Workload visual channel resource quantification method, system and device

Abstract

The invention provides a workload visual channel resource quantification method, system and device, and the method comprises the following steps: S1, analyzing a complex task normal form design principle, and determining a workload visual channel resource assignment method; s2, constructing a mapping relation between visual channel resource types and tasks; s3, based on the visual channel resource type and the mapping relation between the visual channel resource type and the task, an experiment normal form is constructed; s4, building an experimental environment and device, and constructing an experimental process; and S5, carrying out an experiment, collecting an NASA-TLX scale, the accuracy of task completion and response, pupil diameter and P300 peak data, and carrying out principal component and normalization analysis to realize workload visual channel resource quantification based on a multi-resource theory. The invention provides a method for realizing workload visual channel resource quantification based on the change degree of subjective, performance and physiological comprehensive indexes, and solves the problem of workload visual channel resource quantitative prediction of an operator in a system design stage.

Description

Technical Field

[0001] The present invention relates to the field of workload quantification analysis, and specifically carries out workload visual channel resource quantification work for a visual channel among four types of channels: vision, hearing, cognition, and psychomotor. A workload visual channel resource quantification method, system, and device are proposed. Background Art

[0002] When performing tasks, operators need to face complex operating environments and maintain continuous mental concentration. Excessive workload may cause operator fatigue, prolonged reaction time, and even cause operational errors, endangering personal safety. Therefore, by scientifically quantifying and predicting their workload, more reasonable task planning can be provided, human-machine interface design can be optimized, thereby reducing accident risks and ensuring the smooth completion of tasks.

[0003] Human information processing resources usually consist of four parts: vision, hearing, cognition, and psychomotor, collectively known as VACP. The VACP method is a widely used workload assessment method. By decomposing the operation process layer by layer into the smallest task unit, the workload is assessed by comparing the VACP scale according to the resources occupied by the smallest task unit. Due to the superiority of this method in workload assessment in the execution of complex tasks, it has been widely used in different fields such as aerospace, rail transportation, nuclear power, and mechanical operation. The existing VACP scale was originally designed for the aviation field, especially for flight mission design to predict and evaluate the impact of flight missions on pilot workload. The VACP scale assignment method is simple to use and intuitive, and is a flexible and effective assessment method. Since each resource type is compared with other resource types, the results of the assessment and assignment are comprehensive. In addition, in the absence of sufficient statistical data and original data, this method can also make quantitative assessments and is highly practical. The scores of the VACP scale are determined by system experts based on task requirements, without the need for operators to score after experience. This property makes it possible to predict the workload level of operators during the design phase. However, since the accuracy of the expert evaluation method used to obtain the scale mainly depends on the expert's experience and the breadth and depth of knowledge, it is highly subjective, lacking in theoretical and systematic nature, and sometimes it is difficult to guarantee the objectivity and accuracy of the evaluation results. At present, the VACP scale generated by the subjective evaluation method of system experts is generally used to predict and evaluate the workload brought by different design schemes, and the results obtained are prone to inconsistent and distorted prediction results. In contrast, with the continuous advancement of physiological measurement technology, physiological indicators have increasingly highlighted their advantages of sensitivity and objectivity in the application of workload quantification, providing more accurate and reliable data support for related fields. Based on the above analysis, there are relatively few studies on the quantification of workload visual channel resources in different industries at home and abroad. The present invention provides a method for quantifying workload visual channel resources based on the degree of change of subjective, performance, and physiological comprehensive indicators, which solves the problem of quantitative prediction of operator workload visual channel resources in the system design stage. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a method, system and device for quantifying workload visual channel resources, which can map tasks with different visual requirements to corresponding psychological paradigms, and explore a method for quantifying workload visual channel resources based on the degree of change of subjective, performance and physiological comprehensive indicators. By predicting and optimizing system design and task design of workload visual channel resources, problems such as operator fatigue and poor performance caused by improper load distribution can be alleviated.

