0014] [Predetermined value calculation step S2] In this embodiment, the motor functions are sarcopenia, frailty, and fall risk. In the predetermined value calculation step and the determination step, the formulas and thresholds used for each of these motor functions are different, so each step will be described for each motor function. The computer program of this embodiment is configured to calculate and display all of these motor functions, but it is also possible to configure it to select any one of these motor functions and have it calculated, determined, and displayed as necessary. <Common matters> In this step, data on floor reaction force (including the time taken from the start of the movement and the elapsed time) is obtained directly or by calculation from the above physical variables, and the obtained data on floor reaction force is organized by a computer over time as shown in the graph in Figure 3. If the above physical variable is data on floor reaction force, the data on such physical variable is stored directly, and if it is data on acceleration, the data on floor reaction force is stored in the database together with the elapsed time by substituting acceleration and body weight into the formula: F=a*W (where F is floor reaction force, a is acceleration, and W is the subject's body weight). The data to be stored are the minimum floor reaction force (kgf), the maximum floor reaction force F (kgf), and the floor reaction force W (kgf) at the time of completion of standing up, which are calculated from the data shown in FIG. 3. The minimum floor reaction force is the reaction force value at the point where the floor reaction force is the minimum as shown in FIG. 3, and the maximum floor reaction force F is the reaction force value at the point where the floor reaction force is the maximum as shown in FIG. 3. In addition, the time (T1) from recording the minimum floor reaction force point after the start of the standing up motion to measuring the maximum floor reaction force F, and the time (T2) from the start of the standing up motion to the completion of the standing up motion are also calculated and stored. Here, the above-mentioned standing up completion point is defined as the point where the standard deviation of the floor reaction force value per 10 data (a data collection of 10 consecutive pieces of force data measured every 0.125 seconds) falls below 50 gf. That is, the calculation formula for calculating each of these values ​​is stored in the recording medium of the computer, and it is set to perform calculations and calculate each value based on the received data. The calculated minimum floor reaction force, maximum floor reaction force F, floor reaction force W at the completion of standing, time (T1) and time (T2) are each recorded in the database of the storage medium in association with the information about the subject described above. <Sarcopenia> When verifying sarcopenia, this step involves substituting the force data into a specified formula to calculate a specified value, i.e., the sarcopenia score. Here, when the motor function of the subject is sarcopenic, the above-mentioned predetermined formulas become the following formulas (1) and (2). That is, if the subject is male, the following formulas (1) and (a) are used, and if the subject is female, the following formulas (2) and (a) are used. Note that the following formulas (1) and (2) were obtained by performing logistic regression analysis for each sex, with sarcopenia determined according to the AWGS2019 criteria and the presence or absence of sarcopenia as the dependent variable. Score(Male)(predetermined value above) = Coefficient A1 x Age - Coefficient B1 x F - Constant C1(1) Score(female)(given value above) = Coefficient A2 x Age - Coefficient B2 x F - Constant C2(2) Sarcopenia score = 1 / ((1+exp(-1×Score)) (a) (where F (kgf) is the maximum floor reaction force) In the above formula, coefficient A1, coefficient B1, constant C1, coefficient A2, coefficient B2, and constant C2 are each determined by the above logistic regression analysis. For example, in the examples described below, each coefficient and constant is determined as follows. Coefficient A1 and coefficient A2: A1 = 0.110, A2 = 0.090 Coefficient B1 and coefficient B2: B1 = 0.123, B2 = 0.151 Constant C1 and constant C2: C1 = 0.338, C2 = 0.525 In this embodiment, the above formulas (1), (2) and (a) are stored in a recording medium, and the maximum floor reaction force F stored in the recording step is substituted into the above formula (1) or (2), and the obtained score is substituted into formula (a) to calculate the sarcopenia score. The calculated sarcopenia score is stored in a database together with information on the subject and information on the date and time of measurement. [Discrimination step S3] This step is a step of comparing the above-mentioned predetermined value with a predetermined threshold value to determine the motor function of the subject. In this step, sarcopenia is determined using the sarcopenia score stored in the database. That is, the obtained sarcopenia score is compared with the cut point value calculated in the preliminary survey, and if it is equal to or greater than the cut point value, it is determined that the risk of sarcopenia is high (the possibility of muscle mass loss is high). On the other hand, if it is smaller than the cut point value, it is determined that the risk of sarcopenia is low (the possibility of muscle mass loss is low). This cut point value is obtained from the data and sarcopenia score of many subjects obtained in the preliminary survey. Specifically, the cut point value is obtained by calculating the value at which the sensitivity and specificity are optimized by ROC curve analysis using the subject data and sarcopenia score obtained in the preliminary survey. Therefore, the cut point will vary depending on the population in the preliminary survey. This point is the same for frailty and fall risk, which will be described later. For example, in the examples described below, the cut-point values ​​(male = 0.102, female = 0.063) were obtained from a preliminary survey of 627 community-dwelling elderly people, and the values ​​providing optimal sensitivity and specificity were calculated using ROC curve analysis (area under the curve: male = 0.91, female = 0.89, sensitivity / specificity: male = 0.897 / 0.805, female = 0.950 / 0.609). The discrimination results are displayed or output by a computer output means (display device such as a printer or display) together with data regarding the sarcopenia score and floor reaction force.

