Psychological exercise ability multi-task evaluation method and psychological exercise ability multi-task evaluation system

Abstract

The invention relates to the technical field of man-machine interaction and psychological assessment, in particular to a psychological exercise ability multi-task assessment method and system. The method comprises the following steps: configuring a test process and task parameters, selecting at least two tasks from a task library containing multi-finger force control, target tracking, quick response and continuous adjustment tasks, and setting an operation mode; executing the selected task, and collecting user behavior data through various external sensing devices; calculating a multi-dimensional evaluation index of each task based on the behavior data; and integrating all indexes to generate a comprehensive evaluation report. The system comprises a corresponding configuration module, a task execution module, a data acquisition module, an index calculation module and a report generation module. Through comprehensive computerization and multi-task normal forms, objective, refined and multi-dimensional comprehensive assessment of psychological exercise ability is realized, and the defects that a traditional assessment tool is high in subjectivity, single in data dimension and insufficient in ability coverage are effectively overcome.

Description

Technical Field

[0001] This invention relates to the field of human-computer interaction and psychological assessment technology, and more specifically to a multi-task assessment method and system for psychomotor ability. Background Technology

[0002] Psychomotor ability refers to the ability to control human movement and ensure the completion of motor tasks. It is the skill of coordinating sensory information with muscle reactions and has important application value in the selection and evaluation of personnel such as snipers, pilots, and helmsmen.

[0003] Currently, there are various traditional methods for assessing psychomotor abilities, which typically employ a single task to screen for specific sub-abilities. For example: The Purdue Pegboard test assesses hand dexterity, finger dexterity, and hand-eye coordination by requiring participants to insert as many pins as possible into a perforated board within a specified time. The O'Connor Finger Dexterity Test uses tweezers to pick up and place a fine needle, focusing on assessing the fine manipulation ability of the fingertips; In addition, the Go / No-Go task is used to measure reaction inhibition and reaction speed, while the tracking task is used to examine hand-eye coordination and motor control stability.

[0004] The aforementioned traditional assessment methods have significant limitations, mainly in the following two aspects: The evaluation process is subjective and crude, with limited data collection dimensions. Traditional tasks often rely on manual timing and counting, which is not only inefficient but also prone to subjective errors and operational deviations. More importantly, these methods can only provide limited macroscopic data such as total completion time and number of errors, failing to reveal subtle behavioral patterns during the operation process and making it difficult to meet the needs of high-precision evaluation.

[0005] Assessing abilities using only one dimension makes it difficult to comprehensively reflect the overall structure of abilities. Traditional tools typically screen for a specific ability in isolation; for example, the Purdue Pegboard focuses on overall hand dexterity, while the O'Connor test focuses on fine motor dexterity of the fingertips. The single scores they provide cannot comprehensively and systematically reflect the complex psychomotor ability structure of an individual, and cannot achieve a comprehensive deconstruction and assessment of multidimensional sub-abilities such as hand-eye coordination, force control precision, and cognitive flexibility. Summary of the Invention

[0006] In view of this, the present invention provides a multi-task assessment method and system for psychomotor ability, which aims to solve the technical problems of existing psychomotor ability assessment tools, such as subjective and extensive assessment process, limited data collection dimensions, and single assessment ability dimensions. This enables objective, refined, and multi-dimensional comprehensive evaluation of individual psychomotor ability, thereby improving the comprehensiveness, accuracy, and reliability of assessment results.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A multi-task assessment method and system for psychomotor abilities, characterized by comprising: The steps for configuring the test process and task parameters include selecting at least two tasks from a task library and setting the task's running mode. The task library includes multi-finger force control tasks, target tracking tasks, rapid response tasks, and continuous adjustment tasks. The steps to execute multiple selected tasks and collect user behavior data during task execution; Based on the behavioral data, the steps for calculating multi-dimensional evaluation indicators for each task; and The steps involve integrating multi-dimensional evaluation metrics from the aforementioned tasks to generate a comprehensive evaluation report.