[0005] Specifically, on one hand, the present invention provides a workload visual channel resource quantification method, which comprises the following steps:

[0006] S1. Analyze the design principle of complex task paradigm, determine the method of assigning workload visual channel resources, introduce fixed cognitive and psychomotor resource types and design experimental paradigms in combination with different visual channel resource types, take the experimental paradigm of resource type change as the independent variable, and the comprehensive index that can reflect the workload change as the dependent variable;

[0007] S2. According to the assignment method determined in step S1, a mapping relationship between the visual channel resource type and the task is constructed. The specific method is:

[0008] Based on the VACP theory and combined with the task environment, the visual function and motion characteristics of the human eye, the visual tasks of the operator during the task execution were analyzed, summarized and generalized, and 8 visual channel resource types were obtained; the 8 visual channel resource types were defined as V0-V7, and the remaining resource channel types were fixed to determine the task mapping corresponding to V0-V7;

[0009] S3. Based on the visual channel resource types obtained in step S2 and their corresponding task mapping relationships, an experimental paradigm is constructed. The specific method is as follows:

[0010] The task mapping results were used as the basis for screening psychological paradigms. Based on the description of V0-V7 in the VACP scale and the reproduction of typical tasks in related processes, the eight visual channel resource types V0-V7 were mapped one by one with traditional cognitive psychology experimental paradigms to obtain the experimental paradigm screening results, and the experimental paradigms of each specific task were determined in combination with actual scenarios.

[0011] S4. Based on the task experimental paradigm designed in step S3, build the experimental environment and equipment, and construct the experimental process;

[0012] Based on the experimental paradigms of each task in step S3, the duration of the experimental phase, the number of target stimulations, and the target stimulation interval were determined, and the experimental sequence adopted the Latin square experimental design;

[0013] S5. Conduct experiments according to the experimental process constructed in step S4, collect NASA-TLX scale, task completion accuracy and reaction time, pupil diameter and P300 peak data for principal component and normalization analysis, and realize workload visual channel resource quantification based on multi-resource theory, which specifically includes the following sub-steps:

[0014] S51. Determine the performance indicators as the accuracy and reaction time of task completion, where the calculation formula for the accuracy is shown in formula (1-1):

[0015] ACC i =x i / N (1-1)

[0016] Where, ACC i is the accuracy of the i-th task; x i is the number of correct responses made by the operator according to the stimulus displayed in the ith task experiment; N is the total number of stimulus appearances in the ith task experiment, N = 40;

[0017] The calculation formula for the reaction is shown in formula (1-2):

[0018] T reac =T press -T onset (1-2)

[0019] Where, T reac is the reaction time of successful trials in the task phase of the ith task; T press The time the operator presses the button; T onset The time for presentation of experimental stimulus materials;

[0020] S52. Combining the NASA-TLX scale, pupil diameter, and P300 peak, the principal component analysis method was used to reduce the dimension of the measurement data of all indicators to obtain a comprehensive indicator to reflect the operator workload, which specifically includes the following sub-steps:

[0021] S521. Since the task completion accuracy index is negatively correlated with the load index, the accuracy index is positively processed using formula (1-3):

[0022]

[0023] In the formula, x′ i is the value of the correctness index of the i-th task after positive conversion;

[0024] S522. Each indicator uses a different dimension. The data is standardized based on formula (1-4) to eliminate the impact of the dimension:

[0025]

[0026] In the formula, is the standardized value; is the sample mean of the jth indicator, that is, n is the number of operators; is the sample standard deviation of the jth indicator, that is

[0027] S523, perform KMO test and Bartlett test to determine whether principal component analysis is appropriate. If the KMO value is greater than 0.5 and the significance probability of Bartlett's sphericity test is less than 0.05, principal component analysis is appropriate;

[0028] S524, extract the principal components, and based on the component matrix of the principal components and the load percentage of each factor, obtain the calculation formula of the load comprehensive index score as shown in formula (1-5):

[0029] AWL = a 0 x 0 +a 1 x 1 +a 2 x 2 +a 3 x 3 +a 4 x 4 (1-5)

[0030] In the formula, x 0 is the standardized NASA-TLX scale score; x 1 is the standardized reaction time; x 2 is the correct rate after standardization; x 3 is the standardized pupil diameter; x 4 is the normalized P300 peak value;

[0031] S525. Normalize the comprehensive scores of each task according to formula (1-5). Multiply the normalized result by 7 to obtain the quantization result corresponding to V1 to V7. The normalization is shown in formula (1-6):

[0032]

[0033] In the formula, x new is the normalized value; x min is the minimum value of the comprehensive score of each task; x max It is the maximum value of the comprehensive scores of each task.

[0034] Preferably, in step S1, the independent variable is determined to be an experimental paradigm of changes in visual channel resource types, and the dependent variables are the NASA-TLX scale, the accuracy and reaction time of task completion, pupil diameter and P300 peak.

