JP7080137B2 - Score management device and score management method - Google Patents

Description

The present invention relates to a technique for managing a human evaluation score calculated from data acquired by a device that measures the movement of a human body.

In recent years, problems related to labor in companies have been attracting attention, and not only accounting soundness as a company value, but also the fact that employees are managed in a state of physical and mental health is a corporate value from society. It is becoming more and more appreciated. Therefore, it is required to evaluate the soundness of human beings such as employees of companies. For example, questionnaires are used to evaluate the health of individuals and groups, such as whether individuals or people belonging to a group are in a state of stress and can concentrate on their work. Is common, and the evaluation is based on the answers to the questionnaire. However, since the questionnaire can be answered arbitrarily, the evaluation based on the answer to the questionnaire may be insufficiently objective.

On the other hand, it is known that the state of human health can be measured by a device that can be worn on the body, such as a wearable device. For example, the human condition, such as whether stress is accumulated or whether one can concentrate on work, appears in the movement of the body, so an evaluation score that evaluates the human condition from the data acquired by the accelerometer attached to the body is used. It is possible to calculate. Since it is difficult for humans to intentionally keep controlling their body for a long period of time, the evaluation score based on the movement of the body is highly objective. In addition, since the evaluation score based on the movement of the body is highly objective, it is an advantage that the evaluation scores of a plurality of humans or a plurality of groups can be compared with each other.

In Patent Document 1, it is determined whether the person is in an active state or a stationary state based on the acceleration rhythm calculated from the movement of the human body measured by using a wearable sensor node equipped with an acceleration sensor in the triaxial direction. A technique for calculating the duration of a state and estimating whether or not stress is accumulated due to the distribution shape of data in a histogram of the duration of an active state, specifically, a slope or a variation point is disclosed.

Further, in Patent Document 2, stress is accumulated by the linear sum of the occurrence ratios in a specific range in the distribution shape of the data in the histogram of the duration of the active state obtained in the same manner as the method disclosed in Patent Document 1. A technique for simply estimating whether or not a patent is used is disclosed.

Japanese Patent No. 5588563 WO2016 / 125260

It would be nice if all humans could be equipped with the same sensor in order to calculate an evaluation score that would objectively and mutually comparablely evaluate many humans or groups, but that is not practical. In reality, it is expected that many people will wear different devices. Therefore, there is a need for a mechanism for calculating objective and mutually comparable evaluation scores from data measured by various devices.

There are various devices that can measure body movements in some way. For example, a wearable device equipped with a sensor that detects movement and can be worn on the body, a smartphone equipped with a gyro sensor, and a camera that shoots a human video from the outside rather than being worn on the body measure the movement of the body. Can be used for. There are various forms of wearable sensors. For example, there are a wristband type that is worn on the wrist, a name tag type that is hung from the neck, and a ring type that is worn on the finger.

These various devices have different mechanisms for detecting body movements and different accuracy for detecting body movements. For example, the accelerometer devices provided by each manufacturer may have different sampling intervals, data loss occurrence conditions, error magnitudes, mounting positions, and the like. Therefore, even if the same person wears a plurality of wearable devices at the same time, the data measured by those wearable devices may not match. If the data do not match, the human states such as the active state and the stationary state calculated using the data do not match, and as a result, the human evaluation score may change depending on the device.

An object of the present invention is to provide a technique that enables an objective evaluation score of a human being to be obtained even if the movement of a body is measured by different devices.

In order to achieve the above object, the score management device according to one aspect of the present invention includes a device-to-device conversion unit that converts data related to human body movement measured by the device according to a conversion formula corresponding to the device, and the conversion unit. A score calculation unit that calculates the evaluation score for the human condition by applying the data to a common score calculation formula regardless of the device, and a reliability that calculates the reliability of the evaluation score according to the rules according to the device. It has a calculation unit.

Even if the movement of the body is measured by different devices, it is possible to obtain an objective evaluation score for humans.

It is a figure which shows the system outline of the evaluation information management system using a score management apparatus. It is a block diagram which shows an example of the function of the component of the evaluation information management system shown in FIG. It is a sequence diagram which shows the procedure of the calculation processing of the score in the evaluation information management system shown in FIGS. 1 and 2. It is a sequence diagram which shows the procedure of the score acquisition processing in the evaluation information management system shown in FIGS. 1 and 2. It is a figure which shows the format of the score database shown in FIG. It is a sequence diagram which shows the procedure of the device registration processing in the evaluation information management system shown in FIGS. 1 and 2. It is a figure which shows the example of the structure of the database of the authentication device information shown in FIG. It is a figure for demonstrating the process of device authentication in the score management server shown in FIG. 1 and FIG. It is a figure for demonstrating an example of the calculation method of the evaluation score. It is a figure which shows the display example of the screen of a client. It is a figure which shows the display example of the screen of an application. It is a figure which shows the display example when the application is a personnel evaluation system managed by a company. It is a figure which shows the display example when the application is a corporate information management system in a stock investment judgment support system. It is a block diagram which shows the other example of the function of the component of the evaluation information management system shown in FIG. It is a figure which shows the configuration example of the join table created by the join table creation function shown in FIG. It is a figure which shows the configuration example of the join table created by the join table creation function shown in FIG. It is a figure which shows the display example of the screen of an application.

In this embodiment, a score management device for managing the evaluation score of an individual or a group of human beings and an evaluation information management system using the same will be described. The evaluation score is calculated based on the data related to the movement of the person's body, and the evaluation score indicates the reliability of the score calculated by the type of the terminal that acquired the data and the measurement quality of the data. It is characterized by including.

Hereinafter, embodiments of the evaluation information management system using the score management device will be described with reference to the drawings.

<System overview>
FIG. 1 is a diagram showing a system outline of an evaluation information management system using a score management device.

As shown in FIG. 1, the evaluation information management system has a sensor terminal (TR, TR_A, TR_B: hereinafter, when the individual is not identified) worn by the user (US, US2: hereinafter, all are indicated as US when the individual is not identified). All are indicated as TR), a client (CL) that can connect to the terminal TR via short-range wireless communication, etc., and a score management server (SS) that can connect to the client (CL) via a wireless or wired network (NW). ) And the application (AS), the movement of the person is measured by the sensor (not shown) in the terminal (TR), and the measurement data is acquired.