[0008] In one specific implementation, the multi-finger force control task is configured as follows: The pressure applied by the user's four fingers is detected by four pressure sensors. The display interface shows four tracks corresponding to the four pressure sensors, and a target cylinder appearing on at least one track. The height of the ring on the corresponding track is controlled according to the pressure applied, so that the user can maintain the height of the ring within the height range of the target cylinder. The multi-dimensional evaluation index calculated for the multi-finger force control task includes at least one selected from the group consisting of reaction time, completion time, time within the target range, average deviation, single-finger accuracy, and multi-finger collaborative accuracy.

[0009] In one specific implementation, the target tracking task is configured as follows: The movement speed of the crosshair on the screen in the horizontal and vertical directions is controlled by the offset angle of the two joysticks, and the change speed of the crosshair diameter is controlled by the grip force sensor attached to the two joysticks. Control the periodic changes in the position and diameter of the target circle on the screen; The multi-dimensional evaluation metrics calculated for the target tracking task include average position tracking error and size tracking error.

[0010] In one specific implementation, the rapid response task is configured based on the Go / No-Go paradigm, including: The screen sequentially displays stimuli, including target numbers and non-target numbers; Collect user input behavior when pressing external buttons on non-target numbers; The multi-dimensional evaluation metrics calculated for the rapid response task include at least one selected from the group consisting of accuracy, average reaction time, and reaction time variability.

[0011] In one specific implementation, the continuous adjustment task is configured as follows: Present the call sign audio of the target channel to the user; The user selects a target channel from multiple alternative channels that matches the call sign audio via at least one knob. The multi-dimensional evaluation metrics calculated for the continuous adjustment task include accuracy and average time.

[0012] In one specific implementation scheme, the operating modes include sequential operating mode, simultaneous operating mode, and switching operating mode; in simultaneous operating mode, the number of tasks to be executed simultaneously is set; in switching operating mode, the period for switching between different tasks is set.

[0013] A multi-task assessment system for psychomotor abilities, characterized in that it is used to implement the method described in any of the preceding claims, the system comprising: The configuration module is used to configure the test process and task parameters; The task execution module is used to run multiple tasks selected by the configuration module; The data acquisition module includes various external sensing devices that are communicatively connected to the task execution module, used to collect user behavior data during task execution; The indicator calculation module is used to calculate multi-dimensional evaluation indicators for each task based on the behavioral data; and The report generation module is used to integrate the multi-dimensional evaluation indicators and generate a comprehensive evaluation report.

[0014] In one specific implementation, the plurality of external sensing devices include: Four pressure sensors are used to detect finger pressure during the multi-finger force control task; Two joysticks and two grip force sensors attached thereto are used to detect joystick offset angles and grip force during the target tracking task; A button is used to detect the user's response during the rapid response task; At least one knob is used to detect the user's channel selection operation during the continuous adjustment task.

[0015] In one specific implementation, the report generation module is further configured to generate a comprehensive evaluation report that includes a capability profile visualized in the form of a radar chart or bar chart.

[0016] In one specific implementation scheme, the indicator calculation module is further configured to standardize the calculated multi-dimensional evaluation indicators, and the report generation module generates the comprehensive evaluation report based on the standardized indicators.

[0017] Compared with existing technologies, the psychomotor ability multi-task assessment method and system described in this invention are used to objectively and comprehensively assess an individual's psychomotor ability. By constructing a standardized task library integrating multi-finger force control, target tracking, rapid response, and continuous adjustment tasks, and combining it with high-precision behavioral data collected by multimodal sensors, it achieves a leap from single-terminal indicators to multi-dimensional process indicators, effectively improving the objectivity, precision, and comprehensiveness of the assessment, and has the following beneficial effects: 1. Through comprehensive computerization and multimodal sensing technology, the objectivity and precision of evaluation data collection have been achieved.

[0018] This invention enables fully automated, multi-dimensional collection of behavioral data, eliminating subjective errors and operational biases present in traditional manual timing and scoring methods, thus making the evaluation results highly repeatable and comparable.

[0019] 2. Through multi-task paradigm and multi-indicator fusion analysis, a comprehensive and in-depth deconstruction and assessment of psychomotor ability was achieved.