[0035] Preferably, the eight visual channel resource types in step S2 are behavior without visual requirements, perception / detection, visual resolution, visual inspection / verification, visual positioning / alignment, visual tracking / following, visual reading, and visual scanning / searching / monitoring.

[0036] Preferably, step S3 specifically includes the following sub-steps:

[0037] Step S31, based on the relevant description of V0-V7 in the VACP scale and reproducing the typical tasks in the relevant process, the eight visual channel resource types V0-V7 are mapped one by one with the traditional cognitive psychology experimental paradigm to obtain the experimental paradigm screening results;

[0038] Step S32: According to the screening results of the existing experimental paradigms, 8 specific experimental paradigms capable of characterizing the workload visual channel resource types V0-V7 are obtained.

[0039] Preferably, the eight screened experimental paradigms in step S3 are intermittent production task, detection response task, choice reaction time, visual search task, visual matching task, visual tracking task, coordinate confirmation task and signal detection task.

[0040] Preferably, the experimental process constructed in step S4 includes the following sub-steps:

[0041] S41. The experimenter displays the purpose of the experiment to the operator through the computer equipment and provides background knowledge training;

[0042] S42. The operator adjusts the seat by himself, and the experimenter adjusts the angle of the eye tracker. The operator is given the EEG device and the eye tracker is calibrated and verified at 9 points to check that the EEG signal output is normal.

[0043] S43, the experiment starts, the operator observes the human-computer interaction interface of the task, and conducts a test session lasting T minutes;

[0044] S44. After the operator is familiar with all tasks and has passed the test requirements, the experimenter prompts the operator to rest for t minutes through the computer device;

[0045] S45. After the operator has finished resting and indicated that he is in good condition, the experimenter collects t minutes of resting EEG data through the computer equipment;

[0046] S46, the formal experiment phase begins, and the operator's single task lasts for 2t minutes;

[0047] S47. After a single task is completed, the experimenter collects t minutes of resting EEG data of the operator through a computer device;

[0048] S48. The operator uses the NASA-TLX scale to evaluate the subjective workload of this task;

[0049] S49, change the experimental task, repeat steps S43-S47 to carry out the task, until all resource type measurement task data are completely collected;

[0050] S410. The experimenter guides the operator to review all tasks through computer equipment and fill in the task workload visual channel resource scale, and then ends the experiment.

[0051] On the other hand, the present invention also provides an optimization system, which includes a workload visual channel resource assignment determination unit, a visual channel resource type and task mapping relationship construction unit, an experimental paradigm construction unit, an experimental process construction unit, and a workload visual channel resource quantification unit;

[0052] The workload visual channel resource assignment determination unit determines the workload visual channel resource assignment method by analyzing the design principle of the complex task paradigm;

[0053] The mapping relationship construction unit of the visual channel resource type and the task constructs the mapping relationship between the visual channel resource type and the task according to the determined assignment method;

[0054] The experimental paradigm construction unit constructs an experimental paradigm according to the obtained visual channel resource type and its corresponding task mapping relationship;

[0055] The experimental process construction unit builds the experimental environment and equipment and constructs the experimental process according to the constructed task experimental paradigm;

[0056] The workload visual channel resource quantification unit conducts experiments according to the constructed experimental process, collects NASA-TLX scale, task completion accuracy and reaction time, pupil diameter and P300 peak data for principal component and normalization analysis, and realizes workload visual channel resource quantification based on multi-resource theory.

[0057] The present invention also provides an optimization device, which includes a computer device and an optimization system stored on the computer device and operable on a processor.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] (1) The method of the present invention systematically analyzes and deconstructs real tasks based on the hierarchical task analysis method, divides them into specific resource channel levels, identifies key variables and influencing factors, and provides database support for psychological paradigm screening.

[0060] (2) The method of the present invention designs specific experiments based on the psychological paradigm to simulate the real task situation and reflect the main characteristics and operation process of the real task. Based on the description of the visual channel resource type in the VACP scale, the tasks matching the resource requirements are screened and matched with the specific experimental paradigm, so that the paradigm design has consistent sensory input and operation requirements with the specific task, which is more in line with the task execution process and the results are more convincing.

[0061] (3) Taking into account the theoretical deficiencies of expert evaluation methods and the difficulty in ensuring the objectivity and accuracy of evaluation results, the method of the present invention proposes a comprehensive analysis method combining the NASA-TLX scale, task completion reaction time and accuracy, pupil diameter and P300 peak data, and uses subjective and objective data analysis to obtain more effective and reliable workload visual channel resource quantification results.