The terminal (TR) may be a wearable type that the user (US) wears on the body, or may not be worn by the user (US) such as a camera. When the terminal (TR) is a wearable type, the measurement data is associated with the data and the person information as being related to the wearer, and when the terminal (TR) is not worn, by means such as face recognition. Identify and associate the person to be measured. Further, measurement data may be acquired for the group without specifying an individual person such as a group who stayed in a specific room or space. Hereinafter, the terminal (TR) is described as a wearable type having an acceleration sensor, but other means may be used. The terminal (TR) acquires sensor data (hereinafter referred to as 3-axis acceleration data, but other means may be used) relating to the body movement of the user (US) in the in-terminal processing unit (not shown).

The data acquired by the terminal (TR) is stored in the score management server (SS) through the network (NW). The score management server (SS) calculates and stores the evaluation score for a person or a group from the sensor data. When requested by the application (AS) or the client (CL), the score management server (SS) returns an evaluation score.

The application (AS) includes, for example, a POS cash register and a business management system of a company.

The client (CL) is a device such as a mobile phone having an interface with the user (US) such as a screen (CLOD) and fingerprint authentication (not shown), and the network acknowledges that the user (US) has consented to the provision of the score. It is possible to transmit to the score management server (SS) via (NW).

Further, although a plurality of types of terminals (TR) having different forms or different sensors can be used, when registering a new type of terminal B (TR_B) as a target of the score management server (SS), By collecting data in which the same person (US2) wears terminal B (TR_B) and reference terminal A (TR_A) at the same time, the score management server (SS) authenticates terminal B (TR_B) and converts between devices. Model generation and reliability rule generation are performed.

<Block diagram of the entire system>
FIG. 2 is a block diagram showing an example of the functions of the components of the evaluation information management system shown in FIG. Each function in the figure is realized by the cooperation of hardware and software. Further, each of these components has a control unit, a storage unit, and a transmission / reception unit. The control unit is composed of a central processing unit (CPU, not shown), which is a processing unit of a normal computer or the like. The storage unit is composed of a memory device such as a semiconductor storage device or a magnetic storage device. The transmission / reception unit is composed of a network interface such as wired or wireless. In addition, a clock etc. is provided as needed. The arrows in FIG. 2 represent the flow of signals for data and control.

<Terminal (TR)>
As the terminal (TR) shown in FIG. 2 and the assumed terminal A (TR_A) selected as the reference device, for example, a terminal having a name tag shape and being hung from the neck of a person is assumed to be used. However, this is just an example, and other shapes may be used. In many cases, a plurality of terminals (TRs) exist in this series of systems, and are worn by a plurality of persons.

The terminal (TR) has a clock function (TRCK), a sensor (TRSN), a sensor data transmission function (TRSS), and a transmission / reception unit (TRSR), and the storage unit is a user who is a wearer. It holds a user ID (USID) corresponding to (US) and terminal information (TRID) including information on the ID of the terminal itself, the type of the terminal, and measurement conditions. The clock function (TRCK) has a function of holding time information and updating the time information at regular intervals. The time information is periodically updated by connecting to an NTP server (not shown) in order to prevent the time information from deviating from another terminal (TR). The sensor (TRSN) acquires data on the movement of the wearer, and includes, for example, a triaxial acceleration sensor, a gyro sensor, a heart rate sensor, and an electrooculogram sensor. The sensor (TRSN) has any of these three-axis acceleration sensors, gyro sensors, heart rate sensors, electrooculogram sensors, and the like for each terminal (TR).

The terminal (TR) associates the sensor data acquired by the sensor (TRSN) with the information at the time of sensing, and then uses the sensor data transmission function (TRSS) to send and receive the score from the transmitter / receiver (TRSR) through the network (NW) to the score management server. Send to (SS). Although not shown, the terminal (TR) has a storage unit, a control unit, and a power supply, and the storage unit has sensor data and time in addition to the above-mentioned user ID (USID) and terminal information (TRID). Stores information, firmware for sensing, etc. The control unit controls the sensor (TRSN), controls the transmission timing in the data transmission function (TRSS), rewrites the user ID (USID) and the terminal information (TRID), and the like. The power source is connected to a battery or an external power source and maintains the power of the terminal (TRID).

<Score management server (SS)>
The score management server (SS: score management device) includes a transmission / reception unit (SSSR), a storage unit (SSME), and a control unit (SSCO). The score management server (SS) manages data collected from all terminals (TR) and outputs a score in response to a request from an application (AS) or a client (CL). The control unit (SSCO) has a score calculation unit (SSCC), a score acquisition unit (SSCG), and a device registration unit (SSCR).

The score calculation unit (SSCC) has a data reception function (SSCC_RR), a data authentication function (SSCC_AC), a score calculation function (SSCC_CS) as a score calculation unit, and a reliability calculation function (SSCC_CA) as a reliability calculation unit. And a device-to-device conversion function (SSCC_PE) that serves as a device-to-device conversion unit.

The score calculation unit (SSCC) configured in this way receives sensor data from the terminal (TR) through the transmission / reception unit (SSSR) by the data reception function (SSCC_RR), and the data is appropriate by the data authentication function (SSCC_AC). It authenticates something and stores it in the storage unit (SSME) (not shown). In addition, by applying the data to the score calculation program (SSME_PS) in the storage unit (SSME), the evaluation score calculation and reliability calculation by the score calculation function (SSCC_CS) for each person or for each pre-registered group. The reliability is calculated in the function (SSCC_CA) and stored in the score database (SSME_S) in the storage unit (SSME).

Here, when the terminal (TR) that measures the data is other than the reference device described later, device-to-device conversion is performed by the device-to-device conversion function (SSCC_PE). This uses an inter-device conversion program (SSME_PE) to convert the data of the terminal into a form that imitates the data of the reference device, and the data related to the movement of the human body measured by the device is converted to the device. It is a process of converting according to the device-to-device conversion program (SSME_PE) and the device-to-device conversion model (SSCR_GR) which are the corresponding conversion formulas. The conversion formula by the device-to-device conversion program (SSME_PE) or the device-to-device conversion model (SSCR_GR) is the difference between the first data measured by the reference device and the second data measured by another device different from the reference device. Is an equation to reduce.

When device-to-device conversion is performed by the device-to-device conversion function (SSCC_PE), the converted data is applied to the score calculation program (SSME_PS), which is a common score calculation formula regardless of the device, in the score calculation function (SSCC_CS). Thereby, the evaluation score regarding the human condition is calculated, and the reliability of the calculated evaluation score is calculated in the reliability calculation function (SSCC_CA) according to the rule according to the device.

