Analytical equipment, analytical method, and program

Abstract

To provide an analyzer that allows a manager to conduct analysis required for taking care of the mental condition of a worker.SOLUTION: An analyzer 10 according to the present disclosure comprises: an acquisition unit 11 that acquires sensor information detected by using a sensor mounted on an input device operated by an analysis subject; a management unit 12 that manages schedule information including the schedule for at least one business operation related to the analysis subject; a generation unit 13 that generates, by using the sensor information, a feeling value of the analysis subject when the analysis subject executes the business operation; and an analysis unit 14 that analyzes the feeling of the analysis subject by using the feeling value.SELECTED DRAWING: Figure 1

Description

[[Technical Field]]

[0001] The present disclosure relates to an analyzer, an analysis method, and a program. [[Background Art]]

[0002] In recent years, with the popularization of telecommuting, cases where telecommuters and managers communicate directly have decreased. In such cases, it becomes difficult for managers to obtain information about the mental state of telecommuters, which is normally acquired through direct communication. As a result, it becomes difficult for managers to appropriately care for the mental state of telecommuters.

[0003] Patent Document 1 discloses a configuration of a detection device that measures pulse waves using a touch pen or the like and detects whether a subject is experiencing negative emotions such as brain fatigue or anxiety. [[Prior Art Literature]] [[Patent Literature]]

[0004] [[Patent Document 1]] Japanese Unexamined Patent Application Publication No. 2020-168415 [[Summary of the Invention]] [[Problem to be Solved by the Invention]]

[0005] The detection device disclosed in Patent Document 1 measures pulse waves in the morning and afternoon, and detects whether negative emotions are occurring using the measured pulse waves. However, even when using the detection device disclosed in Patent Document 1, it is not possible to analyze which types of daily work affect the worker's mental state, and there is a problem that managers cannot sufficiently care for the worker's mental state.

[0006] One object of the present disclosure is, in view of the above problem, to provide an analyzer, an analysis method, and a program that enable managers to perform analysis necessary for caring for workers' mental state. [Means for solving the problem]

[0007] An analysis apparatus according to a first aspect of this disclosure includes: an acquisition unit that acquires sensor information detected using a sensor mounted on an input device operated by the person being analyzed; a management unit that manages schedule information including the schedule for at least one task related to the person being analyzed; a generation unit that generates an emotional value of the person being analyzed when the task is performed using the sensor information; and an analysis unit that analyzes the emotions of the person being analyzed using the emotional value.

[0008] An analysis method according to a second aspect of this disclosure acquires sensor information detected using a sensor mounted on an input device operated by the person being analyzed, acquires schedule information including the schedule for at least one task related to the person being analyzed, generates an emotional value of the person being analyzed when the task is performed using the sensor information, and analyzes the emotions of the person being analyzed using the emotional value.

[0009] A program according to a third aspect of this disclosure involves causing a computer to acquire sensor information detected using a sensor mounted on an input device operated by the person being analyzed, acquire schedule information including the schedule for at least one task related to the person being analyzed, generate an emotional value of the person being analyzed when the task is performed using the sensor information, and analyze the emotions of the person being analyzed using the emotional value. [Effects of the Invention]

[0010] This disclosure provides analytical devices, analytical methods, and programs that enable managers to perform analyses necessary to care for the mental state of their employees. [Brief explanation of the drawing]

[0011] [Figure 1] This is a diagram showing the configuration of the analytical apparatus according to Embodiment 1. [Figure 2] This is a flowchart of the analytical process performed in the analytical apparatus according to Embodiment 1. [Figure 3] This is a diagram showing the configuration of the analysis system according to Embodiment 2. [Figure 4] This is a diagram showing the configuration of a mouse according to Embodiment 2. [Figure 5] This is a diagram showing the configuration of a mouse according to Embodiment 2. [Figure 6] This is a flowchart of the analytical process performed in the analytical apparatus according to Embodiment 2. [Figure 7] This figure shows the sensor information according to Embodiment 2. [Figure 8] This is a diagram showing planned information according to Embodiment 2. [Figure 9] This figure shows the emotion value associated with the sensor information according to Embodiment 2. [Figure 10] This figure shows the sentiment values ​​aggregated for each task according to Embodiment 2. [Figure 11] This figure shows the relationship between date and sentiment value according to Embodiment 2. [Figure 12] This figure shows Russell's annular model according to Embodiment 2. [Figure 13] These are configuration diagrams of the analytical apparatus according to each embodiment. [Modes for carrying out the invention]

[0012] (Embodiment 1) Embodiments of this disclosure will be described below with reference to the drawings. An example of the configuration of the analysis device 10 according to Embodiment 1 will be described using Figure 1. The analysis device 10 may be a computer device that operates by a processor executing a program stored in memory. The analysis device 10 may be, for example, a server device, or a communication device that communicates with other computer devices via a network.