[0062] (4) The method of the present invention designs a psychological paradigm that fits typical human-computer interaction tasks, collects experimental data for principal component and normalization analysis, and obtains the quantification results of the workload visual channel resources. The overall trend is consistent with the trend of the existing VACP scale, which shows the rationality of the paradigm design. The overall task difficulty shows an upward trend in the visual channel. After further analysis of the data, the effectiveness of the design method is verified, and the existing VACP scale is optimized to make it more suitable for tasks and system designs in different fields in my country. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A schematic diagram of a method flow of a workload visual channel resource quantification method of the present invention;

[0064] Figure 2 Schematic diagram of a detection response task paradigm in an embodiment of the present invention;

[0065] Figure 3 A schematic diagram of a task paradigm for selecting a reaction time in an embodiment of the present invention;

[0066] Figure 4 Schematic diagram of a visual search task paradigm in an embodiment of the present invention;

[0067] Figure 5 Schematic diagram of a visual matching task paradigm in an embodiment of the present invention;

[0068] Figure 6 Schematic diagram of a visual tracking task paradigm in an embodiment of the present invention;

[0069] Figure 7 A schematic diagram of a coordinate confirmation task paradigm in an embodiment of the present invention;

[0070] Figure 8 Schematic diagram of a signal detection task paradigm in an embodiment of the present invention;

[0071] Fig. 9 It is the overall experimental flow chart in the embodiment of the present invention;

[0072] Fig.10 A schematic block diagram of a computer device according to the present invention. DETAILED DESCRIPTION

[0073] Specifically, on the one hand, the present invention provides a method for quantifying workload visual channel resources, which introduces fixed cognitive and psychomotor resource types in combination with different visual channel resource types to design an experimental paradigm, takes the experimental paradigm of resource type change as the independent variable, and takes the comprehensive index that can reflect the workload change as the dependent variable to carry out the experimental process to collect indicator data, processes and analyzes the indicator data through principal component analysis, compares and analyzes the results with the workload measurement results of the baseline task (task without visual activity), and quantifies the workload visual channel resources.

[0074] Specifically, the method comprises the following steps:

[0075] S1. Analyze the design principles of complex task paradigms, determine the method of assigning workload visual channel resources, introduce fixed cognitive and psychomotor resource types and design experimental paradigms in combination with different visual channel resource types, use the experimental paradigm of resource type changes as the independent variable, and the comprehensive index that can reflect workload changes as the dependent variable.

[0076] In a specific embodiment, in step S1, the independent variable is determined to be an experimental paradigm of changes in visual channel resource types, and the dependent variables are the NASA-TLX scale, the accuracy and reaction time of task completion, pupil diameter and P300 peak.

[0077] S2. According to the assignment method determined in step S1, a mapping relationship between the visual channel resource type and the task is constructed. The specific method is:

[0078] Based on the VACP theory and combined with the task environment, the visual function and motion characteristics of the human eye, the visual tasks of the operator during the task execution were analyzed, summarized and generalized, and 8 visual channel resource types were obtained. The 8 visual channel resource types were defined as V0-V7, and the remaining resource channel types were fixed to determine the task mapping corresponding to V0-V7.

[0079] In a specific embodiment, the eight visual channel resource types in step S2 are behavior without visual requirements, perception / detection, visual resolution, visual inspection / verification, visual positioning / alignment, visual tracking / following, visual reading, and visual scanning / searching / monitoring.

[0080] S3. Based on the visual channel resource types obtained in step S2 and their mapping relationship with tasks, construct an experimental paradigm.

[0081] Step S31, based on the relevant description of V0-V7 in the VACP scale and reproducing the typical tasks in the relevant process, the eight visual channel resource types V0-V7 are mapped one by one with the traditional cognitive psychology experimental paradigm to obtain the experimental paradigm screening results.

[0082] Step S32: According to the screening results of the existing experimental paradigms, 8 specific experimental paradigms capable of characterizing the workload visual channel resource types V0-V7 are obtained.

[0083] Preferably, the eight screened experimental paradigms in step S3 are intermittent production task, detection response task, choice reaction time, visual search task, visual matching task, visual tracking task, coordinate confirmation task and signal detection task.

[0084] S4. Based on the task experimental paradigm designed in step S3, build the experimental environment and equipment, and construct the experimental process.

[0085] Based on the experimental paradigms of each flight task in step S3, the duration of the experimental phase, the number of target stimulations, and the target stimulation interval were determined, and the experimental sequence adopted the Latin square experimental design.