[0020] This invention designs a set of task combinations covering different ability dimensions, which can extract a series of indicators reflecting various abilities such as fine motor control, hand-eye coordination, and cognitive flexibility from the task execution process, and finally generate a comprehensive evaluation report including standardized scores, visualized ability profiles and targeted suggestions, overcoming the shortcomings of traditional single-task evaluation tools that do not cover enough ability dimensions. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0022] Figure 1A flowchart for a multi-task assessment method for psychomotor abilities.

[0023] Figure 2 A schematic diagram of the human-computer interaction interface for multi-finger force control tasks.

[0024] Figure 3 A schematic diagram of the human-computer interaction interface for a target tracking task. Detailed Implementation

[0025] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] To address the limitations of traditional assessment methods in terms of objectivity, precision, and comprehensiveness, this invention constructs a multi-dimensional, high-precision, and computerized integrated assessment system, and correspondingly provides a multi-task assessment method for psychomotor abilities. Based on the theoretical framework of psychomotor abilities, the system integrates and runs a task library (assessment task library) consisting of multiple core tasks through a unified hardware platform and software environment, and supports flexible configuration of task parameters and assessment processes. Correspondingly, the method controls the execution flow of the aforementioned tasks through program instructions, coordinates with various external sensing devices to collect high-precision behavioral data, and extracts multi-dimensional assessment indicators from each task to characterize different key sub-elements of psychomotor abilities, thereby ultimately achieving a multi-faceted, comprehensive, and computerized assessment of students' psychomotor abilities.

[0027] like Figure 1 As shown, the multi-task assessment method for psychomotor ability described in this invention is applied to objectively assess psychomotor ability through multiple tasks, and includes the following steps: Step 1: Configure the testing process and task parameters. In the psychomotor ability multi-task assessment system (hereinafter referred to as the assessment system), setting the testing process and task parameters is the first crucial step in achieving the assessment.

[0028] The evaluation system supports three modes: sequential execution, simultaneous execution, and switching execution. In sequential execution mode, each task is executed sequentially after parameter configuration. Simultaneous execution mode requires the user to process multiple tasks within the same time period; therefore, the difficulty of the task is determined by the number of tasks executed simultaneously, and multithreading is used. Switching execution mode allows switching between different tasks at a set period. Therefore, the test flow needs to be configured first, including the evaluation tasks, task time, and execution mode (the number of tasks to be executed simultaneously needs to be set in the simultaneous motion model, and the switching period needs to be set in the switching execution mode). Generally, sequential execution mode should be used.

[0029] Then configure the task parameters. Specifically, there are four tasks: multi-finger force control task, target tracking task, rapid response task, and continuous adjustment task.

[0030] Multi-finger force control tasks require configuring parameters such as the position, appearance time, height, and thickness of the target cylinder, as well as operation sensitivity. The difficulty of the task is controlled by parameters such as the number of target cylinders appearing simultaneously, their thickness, and duration. The target tracking task requires configuring parameters such as the target's position, diameter, appearance time, as well as operation sensitivity and joystick operation method. The difficulty of the task is related to parameters such as operation method and target appearance time. Rapid response tasks require configuring parameters such as target numbers and time per trial.

[0031] Continuous adjustment tasks require configuring parameters such as the number of alternative channels, audio presentation time, and call sign similarity.

[0032] Overall, the flexible configuration of the testing process and parameters not only enables personalized settings for task difficulty, but also ensures that the assessment system covers and examines various aspects of psychomotor abilities, such as fine motor skills / motor control, cognitive flexibility, and hand-eye coordination.

[0033] Step Two: Perform the multi-finger force control task and calculate the evaluation indicators. The multi-finger force control task examines an individual's fine control over finger strength. This task requires four external sensors to measure the pressure applied by the fingers.

[0034] During the task, four tracks are displayed on the screen, corresponding to four pressure sensors (such as...). Figure 2 (As shown). The user uses four fingers to press four pressure sensors to control the height of the rings on the corresponding tracks. During the task, a cylinder may appear on each track, representing the force control target. The user needs to control the height of the rings on the same track within the height range of the cylinder for a certain period of time. If the requirement is met, a green feedback is provided; otherwise, a red feedback is provided. The minimum number of cylinders that can appear at the same time is 1, and the maximum number is 4.