[0015] <Flail> Below, we will explain frailty, focusing on the differences from sarcopenia described above. For points not specifically explained, the explanation for sarcopenia described above applies as appropriate. If the subject's motor function is frail, the frailty score is calculated as a predetermined value using the following formulas (3) and (b). Note that the following formula was obtained by performing a logistic regression analysis with the presence or absence of frailty determined using the Japanese version of the Cardiovascular Health Study (CHS) criteria as the dependent variable. Score = Coefficient A x Age + Coefficient B x Gender - Coefficient C x F + Coefficient D x T1 - Coefficient E x T2 + Coefficient F x W - Constant G (3) Frailty score = 1 / ((1+exp(-1×Score)) (b) (In the formula, F (kgf) is the maximum floor reaction force, T1 (sec) is the time from recording the minimum floor reaction force to recording the maximum floor reaction force F, T2 (sec) is the time from recording the maximum floor reaction force F to the completion of standing, and W (kg) is the floor reaction force at the completion of standing. The above-mentioned completion of standing is the point where the standard deviation of the floor reaction force value per 10 data (0.125 sec) falls below 50gf.) In the formula, the coefficients and constants are determined by the above logistic regression analysis. For example, in the examples described later, the coefficients and constants are as follows: Coefficient A: 0.482 Coefficient B: 0.051 Coefficient C: 0.093 Coefficient D: 5.586 Coefficient E: 0.400 Coefficient F: 0.148 Constant G: 10.364 Gender was calculated as 1 for male and 2 for female. [Discrimination step S3] Next, frailty is determined using the frailty score stored in the database. That is, the obtained frailty score is compared with the cut point value calculated in the preliminary survey, and if it is equal to or greater than the cut point value, it is determined that the risk of frailty is high (probability of frailty is low). On the other hand, if it is smaller than the cut point value, it is determined that the risk of frailty is low (probability of frailty is low). This cut point value is obtained from the data and frailty scores of many subjects obtained in the preliminary survey, and specifically, the cut point value is obtained by calculating the values ​​at which the sensitivity and specificity are optimized by ROC curve analysis using the subject data and frailty scores obtained in the preliminary survey. For example, in the examples described below, the cut point value was obtained from a preliminary survey of 667 community-dwelling elderly people, and the values ​​at which the sensitivity and specificity are optimized by ROC curve analysis were calculated (area under the curve = 0.80, sensitivity = 0.840, specificity = 0.693).

[0016] <Risk of falling> Below, we will explain the risk of falling, focusing on the differences from sarcopenia described above. For points not specifically explained, the explanation of sarcopenia described above applies as appropriate. When the subject's motor function is a fall risk, the predetermined formula is the following formula (4), and the predetermined value is a fall risk score. Fall risk score = maximum floor reaction force F / floor reaction force at standing completion point W (4) In the formula, the maximum floor reaction force F and the floor reaction force W at the completion point of standing are as described above. [Discrimination step S3] The fall risk is determined using the fall risk score stored in the database. That is, the obtained fall risk score is compared with the cut point value calculated in the preliminary survey, and if it is equal to or less than the cut point value, the risk of falling is determined to be high. This cut point value is obtained from the data and fall risk score of many subjects obtained in the preliminary survey. Specifically, the cut point value is obtained by calculating the value at which the sensitivity and specificity are optimized by ROC curve analysis using the subject data and fall risk score obtained in the preliminary survey. For example, in the example described below, the cut point value obtained by calculating the value at which the sensitivity and specificity are optimized by ROC curve analysis obtained from the preliminary survey of 456 community-dwelling elderly people was 1.28 for men and 1.21 for women. In this embodiment, the risk of falling refers to the high possibility of falling two or more times in the next year.

[0017] (Other steps) The program of the present invention may be configured to cause a computer to execute steps that are typically set in this type of program, in addition to the steps described above. For example, a step may be further provided in which an exercise menu, recommended meal menu, etc. are stored in a database and an optimal exercise menu, etc. is output based on the discrimination results.