[0086] The experimental process constructed in step S4 includes the following sub-steps:

[0087] S41. The experimenter displays the purpose of the experiment to the operator through computer equipment and provides background knowledge training.

[0088] S42. The operator adjusts the seat independently, and the experimenter adjusts the angle of the eye tracker. The operator is given the EEG device and the eye tracker is calibrated and verified at 9 points to check whether the EEG signal output is normal.

[0089] S43. Start the experiment. The operator observes the human-computer interaction interface of the task and conducts a test session lasting T minutes.

[0090] S44. After the operator is familiar with all tasks and has passed the test requirements, the experimenter prompts the operator to rest for t minutes through the computer equipment.

[0091] S45. After the operator has finished resting and indicates that he is in good condition, the experimenter collects t minutes of resting-state EEG data through computer equipment.

[0092] S46: The formal experiment phase begins. The operator's single task lasts for 2t minutes.

[0093] S47. After a single task is completed, the experimenter collects t minutes of resting-state EEG data of the operator through computer equipment.

[0094] S48. The operator uses the NASA-TLX scale to evaluate the subjective workload of this task.

[0095] S49, change the experimental task, and repeat steps S43-S47 to carry out the task until all resource type measurement task data are completely collected.

[0096] S410. The experimenter guides the operator to review all tasks through computer equipment and fill in the task workload visual channel resource scale, and then ends the experiment.

[0097] S5. Conduct experiments according to step S4, collect NASA-TLX scale, task completion accuracy and reaction time, pupil diameter and P300 peak data for principal component and normalization analysis, and realize workload visual channel resource quantification based on multi-resource theory, which specifically includes the following sub-steps:

[0098] S51. Determine the performance indicators as the accuracy and reaction time of task completion, where the calculation formula for the accuracy is shown in formula (1-1):

[0099] ACC i =x i / N (1-1)

[0100] Where, ACC i is the accuracy of the i-th task; x i is the number of correct responses made by the operator according to the stimulus displayed in the ith task experiment; N is the total number of stimulus appearances in the ith task experiment, N = 40;

[0101] The calculation formula for the reaction is shown in formula (1-2):

[0102] T reac =T press -T onset (1-2)

[0103] Where, T reac is the reaction time of successful trials in the task phase of the ith task; T press The time the operator presses the button; T onset The time when the experimental stimulus materials are presented.

[0104] S52. Combining multiple indicators such as NASA-TLX scale, pupil diameter and P300 peak, principal component analysis is used to reduce the dimension of the measurement data of all indicators to obtain a comprehensive indicator to reflect the operator workload, which specifically includes the following sub-steps:

[0105] S521. Since the task completion accuracy index is negatively correlated with the load index, the accuracy index is positively processed using formula (1-3):

[0106]

[0107] In the formula, x′ i is the positive value of the accuracy index of the i-th task.

[0108] S522. Each indicator uses a different dimension. The data is standardized based on formula (1-4) to eliminate the impact of the dimension:

[0109]

[0110] In the formula, is the standardized value; is the sample mean of the jth indicator, that is, n is the number of operators; is the sample standard deviation of the jth indicator, that is

[0111] S523, perform KMO test and Bartlett test to determine whether principal component analysis is suitable. If the KMO value is greater than 0.5 and the significance probability of Bartlett's sphericity test is less than 0.05, it is determined that principal component analysis is suitable.

[0112] S524, extract the principal components, and based on the component matrix of the principal components and the load percentage of each factor, obtain the calculation formula of the load comprehensive index score as shown in formula (1-5):

[0113] AWL = a 0 x 0 +a 1 x 1 +a 2 x 2 +a 3 x 3 +a 4 x 4 (1-5)

[0114] In the formula, x 0 is the standardized NASA-TLX scale score; x 1 is the standardized reaction time; x 2 is the correct rate after standardization; x 3 is the standardized pupil diameter; x 4 is the normalized P300 peak value.

[0115] S525. Normalize the comprehensive scores of each task according to formula (1-5). Multiply the normalized result by 7 to obtain the quantization result corresponding to V1 to V7. The normalization is shown in formula (1-6):

[0116]

[0117] In the formula, x new is the normalized value; x min is the minimum value of the comprehensive score of each task; x max It is the maximum value of the comprehensive scores of each task.