[0013] The analysis device 10 includes an acquisition unit 11, a management unit 12, a generation unit 13, and an analysis unit 14. The acquisition unit 11, the management unit 12, the generation unit 13, and the analysis unit 14 may be software or modules that execute processing when a processor runs a program stored in a memory. Alternatively, the acquisition unit 11, the management unit 12, the generation unit 13, and the analysis unit 14 may be hardware such as circuits or chips.

[0014] The acquisition unit 11 acquires sensor information detected using a sensor mounted on an input device operated by a subject to be analyzed. The input device is, for example, a device operated when the subject to be analyzed inputs information to a computer device, and may be, for example, a keyboard, a touch panel, a mouse, or the like.

[0015] The sensor mounted on the input device may be, for example, a sensor that detects biological information related to the subject to be analyzed who operates the input device, or a sensor that detects operation information of the input device, or may be both of these sensors. The sensor information may be biological information, may be operation information, or may include both of these types of information.

[0016] The acquisition unit 11 may acquire sensor information from the sensor via a network, for example. The acquisition unit 11 may acquire sensor information from the sensor via a wireless line or a wired line, for example. The wireless line may be, for example, a mobile communication line provided by a mobile communication carrier, or a communication line using a wireless LAN (Local Area Network). Alternatively, the wireless line may be a communication line using Bluetooth (registered trademark), which is a short-range wireless communication system.

[0017] The management unit 12 manages schedule information, which includes the schedule for at least one task related to the person being analyzed. Managing schedule information can also be rephrased as saving schedule information, accumulating schedule information, etc. A task refers to the work content performed by the person being analyzed, and may include, for example, meetings, document creation, presentations, training, business trips, etc., but examples of tasks are not limited to these. A task schedule may also include information indicating the date on which the task will be performed, the start time, and the end time of the task. Schedule information may include the schedule for one task, or it may include the schedules for two or more tasks. The management unit 12 may acquire schedule information from other devices or systems that manage schedule information and manage the acquired schedule information. Alternatively, the management unit 12 may manage schedule information entered by the operator of the analysis device 10. The operator of the analysis device 10 may be, for example, the employee who is the person being analyzed, or the manager who is the supervisor of the person being analyzed.

[0018] The generation unit 13 uses sensor information to generate emotional values ​​for the person being analyzed when performing a task. The emotional value is a numerical representation of the person's emotions. Emotions may be classified into categories such as happy, angry, sad, and relaxed, and these emotions may be further subdivided. A higher numerical value for an emotional value may indicate that the person being analyzed feels that emotion more strongly. Emotions may be represented using emotional values ​​for any one of the emotions (happy, angry, sad, relaxed), or using emotional values ​​for two or more emotions. For example, an emotion may be represented by a combination of multiple emotional values, such as x being the emotional value for happy and y being the emotional value for angry. x and y may be positive numbers, for example.

[0019] The analysis unit 14 analyzes the emotions of the subject using emotion values. For example, the analysis unit 14 may determine whether the emotion value is greater than or less than a predetermined value. Furthermore, the analysis unit 14 may determine which tasks the subject is stressed about or which tasks they are approaching positively by generating emotion values ​​for each task. For example, if the emotion value for joy or pleasure is high, it may be determined that the subject is approaching that task positively, and if the emotion value for anger or sadness is high, it may be determined that the subject is stressed about that task. The predetermined value may be determined, for example, by statistically processing the emotion values ​​of multiple people. The predetermined value may also be called a threshold. The emotion values ​​of multiple people may be, for example, the emotion values ​​of people belonging to a group of people who share common characteristics. Common characteristics may include, for example, people who have left the company, people who have taken a leave of absence from the company, people who have served as project leaders, new employees, etc.