The score acquisition unit (SSCG) outputs a score in response to a request from an application (AS) or a client (CL), and has a score request determination function (SSCG_RG), a score search function (SSCG_SQ), and a score. It has a transmission function (SSCG_SS).

When the score acquisition unit (SSCG) receives the score request, the score request determination function (SSCG_RG) makes a security judgment such as whether the requester is eligible to receive the score and whether the consent of the requester is obtained. By doing so, the evaluation score is authenticated. If the authentication is successful with the score request judgment function (SSCG_RG) and permission is obtained, the score database (SSME_S) is searched by the score search function (SSCG_SQ), and the score transmission function of the requested target is sent. It is transmitted to the requester by (SSCG_SS).

The device registration unit (SSCR) is for registering a new type of device, and has a data reception function (SSCR_RR), an same target determination function (SSCR_JS), and an inter-device conversion model generation function (SSCR_GT). , Has a reliability rule generation function (SSCR_GR). Further, the device registration unit (SSCR) has a questionnaire input unit (SSCR_Q).

The device registration unit (SSCR) has a reference device (here, terminal A (TR_A)) for which the measurement accuracy is already known and the standard score calculation formula is defined by this data, and another type to be newly registered. (Here, referred to as terminal B (TR_B)) is attached to the same person or group at the same time, and the data of both devices is received by the data reception function (SSCR_RR). As described above, since the measurement accuracy of the reference device is already known and the standard score calculation formula is defined by this data, the score calculation program (without converting the measured data) ( The evaluation score can be calculated by applying it to SSME_PE).

Next, the device registration unit (SSCR) determines whether the acquired two types of data are measured for the same target, person, or group by the same target determination function (SSCR_JS). Time-series data on body movements acquired by different devices may have different sampling qualities, such as sampling intervals and probability of data loss, or may be out of phase depending on the wearing position on the body. After correcting this, for example, by converting it to sampling data at the same interval, mechanically compensating for data loss, or shifting the phase, it is possible to check whether both types of data are synchronized, so that the same target can be obtained. It can be determined whether or not the data is measured. Furthermore, a device-to-device conversion model that converts the data of the new device (TR_B) to the data of the reference device (TR_A) by machine learning or the like is generated by the device-to-device conversion model generation function (SSCR_GT), and the device in the storage unit (SSME). It is stored as an inter-conversion program (SSME_PE). At the same time, the reliability of the rule to calculate the reliability of the new device (TR_B) according to the number and total time of the data used for model generation, the accuracy of the conversion model, the frequency of data loss of the new device (TR_B), etc. It is generated by the rule generation function (SSCR_GR). The reliability rule is a standard for performing reliability calculation (SSCC_CA) when the data measured by the terminal B after the registration of the terminal B (TR_B) is input to the score management server (SS). In the case of a terminal with a large defect or error, a low reliability is calculated. The reliability rule (not shown) includes the reference reliability of the terminal B (TR_B) and the attenuation coefficient of the reliability according to the number of samplings of the input data and the loss rate. If it is determined that the new device (TR_B) satisfies a certain reliability, the information of the new device (TR_B) is combined with the authentication device information (SSME_D) in the storage unit (SSME) as an authentication device together with the reliability rule. Is registered.

In addition, if there is response data of a predetermined questionnaire (questionnaire) that serves as a reference for the evaluation score to be calculated, the questionnaire input section contains the questionnaire responses conducted during the period that overlaps with the measurement period of the new device (TR_B). By inputting to (SSCR_Q), the reliability of terminal B (TR_B) can be increased, or a program (SSME_PS) that calculates the evaluation score directly from terminal B (TR_B) without converting to the reference device can be generated. Is also good.

<Application (AS), Client (CL)>
The application (AS) is a system that utilizes the score, and is a screen (ASOD), a reader (ASOD_R), a score provision consent request function (ASAG), a score request function (ASRE), and a control function (ASCO). ), A score receiving function (ASSR), and a transmission / reception unit (ASSR). Further, the application ID (ASID) is stored in the storage unit.

The client (CL) has a screen (CLOD), a personal authentication function (CLRI), a consent acquisition function (CLAG), a score request function (CLRE), and a transmission / reception unit (CLSR). A user ID (USID) is stored in the storage unit.

The application (AS) and the client (CL) configured as described above are means such as password request or fingerprint authentication by the personal authentication function (CLRI) to determine whether the user (UL) is a pre-registered owner. Authenticate using. Then, when the consent to provide the score of the user (UL) is obtained by using the consent acquisition function (CLAG), the score of the user (US) is transmitted to the score management server (SS) through the transmission / reception unit (CLSR). The score request function (CLRE) requests that the application be sent to an application having a predetermined application ID (ASID). At this time, the client (CL) sends the consent to the application (AS), and after giving the information that the consent has been given, the application (AS) requests the score from the score management server (SS) ( ASRE) may be performed.

When the client (CL) requests a score, the score provision consent request function (ASAG) requests the client (CL) to consent to the score provision, for example, via short-range radio. The application (AS) is equipped with a barcode, QR code (QR code is a registered trademark) or IC chip reader (ASOD_R) to send information that the client (CL) has agreed to the application (AS) directly. May be good.

Then, when the score request determination function (SSCG_RG) determines that the score request is not unreasonable in the score acquisition unit (SSCG) of the score management server (SS), the score database is used by the score search function (SSCG_SQ). The score is searched from (SSME_S), and the score is transmitted to the application (AS) by the score transmission function (SSCG_SS).

The application (AS) receives the evaluation score of the person by the score receiving function (ASRO), and by the control function (ASCO), for example, by changing the information and the operation in the application according to the value of the score. To perform the operation of.

<Score calculation processing sequence>
FIG. 3 is a sequence diagram showing a procedure of score calculation processing in the evaluation information management system shown in FIGS. 1 and 2.

In the evaluation information management system shown in FIGS. 1 and 2, when data on the movement of the user (US) is measured by the terminal (TR) and the score is calculated by the score management server (SS), first, the terminal ( In TR), the user (US) registers as the owner (TRUI) in advance, and the user ID (USID) is recorded in the in-terminal storage unit (TRME).

Next, when the predetermined time is reached, the timer activation (TRTK) or the user (US) instructs the activation to start the sensing (TRSE). During that period, the user (US) wears the terminal (TR) so that the terminal (TR) can measure the movement of the user (US). Information such as time information, user ID, and terminal type is added to the sensed data (TRSA), and the sensed data is appropriately recorded in a storage unit (TRME). The sensor data is transmitted to the score management server (SS) by the sensor data transmission function (TRSS) sequentially or when the predetermined sensing period ends.