[0035] The height of the ring above the ground is linearly related to the pressure measured by the pressure sensor; the greater the pressure, the higher the ring. Parameters such as the trajectory, duration, height, thickness, continuous pressing time, and pressure control sensitivity of the cylinder in multi-finger force control tasks can be adjusted in the parameter setting interface.

[0036] By employing a variety of analytical methods, six representative and discriminative evaluation indicators can be extracted from multi-dimensional raw force data.

[0037] 1) Reaction time, defined as the duration from the appearance of the target cylinder to the detection of the pressing force by the force sensor; 2) Completion time: The completion time is defined as the time from the appearance of the target cylinder to the user achieving the success condition. The success condition is defined as maintaining the pressure within the target range for a specific period of time. 3) Target range time: The target range time represents the cumulative duration of the pressure applied within the target range. 4) Average deviation, the average deviation is defined as the difference between the pressing force and the target force. The average difference between the centers of the target cylinders is given by the following formula:

[0038] in, N S Indicates the number of pressure sampling points. F i Indicates the current pressing pressure.

[0039] 5) Single-finger accuracy, defined as the success rate of a task when only one finger is needed to control the pressing pressure (i.e., when only one target cylinder appears at a time); 6) Multi-finger coordination accuracy is defined as the success rate of a task when two or more fingers are needed to control the pressing pressure simultaneously (i.e., when two or more target cylinders appear at the same time). The above indicators cover multiple aspects of evaluation, including stability, responsiveness, and accuracy of multi-finger force control.

[0040] Step 3: Perform the target tracking task and calculate the evaluation metrics. The target tracking task assesses the user's ability to continuously perform coordinated control of grip strength and position, hand-eye coordination, and bimanual coordination. During the task, a circular target with constantly changing position and diameter is displayed on the screen, along with a crosshair whose position and diameter are controlled by the user. The user needs to make the crosshair track the target object's position and size as accurately as possible. This task requires two external rotatable joysticks and two grip force sensors attached to the joysticks. Figure 3 As shown, the grip strength control of the left joystick increases, while the grip strength control of the right joystick decreases.

[0041] The position and size of the crosshair are controlled by the joysticks. Horizontal movement of the crosshair is controlled by the offset of one joystick, and vertical movement by the offset of the other. The greater the offset angle, the faster the crosshair moves. The increase and decrease in the crosshair diameter are controlled by the grip strength of each joystick; the greater the grip strength, the faster the crosshair diameter increases / decreases.

[0042] The sensitivity parameters for target position and diameter changes, crosshair movement, and diameter changes can be set. The following six parameters control target changes: horizontal position, vertical position, diameter, transition time, and wait time. Horizontal position, vertical position, and diameter define the state the target maintains at the end of the trial. Transition time refers to the time it takes for the target to move from the previous point to the next point (the time between the target's appearance and its movement to the next point is called a trial). Wait time refers to the time the target maintains that position within a trial. According to the above rules, the configuration of "horizontal position 500, vertical position 200, diameter 50, transition time 1 second, wait time 3 seconds" means that the target will change from the previous point to a position 500 pixels horizontally and 200 pixels vertically on the screen, with a diameter of 50 pixels, within 1 second, and maintain this state for 3 seconds.

[0043] This task primarily assesses the user's ability to coordinate force and motion when using both hands to operate the two joysticks, considering the offset and grip strength.

[0044] 1) Average position tracking error and 2) Size tracking error are the main indicators for target tracking tasks. The former refers to the average distance between the crosshair controlled by the user and the center of the target circle during the task, measuring the user's hand-eye coordination. The latter refers to the average deviation between the diameter of the crosshair controlled by the user and the diameter of the target, measuring the user's hand-eye force control. The smaller the average tracking error, the higher the control precision maintained by the user during continuous tracking, reflecting better fine motor skills and hand-eye coordination.

[0045] Step 4: Perform the rapid response task and calculate the evaluation metrics. The rapid response task is based on the "Go / No-Go" paradigm and is a classic task used to assess an individual's cognitive flexibility. This task requires an external keyboard or a single button.