[0020] Next, the flow of the analysis process performed in the analysis device 10 according to Embodiment 1 will be explained using Figure 2. First, the acquisition unit 11 acquires sensor information detected using a sensor mounted on an input device operated by the person being analyzed (S11). Next, the management unit 12 acquires schedule information including the schedule for at least one task related to the person being analyzed (S12). Next, the generation unit 13 uses the sensor information to generate the emotional value of the person being analyzed when they perform the task (S13). Next, the analysis unit 14 uses the emotional value to analyze the emotions of the person being analyzed (S14).

[0021] As explained above, the analysis device 10 performs an analysis using schedule information, which includes the schedule for at least one task, and emotion values ​​generated using sensor information. This allows the analysis device to understand the emotions of the person being analyzed regarding each task, and managers can use the analysis results to understand the mental state of the employee who is being analyzed.

[0022] (Embodiment 2) Next, an example of the configuration of the analysis system according to Embodiment 2 will be described using Figure 3. The analysis system includes an analysis device 10, an input device 20, a business system 30, and a display device 40. The input device 20 may be, for example, a keyboard, a touch panel, a mouse, etc. The business system 30 may be, for example, a system that manages the work schedules of employees or workers. The work schedule means scheduled information. The business system 30 may be a system in which at least one or more computer devices work in cooperation. Employees or workers may transmit information entered into their respective terminals to the business system via the network. The display device 40 displays the analysis results performed by the analysis device 10. The analysis device 10 may transmit information regarding the analysis results to the display device 40 via the network. The display device 40 may be a computer device having a display.

[0023] Figure 3 shows the business system 30 and the display device 40 as separate devices from the analyzer 10, but the analyzer 10, the business system 30, and the display device 40 may be configured as an integrated device. Alternatively, only one of the analyzer 10 or the business system 30 may be configured as an integrated device with the analyzer 10.

[0024] Here, an example of the configuration of a mouse used as an input device 20 will be described using Figures 4 and 5. Figure 4 shows a mouse as viewed from above when placed on a flat surface. Figure 5 shows a mouse as viewed from the side when placed on a flat surface. The mouse has a left button 21, a right button 22, a central part 23, a rear part 24, and a side part 25. Sensors may be placed on the left button 21, the right button 22, the central part 23, the rear part 24, and the side part 25, respectively. The sensors may be, for example, biometric sensors that detect the biological information of the mouse operator, pressure sensors that detect the pressure when the mouse operator grips the mouse, or acceleration sensors that detect the acceleration of the mouse. The biometric sensors may be, for example, a pulse meter, a sweat sensor, a body temperature sensor, etc. For example, a pulse meter may be placed on the left button 21, a sweat sensor on the right button 22, and a pressure sensor on the side part 25. Furthermore, an acceleration sensor may be placed in the central section 23, and a body temperature sensor may be placed in the rear section 24. The placement of the various sensors is not limited to this, and their placement may be changed. In addition, the mouse may have a built-in communication function, and information detected by the various sensors may be transmitted to the analysis device 10 via the network.

[0025] Furthermore, if a keyboard, touch panel, or the like other than a mouse is used as the input device 20, multiple sensors may be arranged on the input device 20, similar to a mouse.

[0026] Next, the flow of the analysis process performed in the analysis apparatus 10 according to Embodiment 2 will be explained using Figure 6. First, the acquisition unit 11 acquires sensor information from the input device 20 (S21). For example, the acquisition unit 11 may acquire sensor information from the input device 20 periodically, or it may acquire sensor information at any timing when information instructing the operator of the analysis apparatus 10 to acquire sensor information is input. In addition, the acquisition unit 11 may acquire all the sensor information detected by each sensor installed in the input device 20, or it may acquire sensor information detected by at least one of the multiple sensors installed in the input device 20. Furthermore, the input device 20 may periodically detect sensor information and transmit the sensor information to the acquisition unit 11 each time it detects sensor information, or it may transmit sensor information detected at different timings to the acquisition unit 11 all at once.

[0027] Figure 7 shows the sensor information acquired by the acquisition unit 11. The date and time indicate the time when the sensor placed, installed, or built into the input device 20 detected the sensor information. Figure 7 shows that the sensor detects sensor information every minute and transmits the detected information to the acquisition unit 11. The employee ID is identification information that identifies the employee operating the input device 20. For example, the input device 20 may detect a fingerprint, etc., and transmit an employee ID pre-associated with the fingerprint to the acquisition unit 11. Alternatively, if the employee operating the input device 20 is predetermined, the predetermined employee ID may be associated with the sensor information acquired from the input device 20. Alternatively, the employee operating the input device 20 may input their employee ID into a terminal, etc., and the employee ID may be transmitted from the terminal to the acquisition unit 11 via the network. Figure 7 shows that the sensor information acquired by the acquisition unit 11 from the input device 20 is sensor information relating to the employee identified by employee ID_a.