In the score calculation unit (SSCC) of the score management server (SS), after receiving the data by the data reception function (SSCC_RR), first, the data is acquired by the data authentication function (SSCC_AC) under appropriate terminals and conditions. Confirm.

Then, when the terminal (TR) that measured the data is other than the reference device (SSCC_1), the data of the terminal is used as the data of the reference device by the device-to-device conversion function (SSCC_PE) using the device-to-device conversion program (SSME_PE). Performs device-to-device conversion to convert to a form that imitates. At this time, the conversion formula by the device-to-device conversion program (SSME_PE) or the device-to-device conversion model (SSCR_GR) that performs device-to-device conversion is measured by the first data measured by the reference device and by another device different from the reference device. It is an equation that reduces the difference from the second data.

When the terminal (TR) that measured the data is the reference device, or after performing device-to-device conversion using the device-to-device conversion function (SSCC_PE), the data is applied to the score calculation program (SSME_PS) in the storage unit (SSME). By doing so, the evaluation score calculation in the score calculation function (SSCC_CS) and the reliability calculation in the reliability calculation function (SSCC_CA) are performed for each person or each pre-registered group, and the score management server (SS) is used. It is stored in the storage unit (SSCC_M) and the score database (SSME_S) in the storage unit (SSME).

In this way, by calculating the evaluation score using the data converted by the conversion formula according to the device and further calculating the reliability, the data on the body movement acquired by various devices is objectively related to the human condition. Evaluation score can be obtained.

Further, the conversion formula by the device-to-device conversion program (SSME_PE) or the device-to-device conversion model (SSCR_GR) that performs device-to-device conversion is measured by the first data measured by the reference device and by another device different from the reference device. 2 By using an expression that reduces the difference from the data, the reference device is set in advance, and for other devices, the difference between the data measured by that device and the data measured by the reference device is reduced. Since the data converted so as to be used is used, for example, even if the device is newly added and the accumulated data is small, the findings (for example, the score calculation formula) obtained from the data measured and accumulated by the reference device can be obtained. It is possible to calculate the evaluation score used. In addition, if the score calculation formula by the reference device is changed based on the new knowledge, the knowledge can be reflected in the evaluation scores of all other devices.

<Score acquisition processing sequence>
FIG. 4 is a sequence diagram showing a procedure of score acquisition processing in the evaluation information management system shown in FIGS. 1 and 2.

In the evaluation information management system shown in FIGS. 1 and 2, in the process of requesting score acquisition from the application (AS) to the score management server (SS) and acquiring the score, the application (AS) is a specific person or group. When requesting the acquisition of the evaluation score, first, the score provision consent request function (ASAG) sends the score provision consent request to the client (CL).

In the client (CL), the user (US) is authenticated by the personal authentication function (CLRI), and then the consent (USAG) of the user (US) is obtained by the consent acquisition function (CLAG) through the screen (CLOD) or the like.

The information to the effect that the consent is sent is sent to the application (AS), and the score request is sent to the score management server (SS) by the score request function (ASRE) on the (ASRE_A) that has been given the consent. It should be noted that the consent acquisition to the user (US) is not carried out every time the score is requested, but by obtaining the consent in advance, the score request is carried out directly from the application (AS) to the score management server (SS). You may.

In the score acquisition unit (SSCG), after the score request determination function (SSCG_RG) determines that the score request is appropriate, the score search function (SSCG_SQ) specifies the target individual, group, and period. ). The storage unit (SSME) searches the score database (SSME_S) for the corresponding evaluation score and returns it to the score acquisition unit (SSCG) (SSME_S1), and the evaluation score is transmitted to the application (AS) by the score transmission function (SSCG_SS). Received by the score receiving function (ASRR).

In this way, the transmission / reception unit (SSSR) of the score management server (SS) receives data from the terminal (TR) via the network (NW), and uses the evaluation score via the network (NW). By fulfilling the function of transmitting to the application (AS) that performs the processing, the application (AS) can provide a predetermined processing according to the evaluation score.

Further, in the score acquisition unit (SSCG), when the application (AS) requests the evaluation score, the evaluation score is authenticated, and when the authentication is successful, the evaluation score is transmitted to the transmission / reception unit (SSSR). By sending to the application (AS) via, the rating score can be provided only if the score request is reasonable.

<Score database>
FIG. 5 is a diagram showing the format of the score database (SSME_S) shown in FIG.

As shown in FIG. 5, the score database (SSME_S) shown in FIG. 2 stores an evaluation score (S01) and a reliability (S02) of the value for each user ID (USID) corresponding to an individual. In addition, incidental information regarding the conditions for calculating the evaluation score and the basis of the reliability may also be stored. For example, information such as the date when the score was updated (S03), the type of device used for measurement (S04), and the measured time (S05). The score database (SSME_S) may store information in the same manner in a group unit such as a company or a department instead of an individual unit. In that case, the user ID (USID) is replaced with the group ID (not shown).

The evaluation score returned to the application (AS) by the score transmission function (SSCG_SS) is the value (S01) of the evaluation score itself and its reliability (S02). The evaluation score is a value that evaluates the soundness of the target person or group, but the type of terminal used for measurement, the amount of measured data, the rate of data loss, the time elapsed from the time of measurement to the present, etc. It is thought that the reliability of the value will decrease. Further, the required reliability differs depending on the purpose of use of the application (AS). For example, if it is a simple game that does not cause any interest, the reliability may be low, but it is desired that the score can be calculated by a simple means. High reliability is required for large amounts of money such as corporate stock prices and investments, and for purposes related to the honor of a person. In this way, the score management server (SS) returns the reliability (S02) of the value together with the evaluation score (S01), so that the evaluation score having the reliability (S02) equal to or higher than the reference value on the application (AS) side. It can be determined that only (S01) is used for control (ASCO).

<Sequence of device registration process>
FIG. 6 is a sequence diagram showing a procedure of device registration processing in the evaluation information management system shown in FIGS. 1 and 2.