[0018] 〔system〕 A computer in which the program of the above-described embodiment is stored and configured to execute each step can be used as a motor function determination system by combining with the above-described detection device. That is, as shown in Fig. 1, the motor function assessment system 100 of this embodiment comprises a detection device 40 that detects the subject's upward movement as a physical variable, and a computer 1 connected to the detection device 40. The computer 1 stores the above-mentioned computer program, and includes a recording means that receives a signal of data related to the above-mentioned physical variable from the detection device 40 and records the data in association with the subject data, a predetermined value calculation means that substitutes the data related to the above-mentioned physical variable into a predetermined formula to calculate a predetermined value, and a discrimination means that compares the predetermined value with a predetermined threshold value to discriminate the motor function of the subject. It functions as:

[0019] (Recording means) The recording means executes the recording step in the computer program by the computer 1, thereby receiving data related to the physical variables transmitted from the detection device 40, calculating the floor reaction force directly or by substituting the received data into an equation using the acceleration, and creating a graph such as the graph shown in Fig. 3. Then, using the graph created here, the minimum floor reaction force (kgf), maximum floor reaction force F (kgf), and floor reaction force W (kg) at the completion of standing up are calculated, and the time (T1) from recording the minimum floor reaction force point after the start of the standing up movement to measuring the maximum floor reaction force F, and the time (T2) from the start of the standing up movement to the completion of the standing up movement are calculated. The calculated data is stored in the recording medium of the computer 1. This process is carried out up to the point of storing the calculated data. (Predetermined value calculation means) This means is a means for causing the computer to execute the above-mentioned predetermined value calculation step using each piece of data stored in the computer 1 by the above-mentioned recording means, and calculating each of the above-mentioned predetermined values. In other words, by the computer executing the above-mentioned specified value calculation step, the specified value is calculated using the above-mentioned formula (1) or (2) for sarcopenia, the above-mentioned formula (3) for frailty, and the above-mentioned formula (4) for fall risk. (Discrimination means) This means causes the computer 1 to execute the discrimination step, and discriminates motor function by comparing each of the predetermined values ​​stored in the computer 1 with the respective threshold values ​​using the predetermined value calculation means. As a result, for each of sarcopenia, frailty, and fall risk, it is determined whether there is a risk of sarcopenia, whether there is a risk of frailty, and whether there is a risk of falling. (Other means) In the motor function discrimination system of the present invention, in addition to the above-mentioned means, various means can be provided without departing from the spirit of the present invention. Also, other members can be provided. The computer in the motor function discrimination system of the present invention can be integrated with the detection device, rather than being separate from the detection device, as long as it is configured to be capable of inputting and outputting the CPU and the recording medium. The recording medium and database can also be installed in a separate server (including a cloud server) that can be connected using a communication means.

[0020] (Example of use) In this embodiment, the motor function discrimination system 100 has subject A place both feet in a seated position on the detection device 40, and then has subject A stand up. At this time, the floor reaction force acting on the floor from subject A's feet is measured, and the measurement data is transmitted to a computer not shown. Then, by executing the above computer program on a computer that receives the data transmitted from the detection device, the computer is caused to execute each of the above steps and function as each of the above means, thereby making it possible to distinguish each of the above motor functions. [Uses and Effects] The motor function determination system and computer program of the present embodiment can easily and conveniently determine motor function with high accuracy. In addition, the above-mentioned detection device and computer can be installed in a weight scale, so that motor function determination such as evaluation and screening of physical function can be performed on a daily basis. Therefore, it is expected to be used in situations where sarcopenia, frailty and fall risk need to be easily assessed, such as in medical settings, local health and welfare services, and events for the elderly. In addition, since the measurement can be performed in a small space and no measuring staff is required, motor function can be more easily assessed. In addition, the motor function assessment in the motor function assessment system and computer program of the present invention assesses dynamic performance rather than static muscle strength, so that it reflects the physical function of the elderly more than conventional methods and allows for detailed assessment.

[0021] The present invention is not limited to the above-described embodiment, and various modifications are possible without departing from the spirit of the present invention. EXAMPLES