[0028] Pressure, acceleration, body temperature, and pulse rate are sensor information obtained from the input device 20. The unit of pressure is Pa (Pascal), and the unit of acceleration is m / s². 2(meters / second) is the unit for body temperature, and the unit for body temperature is °C (degrees). The unit for pulse rate, bpm, stands for beats per minute and indicates the number of beats per minute.

[0029] The acquisition unit 11 may send a request message to the input device 20 requesting the acquisition of sensor information including employee ID_a, and receive a response message in response to the request message containing the sensor information of the employee identified by employee ID_a. Alternatively, the acquisition unit 11 may send a request message to the input device 20 containing information specifying the type of sensor information, and receive the specified sensor information from the input device 20. Alternatively, the acquisition unit 11 may send a request message to the input device 20 containing information specifying a period, and receive sensor information detected during the specified period from the input device 20.

[0030] Returning to Figure 6, the management unit 12 then retrieves the schedule information of the employee identified by employee ID_a from the business system 30 (S22). For example, the management unit 12 may send a request message to the business system 30 requesting the acquisition of schedule information including employee ID_a, and receive a response message containing the schedule information of the employee identified by employee ID_a as a response to the request message. The schedule information may be information associated with employee ID_a, such as the schedule content, start date, end date, and tags, as shown in Figure 8. The tags are set according to the schedule content. For example, different types of meetings, such as the XX meeting and the YY meeting, will both be tagged with "meeting". XX and YY may represent the names of the meetings. The management unit 12 may also include information indicating the period in the request message and acquire schedule information for the specified period from the business system 30.

[0031] Returning to Figure 6, the generation unit 13 then calculates the emotion value for each task (S23). Here, when calculating the emotion value for each task, the generation unit 13 first generates emotion values ​​using sensor information for each date and time, as shown in Figure 7. For example, the generation unit 13 may generate emotion values ​​from the sensor information detected for each date and time using a learning model that takes sensor information as input and outputs emotion values. For example, a learning model may be generated by performing machine learning using sensor information as training data and emotion values ​​as ground truth data. The emotion value as ground truth data may be, for example, the answer to the inquiry, "What numerical value represents the emotion a person felt when the sensor information was detected?"

[0032] Figure 9 shows the emotion values ​​output when sensor information for each day and time is input into the learning model. In Figure 9, for example, the emotion values ​​for joy, anger, sadness, and pleasure are shown as integer values ​​within a predetermined range. For example, the larger the value, the stronger the emotion is felt. In other words, the larger the emotion value for anger, the stronger the feeling of anger.

[0033] The generation unit 13 generates emotion values ​​for each date and time, and then uses the schedule information in Figure 8 to calculate emotion values ​​for each task. For example, the generation unit 13 adds up the emotion values ​​for each emotion (joy, anger, sadness, pleasure) for the XX meeting from 9:00 AM to 10:00 AM, from the emotion values ​​for each date and time shown in Figure 9. In this way, the emotion values ​​for joy, anger, sadness, pleasure are aggregated for each task. Figure 10 shows the emotion values ​​aggregated for each task. Furthermore, the generation unit 13 may aggregate emotion values ​​for each tag. For example, in the example in Figure 10, there are two tasks with "meeting" set as a tag, so the emotion values ​​for tasks with "meeting" set as a tag may be added up.

[0034] Returning to Figure 6, the analysis unit 14 then determines whether a specific emotional value has exceeded a threshold (S24). The specific emotional value may be, for example, the emotional values ​​of anger and sadness, which are included in the negative emotional values ​​among joy, anger, sadness, and pleasure. The threshold may also be calculated using, for example, the emotional values ​​of past employees who have left or taken leave of absence. Past employees who have left or taken leave of absence may be those who have left or taken leave of absence due to some stressor.