In the evaluation information management system of this embodiment, the terminal A (TR_A) for which a method of calculating an individual or group evaluation score from the data obtained by the built-in sensor has already been established is set as a reference device. As a specific example, the reference device is a name tag type sensor, and the built-in acceleration sensor acquires acceleration data in the triaxial direction at 50 Hz with almost no loss. As the method of calculating the evaluation score by the terminal A (TR_A), the existing method disclosed in Patent Document 1 and Patent Document 2 is used, and it is confirmed that the evaluation score with sufficient reliability is calculated by this. It is assumed that it has been done. The standard for evaluating reliability is a questionnaire, which is a questionnaire consisting of predetermined items related to the soundness of individuals or groups, such as stress, well-being, and satisfaction with work. The evaluation score is obtained by calculating one value related to soundness from the result. Acceleration data from the terminal A by the same subjects as the respondents is prepared, and a model for estimating the evaluation score from the data is created in advance. This model is stored in the storage unit (SSME) as a score calculation program (SSME_PS) that calculates an evaluation score from the data of the terminal A (TR_A). Answering the questionnaire can be a hassle for the user (US), and there is concern that asking the same question every day will make the answer inaccurate. By using this program (SSME_PS), the user (US) can obtain an objective evaluation score simply by wearing the terminal A without answering the questionnaire.

Next, assume a situation in which it is desired to be able to calculate an equivalent evaluation score using a terminal B, which is a new type of device. At this time, by preparing the same questionnaire and a data set of measurement data of the terminal B (TR_B), a new model for estimating the evaluation score from the terminal B (TR_B) can be newly generated, but a highly reliable model can be generated. It is necessary to collect samples of many subjects in order to obtain them, which is time-consuming. Therefore, by creating an inter-device conversion program (SSME_PE) that converts the measurement data of the terminal B (TR_B) into the same measurement data as that obtained from the terminal A, a score calculation program (SSME_PS) by the conventional terminal A can be created. Make it available on terminal B (TR_B).

Here, as an example, it is assumed that the terminal B is a bracelet-type wearable sensor, and the built-in acceleration sensor has a higher probability of data loss than the terminal A (TR_A). To create an inter-device conversion program (SSME_PE) from terminal B (TR_B) to reference device terminal A (TR_A) and register terminal B (TR_B) in the authentication device information (SSME_D) handled by the score management server (SS). The same person simultaneously wears the terminal A (TR_A) and the terminal B (TR_B), and prepares several sets of data sets for that period.

First, the time of the clock built in the terminal A (TR_A) and the terminal B (TR_B) is synchronized. Request the NTP server (TS) to provide the time information from each of the terminal A (TR_A) and the terminal B (TR_B) (TRA01) (TRB01), receive the sent time information (TS01), and transfer the built-in clock to the NTP server. Synchronize (TRA02) (TRB02). The clock used as a reference here may be another clock such as a clock of a specific PC instead of the NTP server (TS).

Next, when starting the measurement, the user (US) attaches both the terminal A (TR_A) and the terminal B (TR_B) (US01), and presses the switch for starting sensing (US02). It is also possible to use a method in which the start time is noted without pressing the switch of the terminal and only the data from that time is cut out later.

Upon receiving the start command, both terminals perform sensing (TRA10) (TRB10), respectively, and add information such as time, terminal ID, and user ID to the sensing data (TRA11) (TRB11).

When the user commands the end of sensing (US03), both terminals stop sensing (TRA12) (TRB12) and transmit the sensor data to the device registration unit (SSCR) of the score management server (SS) by the data transmission function (TRSS). do.

When the device registration unit (SSCR) receives data from both terminals (SSCR_RR), the device registration unit (SSCR) determines whether the data is the same target, that is, whether the data is measured in the same person / time zone by the same proposal determination function (SSCR_JS). After that, a device-to-device conversion model from terminal B to terminal A is generated (SSCR_GT). At that time, the reference reliability of the terminal B and the reliability evaluation rule of the evaluation score calculated by the terminal B are also generated by the reliability rule generation function (SSCR_GR).

Finally, by recording the conversion model and the reliability rule in the storage unit (SSME), the conversion program registration (SSME_PE1) and the authentication device information registration (SSME_D1) are completed.

In this way, in the device registration unit (SSCR), the reference device and another device different from the reference device are simultaneously attached to the same human body and measured by the reference device and the first data measured by the other device. Based on the second data, the device-to-device conversion model and reliability rule are determined, and other devices are registered together with them, so that the device can be registered even if there is no information on the measurement characteristics of the new device. Can be done.

<Authentication device information>
FIG. 7 is a diagram showing an example of the configuration of the database of the authentication device information (SSME_D) shown in FIG.

The authentication device information (SSME_D) shown in FIG. 2 is a database for managing the information of the device authenticated by the score management server (SS). The evaluation score based on the sensor data acquired by the authenticated device is managed by the score management server (SS), and its reliability is guaranteed.

As shown in FIG. 7, the authentication device information (SSME_D) includes the device type (D01), whether or not it is a reference device (D02), the date when the device was registered (D03), and the reference reliability thereof. (D04), sensor type (D05), reliability calculation rule (D06), and other information are included. The reference reliability (D04) is uniquely determined according to the device type (D01), but the value attenuated according to the total time of the actual measurement data, the sampling interval, etc. is the reliability of the evaluation score (S02). ). For example, the reference reliability (D04) of the terminal B is calculated based on the evaluation result of the device-to-device conversion model to the terminal A. That is, the higher the reference reliability (D04), the more accurately the model can imitate the terminal A.

The sensor type (D05) is classified according to the mounting location and mounting form, or according to the type of sensor used. Since the device-to-device conversion program (SSME_PE) is generated corresponding to each device type (D01), even if the same sensor is attached at different locations, it may be treated as a different device type (D01). .. The sensor type (D05) may be any sensor type (D05) as long as it can acquire time-series data related to human movement. In addition to the acceleration sensor of the name tag type or bangle type wearable terminal, the acceleration sensor built in the smartphone may be used, or the heart rate data or the blinking sensor built in the glasses may be used. As a method of not attaching the sensor, time-series data related to the magnitude and rhythm of movement may be acquired from the face image acquired by the Web camera built in the display of the PC, or time-series data related to the rhythm of keyboard typing may be acquired. You may.

The reliability calculation rule (D06) describes the items of the terminal B (TR_B) that may affect the accuracy of the device-to-device conversion model and their weighting coefficients. For example, the total time of the measured data, the sampling feeling, and the data loss. There is a rate and resolution.

<Device authentication process>
FIG. 8 is a diagram for explaining the device authentication process in the score management server (SS) shown in FIGS. 1 and 2.

It is assumed that the reference device is terminal A and the two types of new devices are terminals B and C, each of which is converted into the data form of terminal A, and the accuracy is evaluated and the reference reliability is generated. For the sake of simplicity, all terminals shall acquire time-series uniaxial acceleration data using accelerometers.