[0022] The present invention will be described in more detail below with reference to examples, but the present invention is not limited to these examples. Example 1 For one subject (male, 75 years old), the floor reaction force during the standing movement with maximum effort was measured using the motor function analysis device zaRitz (product name, model number "BM-220" manufactured by Tanita Corporation) as the detection device. The subject was instructed to stand up with maximum effort (the subject's maximum strength) with both arms folded in front of his chest. The measurement was performed twice, and the higher maximum floor reaction force F was used. In addition, a computer was connected to the detection device via WIFI (registered trademark), and the computer program of the present invention was stored in this computer, and these constituted the motor function discrimination system of the present invention. Then, based on data relating to the subject's force obtained from the detection device, the minimum floor reaction force, the maximum floor reaction force (F), the time T1 (sec) from recording the minimum floor reaction force to recording the maximum floor reaction force F, the time T2 (sec) from recording the maximum floor reaction force F to the completion of standing up, and the floor reaction force W (kg) at the point of completion of standing up were calculated. Then, based on each of the obtained data, the above-mentioned predetermined value calculation step and the above-mentioned discrimination step were executed to discriminate the motor function. The results were as follows: The basic data used to set the formula and threshold values ​​was calculated based on the data obtained by detecting similar ground reaction forces in elderly people living in Tokyo (sarcopenia: 627 people, frailty: 667 people, falls: 456 people). Specifically, formulas (1) to (4) are as follows: Ground reaction force parameters F=80.2kgf, W=63.1kgf, T1=0.41, T2=1.48 -Assessment of sarcopenia Judgment formula: Score(male) = 0.110 x 75 (years) - 0.123 x 80.2 (kgf) - 0.338 = -1.952(1) Sarcopenia score = 1 / ((1+exp(-1×-1.952))=0.124 (a) - Flail determination Judgment formula: Score=0.482×75(years old) +0.051×1-0.093×80.2 (kgf) +5.586×0.41(sec)-0.400×1.48(sec)+0.148×63.1 (kgf) -10.364(3) Frailty score = 1 / ((1+exp(-1×-2.471))=0.078 (b) -Identifying risk of falling Judgment formula: Fall risk score = 80.2 (kgf) ÷ 63.1 (kgf) = 1.27 (4) - About the subjects: Sarcopenia score = 0.124 (at risk), Frailty score = 0.078 (at risk), Fall risk = 1.27 (at risk of falling within 1 year)

Claims

1. A computer program for assessing motor function that causes a computer connected to a detection device that detects an upward movement of a subject as a physical variable to execute the following steps: The motor function of the subject is sarcopenic, a recording step of receiving a signal of data of the physical variable from the detection device and recording the data regarding the physical variable in association with subject data; a predetermined value calculation step of calculating a predetermined value by substituting the recorded data on the physical variables into a predetermined formula, the calculation step including a step of obtaining a maximum floor reaction force F from the physical variables; a calculation step in which the above-mentioned predetermined formula is the following formulas (1) and (a) when the subject is male, and the following formulas (2) and (a) when the subject is female; Score A (male) = coefficient A 1 × age − coefficient B 1 × F − constant C 1 (1) ScoreB (female) = coefficient A 2 × age − coefficient B 2 × F − constant C 2 (2) Sarcopenia score = 1 / (1 + exp (-1 x Score A or Score B)) (a) (where F (kgf) is the maximum floor reaction force) and A discrimination step of comparing the predetermined value with a predetermined threshold value to discriminate the motor function of the subject. A computer program that executes the following:

2. A computer program for assessing motor function that causes a computer connected to a detection device that detects an upward movement of a subject as a physical variable to execute the following steps: The subject's motor function is frail, a recording step of receiving a signal of data of the physical variable from the detection device and recording the data regarding the physical variable in association with subject data; a predetermined value calculation step of substituting the recorded data on the physical variables into a predetermined formula to calculate a predetermined value, the calculation step including a step of obtaining a maximum floor reaction force F from the physical variables, the predetermined formula being the following formulas (3) and (b); Score C = coefficient A × age + coefficient B × gender + coefficient C × F + coefficient D × T1 + coefficient E × T2 + coefficient F × W - constant G (3) Frailty score = 1 / (1 + exp (-1 x Score C)) (b) (In the formula, F (kgf) is the maximum floor reaction force, T1 (sec) is the time from recording the minimum floor reaction force to recording the maximum floor reaction force F, T2 (sec) is the time from recording the maximum floor reaction force F to the completion of standing, and W (kgf) is the floor reaction force at the standing completion point. The standing completion point is the point where the standard deviation of the floor reaction force value per 10 data (0.125 sec) falls below 50 gf.) and A discrimination step of comparing the predetermined value with a predetermined threshold value to discriminate the motor function of the subject. A computer program that executes the following:

3. 3. A motor function assessment system comprising: a detection device which detects an upward movement of a subject as a physical variable; and a computer connected to the detection device, wherein the computer stores the computer program of claim 1 or 2, and functions as a recording means which receives a signal of data relating to the physical variable from the detection device and records the data in association with subject data, a predetermined value calculation means which substitutes the data relating to the physical variable into a predetermined formula to calculate a predetermined value, and a discrimination means which compares the predetermined value with a predetermined threshold value to discriminate the motor function of the subject.

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