[0035] For example, the analysis unit 14 accumulates emotional values ​​for each task related to past employees who have left the company or are on leave for a predetermined period. Specifically, the analysis unit 14 may accumulate emotional values ​​for anger and sadness among the emotional values ​​for each task, such as creating presentation materials, for a predetermined period such as one week or one month. Alternatively, the analysis unit 14 may accumulate emotional values ​​for anger and sadness among the emotional values ​​for each tag, such as meeting tags, for a predetermined period such as one week or one month. Furthermore, the analysis unit 14 may calculate the average of the weekly or monthly cumulative emotional values ​​of multiple past employees who have left the company or are on leave, and set the average as a threshold.

[0036] The analysis unit 14 determines, for example, whether the cumulative value of negative sentiment for each task related to employee ID_a exceeds a threshold. If the threshold is, for example, the average of the cumulative values ​​over one week, the analysis unit 14 determines whether the cumulative value of negative sentiment for each task related to employee ID_a over a period of less than one week exceeds the threshold. Also, if the threshold is the average of the cumulative values ​​over one month, the analysis unit 14 determines whether the cumulative value of negative sentiment for each task related to employee ID_a over a period of less than one month exceeds the threshold.

[0037] For example, in Figure 11, the horizontal axis represents the date and the vertical axis represents the emotion value. In Figure 11, the horizontal line represents the threshold, and the line showing the increase in emotion value over time represents the cumulative value of negative emotion values ​​for a particular task related to employee ID_a. The threshold is, for example, the average of the cumulative values ​​over one month. For example, Figure 11 shows the threshold for the task of creating presentation materials and the cumulative value of negative emotion values ​​related to creating presentation materials for employee ID_a. In addition to what is shown in Figure 11, analyses of thresholds and cumulative values ​​for other tasks such as meetings and training are also performed. Figure 11 shows that in late September 2021, the cumulative value of negative emotion related to the task of creating presentation materials for employee ID_a exceeded the threshold.

[0038] The analysis unit 14 outputs an alert to the display device 40 (S25) if it determines that a specific emotional value, for example, a negative emotional value, exceeds a threshold. For example, the analysis unit 14 may send a message to the display device 40 indicating that employee ID_a's negative emotional value exceeds a threshold. Alternatively, the analysis unit 14 may send a message to a terminal held by an administrator or the like. For example, if the negative emotional value for work related to creating presentation materials exceeds the threshold less than one month after the emotional value has accumulated, it indicates that creating presentation materials is a source of stress for employee ID_a. The analysis unit 14 may also analyze that the earlier the accumulated emotional value exceeds the threshold, the higher or more serious the employee's stress level is. The analysis unit 14 may also send such analysis results to the display device 40.

[0039] The analysis unit 14 terminates processing if it determines that a specific emotional value, such as a negative emotional value, does not exceed a threshold. For example, if the negative emotional value for the task of creating presentation materials does not exceed a threshold even after one month of accumulating emotional values, it indicates that creating presentation materials is not a source of stress for employee ID_a.

[0040] As described above, the analysis system according to Embodiment 2 determines whether an employee's negative emotional value exceeds a threshold for each task or tag. The threshold may be set based on the negative emotional values ​​of former or current employees who are presumed to have experienced significant stress in the past. Therefore, if the analysis system notifies the manager that an employee's negative emotional value exceeds the threshold, the manager can provide mental health support to that employee.

[0041] Furthermore, while we have shown examples of the analysis unit 14 performing analysis using negative emotion values, it is not limited to this. For example, the analysis unit 14 may also perform analysis using positive emotion values ​​that indicate positive emotions such as joy and pleasure.

[0042] For example, the analysis unit 14 may set thresholds using positive emotional values, such as those of employees who successfully led a project or those who were not late or absent without notice. Furthermore, the analysis unit 14 may determine whether the cumulative value of an employee's positive emotional values ​​exceeds the threshold set using positive emotional values. For example, a manager may determine that an employee's mental state is stable if the cumulative value of an employee's positive emotional values ​​exceeds the threshold set using positive emotional values. Also, if the cumulative value of an employee's positive emotional values ​​in a particular task exceeds the threshold set using positive emotional values, the manager may determine that the employee is positively engaged in that task and increase the employee's allocation of that task. The way managers utilize the analysis results is not limited to what has been described above.