Acceleration data when the same person wears three terminals at the same time is shown as a graph (AA01).

As shown in the graph (AA01), the acceleration data of the terminal B shown by the broken line in the graph is almost synchronized with the acceleration data of the terminal A shown by the solid line in the graph, but the value is as high as 0.3 as a whole. ing. On the other hand, the acceleration data of the terminal C shown by the dotted line in the graph has almost the same center of vibration as the acceleration data of the terminal A shown by the solid line in the graph, but tends to swing more up and down than the acceleration data of the terminal A. be. These differences can easily occur depending on the mounting location, the manufacturer of the sensor, and the like.

As an example of the score calculation process using the score calculation program (SSME_PS) in the score calculation function (SSCC_CS) of the terminal A, a specific time unit (for example, 1 minute) of the continuous acceleration data shown in the graph (AA01) is described. If the value is greater than or equal to a predetermined threshold, it is set to 1 and if it is less than a predetermined threshold, it is set to 0 to binarize static and dynamic. Is calculated.

FIG. 9 is a diagram for explaining an example of a method of calculating an evaluation score.

As shown in FIG. 9, for example, the evaluation score is obtained by using the distribution (AA05) when the cumulative occurrence ratio for each activity duration is shown in a log-log graph, and using the slope of the distribution or the value in a specific range as variables. It is possible to calculate.

As the score calculation formula by the score calculation program (SSME_PS), it is determined based on the above-mentioned acceleration data that the active state in which the human is active and the stationary state in which the human is stationary. It is conceivable to use an equation for calculating the evaluation score based on at least one of the active state in which the human is active and the stationary state in which the human is stationary.

Further, as an example of the same target determination method by the same object determination function (SSCR_JS), the average error (E01) and the correlation coefficient (E02) of the time-series acceleration data with the reference device are obtained, and each of them has a predetermined range. If it is satisfied, there is a method of determining that the measurement is performed on the same target as the reference device (E04). Further, it may be a condition that the loss rate (E03) of the acceleration data is within a predetermined range. If it is determined that they are not the same target, the terminal is not registered for authentication device information (SSME_D1).

Further, as an approach of device-to-device conversion model generation in the device-to-device conversion model generation function (SSCR_GT), the time-series acceleration data by the graph (AA01) is directly approximated from the time-series data of the terminal B to the time-series data of the terminal A. There is a way to generate a model. As another method, the time series data of the terminal A and the terminal B are separated for each specific time unit, and the conversion model from the terminal B to the terminal A is generated by machine learning so that the static and dynamic judgment results match. There is a way to do it.

In this way, in the device-to-device conversion model generation function (SSCR_GT) of the device registration unit (SSCR), whether the person wearing the terminal A is in the active state or the stationary state is determined from the acceleration data measured by the terminal A as the reference device. The device-to-device return model is set so that the state of the person who is determined and determined from the acceleration data measured by the other terminals B and C approaches the state of the person determined from the acceleration data measured by the terminal A. It will be generated and reflected in the device-to-device conversion program (SSME_PE). As a result, it becomes possible to make a judgment close to the judgment from the data of the reference device whether it is an active state or a stationary state from the data of another device, and as a result, a value close to the evaluation score can be obtained.

Here, the result of converting the above-mentioned acceleration data into binarized data is shown in FIG. (AA03).

The higher the error rate (E05) in the binarization result, the larger the deviation of the distribution (AA05), so that the error when calculating the evaluation score increases.

Therefore, in the reliability rule generation function (SSCR_GR) of the device registration unit (SSCR), the active state and the stationary state are determined from the data obtained by converting the acceleration data of the terminals B and C by the conversion formula by the inter-device conversion program (SSME_PE). If the converted binarization error rate (E05), which is the rate of discrepancy between the binarized data and the binarized data for which the active state and the stationary state are determined from the acceleration data of the terminal A, is high, the reference of the terminal. The reliability rule is determined so that the reliability (D04) is low. As a result, the objectivity of the evaluation score can be improved by reflecting how close these states are to the reliability.

The reference reliability (D04) may be determined by a correlation coefficient (E02) with the reference device, a data loss rate (E03), or the like. The evaluation result (E00) shows the difference between the evaluation results of the terminal B and the terminal C as an example. In the reliability rule generation function (SSCR_GR) of the device registration unit (SSCR), the error (E01) is large, the correlation coefficient (E02) is low, and the binarization error rate (E05) is large when compared with the terminal A. ) Is higher, and the data loss rate (E03) is higher, the reference reliability (D04) of the new terminal is determined to be lower. This makes it possible to determine the rules so that the reliability of the evaluation score is high when the data acquired by other devices well represents the movement of the body.

Hereinafter, the processing provided by utilizing the score in the control function (ASCO) of the application (AS) will be specifically described.

One embodiment of the application (AS) includes, for example, a POS register in a supermarket. In that case, it is conceivable to give a discount according to the evaluation score of the purchaser. The client (CL) is assumed to be an electronic device such as a smartphone or tablet that is a point of contact with the purchaser, but other means may also be used.

The application (AS) requests the buyer's evaluation score information at the time of payment at the POS register. At this time, the application (AS) requests the client (CL) whether or not to consent to the score provision by the score request function (ASAG), for example, through short-range radio. The client (CL) authenticates the user (UL) as a pre-registered owner by means of a personal authentication function (CLRI) such as a password request or fingerprint authentication. Then, when the user (UL) consents to the score provision by the score provision consent function (CLAG), the score of the user (US) is transmitted to the score management server (SS) through the transmission / reception unit (CLSR) by a predetermined application ID (US). The score request function (CLRE) conveys a request to send to an application having ASID).

Then, when the control function (ASRC) receives the evaluation score transmitted from the score acquisition unit (SSCG) via the score reception function (ASRR), the control function (ASCO) uses the control function (ASCO) to charge the score according to the value of the score. It is conceivable to give a discount.

FIG. 10 is a diagram showing a display example of a screen (CL0D) of a client (CL). FIG. 11 is a diagram showing a display example of a screen (ASOD) of an application (AS).

As shown in FIG. 10, a screen asking for consent is displayed on the client screen (CLOD), and the application (AS) or the score management server (SS) agrees that the user (US) presses the consent button (CL01). ) Is sent.