[0118] The present invention also provides an optimization system for a workload visual channel resource quantification method, which includes a workload visual channel resource assignment determination unit, a visual channel resource type and task mapping relationship construction unit, an experimental paradigm construction unit, an experimental process construction unit and a workload visual channel resource quantification unit.

[0119] The workload visual channel resource assignment determination unit determines the workload visual channel resource assignment method by analyzing the design principle of complex task paradigm.

[0120] The mapping relationship construction unit between the visual channel resource type and the task constructs the mapping relationship between the visual channel resource type and the task according to the determined assignment method.

[0121] The experimental paradigm construction unit constructs the experimental paradigm according to the obtained visual channel resource types and their corresponding task mapping relationships.

[0122] The experimental process construction unit builds the experimental environment and equipment and constructs the experimental process according to the constructed task experimental paradigm.

[0123] The workload visual channel resource quantification unit conducts experiments according to the constructed experimental process, collects NASA-TLX scale, task completion accuracy and reaction time, pupil diameter and P300 peak data for principal component and normalization analysis, and realizes workload visual channel resource quantification based on multi-resource theory.

[0124] The present invention also provides an optimization device, comprising: a computer device and an optimization system stored on the computer device and operable on a processor.

[0125] like Fig.10 As shown, the computer device includes a processor, a memory, an input / output interface and a communication interface, wherein the processor, the memory and the input / output interface are connected via a system bus, the communication interface is connected to the system bus via the input / output interface, the processor is used to provide computing and control capabilities, the memory includes a non-volatile storage medium and an internal memory, the non-volatile storage medium stores an operating system, a computer program and a database, the internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium, the database is used to store pending transactions, the input / output interface is used to exchange information between the processor and an external device, and the communication interface of the computer device is used to communicate with an external terminal via a network connection.

[0126] Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[0127] Example 1

[0128] This embodiment provides a workload visual channel resource quantification method, such as Figure 1 As shown, the method comprises the following steps:

[0129] S1. In order to accurately understand the characteristics of visual channel resource types and the differences between different visual resource types, the definition and characteristics of each visual channel resource type are summarized, and its language anchor is mapped to the relevant psychological paradigm to describe the characteristics and changes of different visual channel resource types. Through the design and implementation of a series of experimental paradigms corresponding to different levels of language anchors, more effective and reliable workload visual channel resource quantification results are obtained according to the degree of change of the operator's comprehensive indicators. In the task design, the workload cognitive channel and psychomotor channel resources are introduced, and the load levels of these two channels are used as control variables and set to fixed levels. By measuring the workload induced by tasks corresponding to different visual channel resources, the indicator data are processed and analyzed by principal component analysis, and the results are compared with the workload measurement results of the baseline task (task without visual activity). The quantification results of the visual channel resource types are obtained by normalization analysis. Since the existing VACP scale is a 7-point scale, in order to facilitate comparison and discussion with it, the normalized quantification results are multiplied by 7 as the final results.

[0130] Based on this, the experimental paradigm of resource type change was used as the independent variable, and the NASA-TLX scale that can reflect the load change, the accuracy and reaction time of task completion, the pupil diameter and the P300 peak were used as the dependent variables. According to the degree and range of change of the comprehensive indicators of different resource types of the visual channel, the workload visual channel resources were quantified.

[0131] S2. Based on the VACP theory and combined with the flight mission environment and the visual functions and motion characteristics of the human eye, the visual tasks of pilots during the mission are analyzed, summarized and generalized. The following 8 types of visual channel resources can more completely describe the visual perception requirements of all vision-related tasks during the flight:

[0132] Non-visual behaviors, perception / detection (detecting the presence of images), visual discrimination (detecting visual differences), visual inspection / verification (discrete inspection / static conditions), visual localization / alignment (selective orientation), visual tracking / following (maintaining orientation), visual reading (symbols), and visual scanning / searching / monitoring (continuous / serial inspection, multiple conditions).

[0133] Based on the hierarchical task analysis method, the flight operation tasks were decomposed and sorted out with reference to existing literature, and the flight task-resource type mapping was realized by combining the analysis of resource types and task requirements. On this basis, the flight operation tasks with workload visual channel resource levels ranging from level 0 to level 7 were sorted out, and the descriptions of relevant specific flight tasks with visual channel load levels of V0-V7, cognitive channel load levels of C2, and psychomotor channel load levels of P2 are summarized as shown in Table 1, which serves as the task basis for psychological paradigm screening.