[0046] During the task, users are presented with a continuous stream of stimuli (numbers 0-9 displayed on the screen), with a brief interval between each stimulus. The rules are: when a non-target number appears, the user must press a key as quickly as possible; when the target number (such as "3") appears, the user must suppress the key press. This setup assesses the user's ability to maintain focus and control impulses during extended tasks through monotonous repetition. The parameters that can be set for this assessment task include: the number of target numbers for which key presses must be suppressed, and the interval between stimuli.

[0047] For this task, three metrics are calculated to measure cognitive flexibility: 1) Accuracy. This refers to the ratio of correct key press responses to successful suppression control, reflecting the response-suppression control capability.

[0048] 2) Average reaction time and 3) Reaction time variability, namely the mean and standard deviation of key press response time, reflect the ability to maintain focus.

[0049] Step 5: Perform the continuous adjustment task and calculate the evaluation indicators. The continuous adjustment task assesses an individual's fine motor skills and decision-making abilities. This task requires one or two external rotatable knobs.

[0050] In this task, the user will receive audio information called a callsign, which is the frequency of the target channel. Based on this information, the user needs to quickly select the target channel from the pool of available channels that matches the callsign, using a rotary knob. This task simulates the filtering and reaction to received information during flight. The speed and accuracy of the knob operation can be used to assess an individual's fine motor skills. Parameters that need to be configured in advance include the number of available channels, their corresponding frequencies, presentation time, and callsign similarity.

[0051] The more alternative channels there are, the higher the demands on the user's channel memory retrieval and knob operation. Callsign similarity refers to the degree of similarity between the target call channel's callsign and other unrelated callsigns. The higher the similarity, the more likely the user is to misidentify the information.

[0052] There can be a maximum of 24 channels in the task. The 24 channels will be arranged in a 12-column x 2-page format. Users can use one knob to select one of the 12 channels on a page (vertical line break) and the second knob to switch pages (horizontal page break).

[0053] The task extracts two metrics, including: 1) Accuracy rate. This refers to the percentage of channels that are correctly selected from the available channels using a knob, matching the target call sign.

[0054] 2) Average time taken. This refers to the average time taken to select a channel that matches the target call sign by operating the knob.

[0055] Step Six: Integrate Indicators and Generate Assessment Result Report. After completing the testing and indicator calculation for each psychomotor ability assessment task, the system enters the data integration and report generation stage, scientifically decoding the individual's psychomotor ability structure from complex behavioral data.

[0056] First, the system cleans the raw data from tasks such as multi-finger force control, target tracking, rapid response, and continuous adjustment, removing invalid information caused by equipment interference or operational errors. Then, it calculates the z-score for each extracted indicator (such as reaction time, tracking error, and continuous adjustment accuracy) based on its norm-normal distribution. A z-score greater than 0 indicates exceeding the norm-normal average, while a z-score less than 0 indicates falling below the norm-normal average, thus eliminating differences in units and value ranges. Finally, a weighted average of the z-scores for each indicator is calculated to obtain the total score. The weights are set according to the evaluation purpose or user preferences; if there is no bias, all weights are equal.

[0057] In addition to the total score, the system will ultimately generate results that visualize the z-score of each indicator in the form of a radar chart or bar chart, intuitively showing the user's strengths and weaknesses in each psychomotor ability dimension. After completing the above steps, the system will output a structured comprehensive evaluation report. This report not only includes the user's basic information, test time, and task completion status, but also provides an overall psychomotor ability index and sub-indicator ability interpretation, and proposes targeted training suggestions based on this. Through this complete process, this invention can achieve the scientific measurement and accurate assessment of psychomotor ability, providing reliable data support and decision-making basis for the selection, ability diagnosis, and training of military personnel.