Confirmation of consent may be performed using fingerprint authentication (not shown), voice authentication (not shown), or the like instead of the consent button (CL01). Further, the user (US) can have the reader (ASOD_R) of the application (AS) read the barcode (CL02) or QR code (not shown) displayed on the screen, or the IC chip (CL) built-in (CL). A method may be used in which the user (US) is deemed to have agreed by having the reader (ASOD_R) read the reading (not shown).

As shown in FIG. 11, on the screen (ASOD) of the application (AS), the fact that the discount is performed from the billed amount and the discount rate are displayed according to the value of the score.

As an application (AS) according to one embodiment, for example, a personnel evaluation system (ASHR) managed by a company can be considered. Here, too, the system configurations shown in FIGS. 1 and 2 are adopted.

FIG. 12 is a diagram showing a display example when the application (AS) is a personnel evaluation system (ASHR) managed by a company.

Employees are equipped with some kind of authenticated terminal (TR) in advance, and evaluation scores are calculated for each employee or each section or team and stored in the score management server (SS). The personnel evaluation system (ASHR), which is an application (AS), holds an employee ID (HR01), affiliation (HR02), and an individual evaluation (HR03), which is an evaluation of the performance of the employee, in a storage unit (not shown) in the system in advance. is doing.

The application (AS) obtains the team score (HR04) and the reliability (HR05) by requesting the score from the score management server (SS) by the score request function (ASRE). Then, the control function (ASCO) weights the individual evaluation and the team score (HR04), and the sum is calculated as the bonus evaluation (HR06). Here, the reliability of the score (HR05) is the same as the reliability (S02) shown in FIG. 5, and the score may be added only when this is equal to or higher than a certain level.

In this way, by adding the team score, which indicates the soundness of the team, to the personnel evaluation element, it is possible to raise the evaluation of the person who contributed to the team and present a high bonus amount even if the person's own performance is not high. become.

As an application (AS) according to one embodiment, for example, a corporate information management system (ASCI) in a stock investment judgment support system can be considered. Here, too, the system configurations shown in FIGS. 1 and 2 are adopted.

FIG. 13 is a diagram showing a display example when the application (AS) is a corporate information management system (ASCI) in a stock investment judgment support system.

Existing information about the company, company ID (CI01), stock price (CI02), operating profit (CI03), etc. are stored in a storage unit (not shown) in the system in advance.

The application (AS) obtains a company score (CI04) and a reliability (CI05) by requesting a score from a score management server (SS) by a score request function (ASRE). For example, the investment priority (CI06), which is an index used for investment judgment, is calculated by weighting the operating profit (CI03) and the company score (CI04) and totaling them. Here, the reliability of the score (CI05) is the same as the reliability (S02) shown in FIG. 5, and the score may be added only when this is equal to or higher than a certain level.

In this way, by adding the company score, which indicates the soundness of the company, to the elements of the company evaluation, it is considered that the fact that the employees are performing well in a healthy state has the future potential of the company, and it becomes a company with high future potential. It will be possible to decide to prioritize the investment of.

As an application (AS) according to one embodiment, for example, a work style evaluation information management system (ASEP) can be considered.

Here, a score based on the physical rhythm of a person is used as a means for evaluating the effect of a thing (product) or a thing (thing to be carried out), not for the purpose of evaluating a person. In other words, the degree of improvement in the score of the person when using the thing or performing the thing is evaluated as the effect of the target. Here, the scores are the same as those shown in Examples 1 to 3. Further, as the fourth embodiment, a system for evaluating the working style of a meeting is assumed, but it is also possible to apply it as a system for evaluating the effect of a specific product by the same mechanism.

In the past, when evaluating objects such as things and things, only subjective indicators such as user impressions could be obtained. The challenge of subjective indicators is that different people have different evaluation criteria and that they can be influenced by factors other than the essence of the subject, such as the timing of answers and the wording of questions. Therefore, it is possible to objectively evaluate the object by using an index based on the movement of the human body for evaluation. In addition, by calculating the effect in association with the attribute information, it is possible to find a target with a high effect in a specific attribute and utilize it as a standard when selecting a thing or a thing.

FIG. 14 is a block diagram showing another example of the function of the component of the evaluation information management system shown in FIG.

In this example, as shown in FIG. 14, the configurations of the client (CL), the application (AS), and the score management server (SS) are different from those shown in FIG. The score management server (SS) in this example has a score totaling unit (SSSM) instead of the score acquisition unit (SSCG) shown in FIG. Only the difference part will be described below.

The user (US) inputs an activity record (CLRA) through a client (CL) when performing a target activity or using a product. For example, the method of holding the meeting, face-to-face meeting, telephone meeting, or Web meeting is input from the client (CL) of the smartphone.

The client (CL) adds a user ID (USID) and information on the time when the target is performed to the activity record (CLAT), and transmits the activity record to the score management server (SS) by the activity record transmission function (CLSA).

The activity record transmitted from the client (CL) is received by the effect totaling unit (SSSM) of the score management server (SS) (not shown), and is already stored at a specific timing when the timer is started (not shown). The score data of the user in the relevant day or time zone is searched from the score database (SSME_S) by the score search function (SSSM_SQ), and the join table is created together with the activity record data by the join table creation function (SSSM_CT).

15 and 16 are diagrams showing a configuration example of a join table created by the join table creation function (SSSM_CT) shown in FIG.

In the join table creation function (SSSM_CT), first, the reference score information table (SSSM_A) shown in FIG. 15 is created. The reference score information table (SSSM_A) is a table in which a reference score (A01) is calculated from past scores in association with a user ID (USID) and stored together with the reliability (A02) of the value. In order to display the effect for each attribute later in the application (AS), information on the attribute (A00) such as job title, job type, gender, and classification by questionnaire may be merged.

The reference score (A01) indicates the average score that serves as a reference for each user, and is defined by, for example, the average value of the scores for the past three days or one month stored in the score database (SSME_S). The average.

Next, the join table creation function (SSSM_CT) creates an activity-score join table (SSSM_T). As shown in FIG. 16, the activity-score join table (SSSM_T) is associated with the activity record (T04) for each user ID (USID) and date (T00), and the evaluation score (SSME_S) acquired from the score database (SSME_S). It is a table for storing T01).

Here, as an example of the method of calculating the effect (T02), the difference between the reference score (A01) and the evaluation score (T01) on the day can be used as the effect (T02). In other words, whether or not the evaluation score of the user on the day when the activity is performed is higher than normal is regarded as the target effect. Further, in order to visualize the effect in an easy-to-understand manner, an effect category (T03) in which the effect is divided into five stages may be added.