[0043] (Modified version of Embodiment 2) Next, a modified example of Embodiment 2 will be described regarding the generation of emotion values ​​in the generation unit 13. Figure 12 is a diagram of Russell's annular model. Russell's annular model classifies emotions based on two axes, a vertical axis and a horizontal axis. The horizontal axis represents Valence, which means pleasant / unpleasant emotions, and the vertical axis represents Arousal, which indicates whether one is awake or sleepy. Furthermore, this two-dimensional plane has HAPPY in the first quadrant, ANGRY in the second quadrant, SAD in the third quadrant, and RELAXED in the fourth quadrant. Emotion values ​​are quantitatively assigned to each event value based on the acquired biological information, determining which value the emotion of the subject corresponds to. For example, emotion values ​​may be assigned to one of the first to fourth quadrants, and the value may be determined according to the distance between the assigned position and the origin.

[0044] Allocation based on biometric information may be performed according to a learning model. For example, a learning model may be generated by using biometric information as training data and the position in Russell's torus model associated with that biometric information as ground truth data through machine learning.

[0045] After the generation unit 13 generates sentiment values ​​based on Russell's annular model, the analysis is performed in the analysis unit 14, similar to the second embodiment.

[0046] Figure 13 is a block diagram showing an example configuration of the analysis device 10 described in the above-described embodiment. Referring to Figure 13, the analysis device 10 includes a network interface 1201, a processor 1202, and memory 1203. The network interface 1201 may be used to communicate with a network node. The network interface 1201 may include, for example, a network interface card (NIC) compliant with the IEEE 802.3 series. IEEE stands for Institute of Electrical and Electronics Engineers.

[0047] The processor 1202 reads and executes software (computer programs) from the memory 1203 to perform the processing of the analysis device 10 as described using a flowchart in the above embodiment. The processor 1202 may be, for example, a microprocessor, an MPU, or a CPU. The processor 1202 may include multiple processors.

[0048] Memory 1203 is composed of a combination of volatile and non-volatile memory. Memory 1203 may also include storage located away from the processor 1202. In this case, the processor 1202 may access memory 1203 via an I / O (Input / Output) interface, which is not shown.

[0049] In the example shown in Figure 13, memory 1203 is used to store a group of software modules. The processor 1202 can read these software modules from memory 1203 and execute them, thereby enabling the analysis device 10 to perform the processing described in the above embodiment.

[0050] As explained with reference to Figure 13, each of the processors in the analysis apparatus 10 in the above-described embodiment executes one or more programs that include a set of instructions for causing the computer to perform the algorithm described with reference to the drawings.

[0051] In the examples described above, the program includes a set of instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more of the functions described in the embodiments. The program may be stored on a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited to, include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disc (DVD), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited to, include temporary computer-readable medium or a communication medium that includes electrically, optically, acoustically or otherwise propagating signals.

[0052] Furthermore, the technical concepts in this disclosure are not limited to the embodiments described above, and may be modified as appropriate without departing from the spirit of the invention.

[0053] Some or all of the above embodiments may also be described as follows, but are not limited to the following: (Note 1) An acquisition unit that acquires sensor information detected using a sensor mounted on an input device operated by the person being analyzed, A management department that manages schedule information including the schedule for at least one task related to the aforementioned person being analyzed, A generation unit that generates emotional values ​​of the subject of analysis when the aforementioned work is performed, using the aforementioned sensor information, An analytical apparatus comprising an analytical unit that analyzes the emotions of the subject of analysis using the aforementioned emotion values. (Note 2) The acquisition unit is, The aforementioned sensor information is acquired periodically, The generating unit is The analysis apparatus according to Appendix 1, which calculates the emotional value of the person being analyzed at the time the sensor information is acquired and accumulates the emotional value while the person being analyzed is performing the work. (Note 3) The aforementioned analysis unit is The analytical device described in Appendix 1 or 2, which outputs an alert when the negative emotion value of the person being analyzed exceeds a threshold. (Note 4) The analysis department, The analysis device described in Appendix 3, which accumulates the negative emotional values ​​of the subject of analysis over a predetermined period and outputs an alert when the accumulated emotional values ​​exceed a threshold. (Note 5) The aforementioned threshold is The analytical device described in Appendix 3, which is calculated using the emotional values ​​of individuals belonging to a specific group. (Note 6) The aforementioned analysis unit is The analysis device described in Appendix 3, which transmits the aforementioned alert to a terminal device owned by the administrator of the person being analyzed. (Note 7) The generating unit is An analysis device according to any one of the appendices 1 to 6, which generates the emotional value of the subject of analysis using a learning model that takes the sensor information as input and outputs the emotional value. (Note 8) The aforementioned sensor is The analytical apparatus according to any one of the appendices 1 to 7, comprising a biometric information sensor for detecting the biometric information of the person being analyzed, and an operation information sensor for collecting operation information when the person being analyzed operates the input device. (Note 9) The input device is a mouse, as described in any one of the appendices 1 to 8. (Note 10) Sensor information detected using sensors mounted on an input device operated by the person being analyzed is acquired. Obtain schedule information including the schedule for at least one task related to the aforementioned subject of analysis, Using the aforementioned sensor information, the emotional value of the subject of analysis when the aforementioned task was performed is generated. An analytical method for analyzing the emotions of the subject of analysis using the aforementioned emotion values. (Note 11) Sensor information detected using sensors mounted on an input device operated by the person being analyzed is acquired. Obtain schedule information including the schedule for at least one task related to the aforementioned subject of analysis, Using the aforementioned sensor information, the emotional value of the subject of analysis when the aforementioned task was performed is generated. A program that causes a computer to perform an analysis of the emotions of the subject of analysis using the aforementioned emotion values. [Explanation of Symbols]