[0058] The following is an example: Step 1: Set task parameters, for example: Multi-finger force control task: The number of trials is 100. The height of the cylinder center from the ground is 500 pixels, the cylinder width is 50 pixels, the pressure sensitivity is 100 (1N of vertical positive pressure corresponds to 100 pixels), the duration of each trial is 2 seconds, and the correspondence between the four sensors and the four channels is set as follows (from left to right, 1-A, 2-B, 3-C, 4-D). The cylinder numbers appearing in each trial are: 1, 2, 4, 3, 2, 3…… (meaning the first trial is channel 1, the second trial is channel 2, and so on, representing that you only need to control the pressure of one finger each time) 1,2; 2,3; 1,4; ... (meaning the first trial uses channels 1 and 2, the second trial uses channels 2 and 3, the third trial uses channels 1 and 4, and so on, representing that each time the pressure of two fingers needs to be controlled simultaneously) Target tracking task: The number of trials is 50, the motion sensitivity is 20 (for every 1 degree of joystick deflection, the movement speed is 20 pixels / second; a 10-degree deflection results in 200 pixels / second movement), the grip strength sensitivity is 10 (1N of grip strength represents a change in the diameter of the red target at a rate of 10 pixels / second; a 2N grip strength results in a change in diameter at 20 pixels / second), and each trial lasts for 5 seconds. The location of the target in each trial is as follows: [800, 500], [600, 700], [200, 400], ... (represents the coordinates of the center of the red target circle in each trial, which can also be set to be random within a certain range) The diameter of the target in each trial is: 40, 30, 20, 24, ... (can also be set to random within a certain range) Rapid response mission: The number of trials is 100, the target number is 3, the duration of each trial is 1 second, the interval is 1 second, and the probability of the target number appearing is 0.1 (i.e., completely random). Continuous adjustment task: The number of trials is 50, the number of candidate channels is 12 (i.e., 12 channels per page), and the presentation time for each trial is 10 seconds. The target frequencies for each trial are: 118MHz, 117MHz, ... Call sign similarity is represented by the candidate frequency band range, for example, a candidate range of 108-120MHz. Step 2: Perform multi-finger force control tasks Users perform multi-finger force control tasks according to the above configuration. The system records data (pressure applied in each trial) and calculates relevant indicators. Step 3: Perform the target tracking task Users execute target tracking tasks according to the above configuration. The system records data (target trajectory and diameter changes in each trial) and calculates relevant indicators. Step 4: Execute a rapid response mission Users execute the quick response task according to the above configuration. The system records data (numbers for each trial and press response time) and calculates relevant metrics. Step 5: Perform continuous adjustment tasks The user executes the continuous adjustment task according to the above configuration. The system records data (time for each trial, number of knob rotations, etc.) and calculates relevant indicators. Step 6: Integrate indicators and generate an evaluation report. After confirming the completeness and quality of the data, for a specific indicator, calculate the user's z-score for that indicator based on the normal distribution (standard deviation and mean) of the indicator's norm. The overall z-score for the evaluation is: zsum = a1z1 + a2z2 + a3z3 + ... z1, z2, and z3 are the z-scores for each indicator, and a1, a2, and a3 are the indicator weights, which are set by the user according to the purpose of the assessment. If there is no bias, they can all be set to 1. If the final assessment result zsum is greater than 0, it means that the overall result exceeds the norm mean; if it is less than 0, it means that the overall result is less than the norm mean. zsum can also be converted to a percentage.

[0059] Test data: Compared with traditional assessment methods (Pudu nail board, O'Connor tweezers test), the reliability and validity of the assessment indicators proposed in this invention exceed those of traditional methods, specifically including: Reliability: Cronbach's alpha coefficient (internal consistency reliability): 0.52 for this invention, 0.38 for traditional assessment tools. Predictive validity: The correlation coefficient with the Adult Movement Disorders Scale (ADC), i.e. the predictive value of movement disorders in daily life, is 0.17 for this invention and 0.04 for the conventional assessment.

[0060] Construct validity: The mean variance extraction rate (AVE) is 0.38 in this invention and 0.29 in traditional evaluation.

[0061] Composite reliability (CR): 0.62 for this invention, and 0.58 for traditional assessment.

[0062] The above data demonstrates that the assessment system, tasks, and indicators proposed in this invention have advantages such as good consistency and high validity compared to traditional assessment tools.

[0063] The various embodiments described in this specification are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for multi-task evaluation of psychomotor abilities, characterized in that, The method comprises: a step of configuring a test procedure and task parameters, wherein the test procedure comprises selecting at least two tasks from a task library, and setting a running mode of the tasks, the task library comprising a multi-finger force control task, a target tracking task, a fast reaction task, and a continuous adjustment task; a step of executing the selected tasks and collecting behavior data of a user during execution of the tasks; a step of calculating, based on the behavior data, a multi-dimensional evaluation index corresponding to each task; and a step of integrating the multi-dimensional evaluation indexes from the tasks to generate a comprehensive evaluation report.