[0134] Table 1 Mapping relationship between visual channel resource types and typical tasks

[0135]

[0136]

[0137] S3. Based on the visual channel resource type obtained in step S2 and its mapping relationship with the task, an experimental paradigm is constructed. The specific steps are as follows:

[0138] S31. Based on the description of V0-V7 in the VACP scale and the reproduction of typical tasks in related models, the eight visual channel resource types V0-V7 are mapped one by one with the traditional cognitive psychology experimental paradigm to obtain the experimental paradigm screening results. The specific mapping process is as follows:

[0139] The present invention combines the specific description of the resource types of the four resource channels with the typical flight missions in the relevant aircraft models, and screens out 8 experimental paradigms that can characterize the different resource types V0-V7 of the workload visual channel, and the cognitive channel is C2 and the psychomotor channel is P2 from the perspective of the human-computer interaction interface and the task resource requirements. Through literature review, combined with the description of the visual channel resource types in step S2, it is determined that the experimental paradigms used in this experiment are: intermittent production task, detection response task, selection reaction time, visual search task, visual matching task, visual tracking task, coordinate confirmation task and signal detection task. The screening results of the experimental paradigms corresponding to different resource types of the workload visual channel are shown in Table 2.

[0140] Table 2 Screening results of experimental paradigms corresponding to visual channel resource types

[0141]

[0142]

[0143] S32. Based on the screening results of the existing experimental paradigms, 8 specific experimental paradigms that can characterize the workload visual channel resource types V0-V7 are obtained. Combined with the actual scene, the specific flight tasks are determined, hereinafter referred to as the specific design of each Block i task as follows:

[0144] Block 0 Mission

[0145] The Block 0 task requirement is V0+C2+P2. According to the paradigm screening results, the experimental paradigm that meets the Block 0 task requirement is determined to be the intermittent production task. In this task, the operator does not need any sensory input and presses the space bar approximately every 15 seconds at a comfortable rhythm to generate a series of relatively regular time intervals.

[0146] Block 1 Mission

[0147] The task requirements of Block 1 are V1+C2+P2. According to the results of paradigm screening, the experimental paradigm that meets the task requirements of Block 1 is determined to be the detection response task. Figure 2 As shown, in this task, the operator first observes the cross-shaped fixation point that appears on the screen for a random number T1 between 500-800ms; in order to prevent the operator from predicting the time when the stimulus appears instead of noticing the stimulus and responding, a blank interface will be displayed on the screen for a period of time before the stimulus is displayed, and the duration of the blank interface is a random number T2 between 200ms and 500ms; then the operator needs to pay attention to the position of the yellow pie that appears on the screen. If the yellow pie appears at the position of the first light, the operator needs to press the number key "1" as quickly as possible to respond, and if the yellow pie appears at the position of the second light, the operator needs to press the number key "2" as quickly as possible to respond. The system records the operator's reaction time T3 for this trial. In order to ensure that the duration of each trial is 15s, after the operator responds, a blank interface will appear for a period of time. The display time T of the blank interface is calculated as shown in formula (3-1):

[0148] T=15000ms-T 1 -T 2 -T 3 (3-1)

[0149] The display time of the fixation point and the blank interface in Block 2-Block 7 has the same pattern as in Block 1.

[0150] Block 2 Mission

[0151] The resource requirements of Block 2 task are V2+C2+P2. According to the results of paradigm screening, the experimental paradigm that meets the requirements of Block 2 task is determined to be the choice reaction time task. Figure 3 As shown, in this task, the operator needs to observe the Z or M stimuli appearing on the screen and press the corresponding Z and M keys as quickly as possible to respond.

[0152] Block 3 Mission

[0153] The resource requirements of Block 3 task are V3+C2+P2. According to the paradigm screening results, the experimental paradigm that meets the requirements of Block 3 task is determined to be the visual search experimental paradigm. Figure 4 As shown in the figure, in this task, the operator needs to observe the four numbers appearing on the screen, find the position of the number 1 as quickly as possible, and press the number key at the corresponding position to respond. When the number "1" appears in the first position from left to right, the operator needs to press the number key 1; when the number "1" appears in the second position from left to right, the operator needs to press the number key "2", and so on.

[0154] Block 4 Mission

[0155] The resource requirements of Block 4 task are V4+C2+P2. According to the paradigm screening results, the experimental paradigm that meets the requirements of Block 4 task is confirmed to be the visual matching experimental paradigm. Figure 5 As shown in the figure, in this task, the operator needs to observe the random number keyboard appearing on the screen, find the target number as quickly as possible, and respond by pressing the number key in the corresponding position. When the target number appears in the lower left corner, the operator's correct response is to press the number key 1; when the target number appears in the second position from left to right in the bottom row, the operator's correct response is to press the number key 2, and so on.