[0054] 10 Analyzer 11 Acquisition Department 12 Management Department 13 Generation part 14 Analysis Department 20 Input devices 21 Left button 22 Right button 23 Central part 24 Rear 25 Side part 30 Business Systems 40 Display device

Claims

1. An acquisition unit periodically acquires sensor information detected using a sensor mounted on an input device operated by the person being analyzed, A management department that manages schedule information including the schedule for at least one task related to the aforementioned person being analyzed, A generation unit that uses the sensor information to generate the emotional value of the person being analyzed when the task is performed, which is the emotional value of the person being analyzed at the time the sensor information is acquired, and accumulates the emotional value while the person being analyzed is performing the task, An analysis device comprising: an analysis unit that analyzes the emotions of the subject of analysis using the cumulative value of the subject of analysis's emotional value and a threshold value generated based on the cumulative value of the emotional values ​​of persons who have previously been involved in the aforementioned work over a predetermined period.

2. The analysis department, The analysis device according to claim 1, which accumulates the negative emotional values ​​of the person being analyzed over a predetermined period, and outputs an alert when the accumulated emotional values ​​exceed the threshold.

3. The aforementioned threshold is The analysis device according to claim 1, which is calculated using the emotional values ​​of individuals belonging to a specific group.

4. The aforementioned analysis unit is The analysis apparatus according to claim 2, wherein the aforementioned alert is transmitted to a terminal device owned by the administrator of the person being analyzed.

5. The generating unit is The analysis apparatus according to claim 1, which generates the emotional value of the person being analyzed using a learning model that takes the sensor information as input and outputs the emotional value.

6. The aforementioned sensor is The analytical apparatus according to claim 1, comprising a biometric information sensor for detecting the biometric information of the person to be analyzed, and an operation information sensor for collecting operation information when the person to be analyzed operates the input device.

7. The analytical device is Sensor information detected using sensors mounted on input devices operated by the person being analyzed is acquired periodically. Obtain schedule information including the schedule for at least one task related to the aforementioned subject of analysis, Using the sensor information, generate the emotional value of the person being analyzed when performing the task, which is the emotional value of the person being analyzed at the time the sensor information was acquired, and accumulate the emotional value of the person being analyzed while performing the task. An analysis method for analyzing the emotions of the subject of analysis, using the cumulative value of the subject's emotional value and a threshold value generated based on the cumulative value of the emotional values ​​of persons who have previously been involved in the aforementioned work over a predetermined period.

8. Sensor information detected using sensors mounted on input devices operated by the person being analyzed is acquired periodically. Obtain schedule information including the schedule for at least one task related to the aforementioned subject of analysis, Using the sensor information, generate the emotional value of the person being analyzed when performing the task, which is the emotional value of the person being analyzed at the time the sensor information was acquired, and accumulate the emotional value of the person being analyzed while performing the task. A program that causes a computer to perform an analysis of the emotions of the subject of analysis using the cumulative value of the subject's emotional value and a threshold value generated based on the cumulative value of the emotional values ​​of persons who have previously been involved in the aforementioned work over a predetermined period.

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