2. The method according to claim 1, wherein, The multi-finger force control task is configured to: detect pressing forces of four fingers of the user through four pressure sensors respectively; present, on a display interface, four tracks corresponding to the four pressure sensors respectively, and a target cylinder appearing on at least one track; control a height of a ring on a corresponding track according to the pressing forces, so that the user maintains the height of the ring within a height range of the target cylinder; wherein the multi-dimensional evaluation index calculated for the multi-finger force control task comprises at least one selected from a group consisting of reaction time, completion time, target range time, average deviation, single-finger accuracy, and multi-finger coordination accuracy.

3. The method of claim 1, wherein the method is a method of measuring psychological motor ability multitasking. The target tracking task is configured to: control movement speeds of a crosshair on a screen in horizontal and vertical directions through offset angles of two joysticks, and control a change speed of a diameter of the crosshair through grip force sensors attached to the two joysticks; control periodic changes of a position and a diameter of a target circle on the screen; wherein the multi-dimensional evaluation index calculated for the target tracking task comprises average position tracking error and size tracking error.

4. The method of claim 1, wherein the method is a method of measuring psychological motor ability multitasking. The fast reaction task is configured based on a Go / No-Go paradigm, comprising: presenting, on a screen, stimuli including target numbers and non-target numbers in sequence; collecting a key pressing reaction behavior of the user on non-target numbers through an external key; wherein the multi-dimensional evaluation index calculated for the fast reaction task comprises at least one selected from a group consisting of accuracy, average reaction time, and reaction time variability.

5. The method of claim 1, wherein the method is a method of measuring psychological motor ability multitasking. The continuous adjustment task is configured to: present a target channel call sign audio to the user; receive an operation of the user selecting a target channel matching the call sign audio from a plurality of alternative channels through at least one knob; wherein the multi-dimensional evaluation index calculated for the continuous adjustment task comprises correctness and average time consumption.

6. The method of claim 1, wherein the method is a mental motor ability multitask evaluation method. The running mode comprises a sequential running mode, a simultaneous running mode, and a switching running mode; in the simultaneous running mode, a number of tasks executed simultaneously is set; in the switching running mode, a period of switching between different tasks is set.

7. A psychomotor ability multitasking evaluation system, characterized by, The system for implementing the method according to any one of claims 1 to 6 comprises: a configuration module configured to configure a test procedure and task parameters; a task execution module configured to execute a plurality of tasks selected by the configuration module; a data collection module comprising a plurality of external sensing devices communicatively connected to the task execution module, and configured to collect behavior data of a user during execution of the tasks. An index calculation module is configured to calculate a multi-dimension evaluation index corresponding to each task based on the behavior data. A report generation module is configured to integrate the multi-dimension evaluation index and generate a comprehensive evaluation report.

8. The psychomotor ability multitask evaluation system according to claim 7, wherein, The plurality of external sensing devices include: four pressure sensors configured to detect finger pressing force in the multi-finger force control task; two joysticks and two grip force sensors attached to the two joysticks, configured to detect the joystick deflection angle and grip force in the target tracking task; one button configured to detect user reaction in the fast reaction task; and at least one knob configured to detect user channel selection operation in the continuous adjustment task. The plurality of external sensing devices include: four pressure sensors configured to detect finger pressing force in the multi-finger force control task; two joysticks and two grip force sensors attached to the two joysticks, configured to detect the joystick deflection angle and grip force in the target tracking task; one button configured to detect user reaction in the fast reaction task; and 9. The mental motor ability multitask evaluation system according to claim 7, wherein at least one knob configured to detect user channel selection operation in the continuous adjustment task.

10. The psychomotor performance multitasking evaluation system according to claim 7, wherein, The report generation module is further configured to generate the comprehensive evaluation report including the capability profile visualized in the form of a radar chart or a column chart. The index calculation module is further configured to perform standardization processing on the calculated multi-dimension evaluation index, and the report generation module generates the comprehensive evaluation report based on the standardized index.

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