In this way, the effect totaling unit (SSSM) acquires the user's activity record from the client (CL), and calculates the effect based on the acquired activity record and the evaluation score stored in the score database (SSSM_SQ). become.

FIG. 17 is a diagram showing a display example of a screen (ASOD) of an application (AS), and shows a display example when the application (AS) is a work style evaluation information management system (ASEP).

The system in this embodiment is assumed to be a Web application, but other forms may be used.

When the operator (not shown) wants to check the work style evaluation information on this system, the attribute selection button (EP02) wants to display the target work style classification with the target selection button (EP01). When each of the categories is selected and the request transmission button (EP03) is pressed, the effect request is transmitted from the application (AS) by the effect request function (ASRE).

When the score management server (SS) receives the effect request sent from the application (AS), the effect aggregation function (SSSM_SE) of the score management server (SS) activates the activity-score join table (SSSM_T) based on the condition of the effect request. ) Aggregate the values related to the above effects. In this tabulation, the average value of the effect (T02) is calculated according to the type and attribute (T00) of the activity record (T04), and the number of cases for each effect category (T03) is totaled.

Finally, the effect transmission function (SSSV_SS) of the score management server (SS) transmits the aggregated result to the application (AS) through the transmission / reception unit (SSSR).

When the effect reception function (ASRO) of the application (AS) receives the aggregated result transmitted from the score management server (SS), the control function (ASCO) reflects the received result and the effect in the screen (ASOD). It is displayed in the display area (EP10).

For example, as shown in FIG. 17, the average value of the effects can be displayed for each type and attribute of the conference, and the distribution of the number of effect categories can be displayed as a histogram. As a result, the operator of this system can confirm that the effect differs depending on the attribute even if the target (working style) is the same, and utilize it to select a highly effective target (working style) according to the attribute. be able to.

As described in Example 4, the present invention is a score management device, which is a device-to-device conversion unit that converts data related to human body movement measured by a device according to a conversion formula corresponding to the device. , The score calculation unit that calculates the evaluation score for the human condition by applying the converted data to a common score calculation formula regardless of the device, and the reliability of the evaluation score according to the rules according to the device. A reliability calculation unit for calculating, a transmission / reception unit that receives the data from the device via the communication network and transmits the evaluation score to the application device that performs processing using the evaluation score via the communication network. The device has an effect totaling unit that acquires a human activity record in which data related to body movement is measured and calculates the effect based on the activity record and the evaluation score, and the application device has the said. It is characterized by displaying and outputting the effect calculated by the effect totaling unit.
In this way, by using an index based on the movement of the human body to evaluate the effects of things (commodities) and things (things to be carried out), it is possible to objectively evaluate things and things.

Although the embodiments of the present invention have been described above, the present invention is not limited to the above embodiments, and various modifications can be made, and it is possible to appropriately combine the above-described embodiments. It will be understood by the trader.

TR, TR2 ~ 3 ... Terminal, US, US2 ~ 3 ... User, NW ... Network, SS ... Score management server, AS ... Application, CL ... Client

Claims (13)

An inter-device conversion unit that converts data related to human body movements measured by the device according to the conversion formula corresponding to the device, and
A score calculation unit that calculates the evaluation score for the human condition by applying the converted data to a common score calculation formula regardless of the device.
It has a reliability calculation unit that calculates the reliability of the evaluation score according to a predetermined reliability rule.
The reliability rule includes a reference reliability uniquely determined for the device and a reliability calculation rule indicated by an attenuation coefficient based on at least one of measurement period, sampling interval, data loss rate, and resolution.
Score management device. A reference device that can calculate the evaluation score by applying it to the score calculation formula without converting the measured data is set in advance.
The conversion formula is a formula for reducing the difference between the first data measured by the reference device and the second data measured by another device different from the reference device.
The score management device according to claim 1. Based on the first data measured by the reference device and the second data measured by the other device when the reference device and another device different from the reference device are simultaneously attached to the same human body. Further having a device registration unit for determining the conversion formula and the reference reliability and registering the other device together with the conversion formula and the reliability rule.
The score management device according to claim 2. The score calculation formula is a formula for calculating the evaluation score based on at least one of an active state in which a human is active and a stationary state in which a human is stationary.
The device registration unit determines whether the human is in an active state or a stationary state from the first data measured by the reference device, and determines the human condition from the second data measured by the other device. The conversion formula is determined so as to approach the human condition determined from the first data measured by the reference device.
The score management device according to claim 3. The device registration unit has binarized data in which the active state and the stationary state are determined from the data obtained by converting the second data by the conversion formula, and binarized data in which the active state and the stationary state are determined from the first data. If the rate of inconsistency with is high, the reference reliability is determined so that the reliability is low.
The score management device according to claim 4. If the correlation between the body movement represented by the second data and the body movement represented by the first data is high, the device registration unit has high reliability, and the second data is often missing. For example, the reference reliability is determined so that the reliability is low.
The score management device according to claim 4. Further comprising a transmission / reception unit that receives the data from the device via the communication network and transmits the evaluation score to the application device that performs processing using the evaluation score via the communication network.
The score management device according to claim 1. A score acquisition unit that authenticates the evaluation score when the application device requests the evaluation score, and transmits the evaluation score to the application device via the transmission / reception unit when the authentication is successful. Have more
The score management device according to claim 7. The application device calculates and presents a bonus evaluation according to the evaluation score.
The score management device according to claim 7. The application device calculates and presents an investment priority according to the evaluation score.
The score management device according to claim 7. An activity record is obtained that records a human activity for which data on body movements are measured by the device, and the effect of a predetermined object to which the activity is related is calculated based on the activity record and the evaluation score. It has an effect totaling unit to send to the application device.
The application device displays and outputs the effect calculated by the effect totaling unit.
The score management device according to claim 7. When an attribute that can classify the target is specified, the effect totaling unit calculates the effect of the activity on the attribute.
The application device displays the effect of the target in the attribute calculated by the effect totaling unit.
The score management device according to claim 11. Inter-device conversion processing that converts data related to human body movement measured by the device according to the conversion formula according to the device, and
A score calculation process for calculating the evaluation score for the human condition by applying the converted data to a common score calculation formula regardless of the device, and
The computer executes a reliability calculation process for calculating the reliability of the evaluation score according to a predetermined reliability rule.
The reliability rule includes a reference reliability uniquely determined for the device and a reliability calculation rule indicated by an attenuation coefficient based on at least one of measurement period, sampling interval, data loss rate, and resolution.
Score management method.

Images