[0156] Block 5 Mission

[0157] The resource requirements of Block 5 task are V5+C2+P2. According to the paradigm screening results, the experimental paradigm that meets the requirements of Block 5 task is confirmed to be the visual tracking experimental paradigm. Figure 6 In this task, 9 intertwined curves are displayed on the screen. The end points below the curves are marked with numbers 1-9 from left to right. The red arrow above marks the starting point of a line. The operator needs to use vision to see the end point along the line and press the corresponding number key.

[0158] Block 6 Mission

[0159] The resource requirements of Block 6 tasks are V6+C2+P2. According to the results of paradigm screening, the experimental paradigm that meets the requirements of Block 6 tasks is confirmed to be the coordinate confirmation task, such as Figure 7 In this task, the operator needs to observe the two horizontally arranged longitude and latitude coordinates (coordinate 1 and coordinate 2) that appear on the screen, and confirm as quickly as possible whether the two coordinates are consistent. If the two coordinates are consistent, press the number key 1 to respond. If the two coordinates are inconsistent, press the number key 2 to respond.

[0160] Block 7 Mission

[0161] The resource requirements of Block 7 tasks are V7+C2+P2. According to the results of paradigm screening, the experimental paradigm that meets the requirements of Block 7 tasks is confirmed to be the signal detection task, such as Figure 8 In this task, the operator needs to visually scan all approximately 64 signal points appearing on the screen, find all squares composed of 4 signal points, and respond by pressing the corresponding number keys as quickly as possible.

[0162] S4. Based on the experimental paradigm design in step S3, the duration of the experimental phase was set to 10 minutes, during which the target stimulus appeared 40 times, once every 15 seconds on average. The experimental sequence adopted a Latin square experimental design to eliminate the impact of factors such as fatigue on the operator.

[0163] In this embodiment, Fig. 9 As shown in the figure, the overall experimental process is as follows:

[0164] S41. The experimenter explains the purpose of the experiment to the operator and provides background knowledge training;

[0165] S42. Ask the operator to adjust the seat by himself, and the experimenter will adjust the angle of the eye tracker accordingly, and put the EEG device on the operator. Ask the operator to cooperate with the 9-point calibration and verification of the eye tracker, and the experimenter will check that the EEG signal output is normal;

[0166] S43, the experiment started, the operator first observed the task's human-computer interaction interface and performed a test session that took a total of 16 minutes;

[0167] S44. When the operator is familiar with all tasks and has passed the test requirements, the operator is forced to take a silent rest for 5 minutes;

[0168] S45, after the operator has finished resting and indicates that he is in good condition, collect 5 minutes of resting EEG data of the operator;

[0169] S46, the formal experiment begins. The operator needs to achieve the best performance possible. The duration of a single task is 10 minutes.

[0170] S47. After a single task is completed, collect 5 minutes of resting EEG data of the operator;

[0171] S48. Please use the NASA-TLX scale to rate the subjective workload of this task.

[0172] S49, changing the experimental task, repeating steps S43 to S47 to carry out the task, until all resource type measurement task data are completely collected; in order to avoid the fatigue effect caused by the task sequence causing the fatigue level of the operator to change, the task sequence is balanced among the operators;

[0173] S410. The operator reviews all tasks under the guidance of the experimenter and fills in the task workload visual channel resource scale, thus ending the experimental process of one operator.

[0174] S5. The performance indicators are determined as the accuracy and reaction time of task completion. The data are collected by E-prime software, and the calculation formula for the accuracy is shown in formula (1-1).

[0175] ACC i =x i / N (1-1)

[0176] Where, ACC i is the accuracy rate of Block i task; x i is the number of times the operator made correct responses to the stimuli displayed in the Block i experiment; N is the total number of stimuli appearing in the Block i experiment, N = 40.

[0177] The calculation formula for the reaction is shown in formula (1-2).

[0178] T reac =T press -T onset (1-2)

[0179] Where, T reac T is the reaction time of successful trials in the Block i task phase; press The time the operator presses the button; T onset The time when the experimental stimulus materials are presented.

[0180] In order to more comprehensively and accurately reflect the characteristics of operator workload and its changing rules, multiple indicators including NASA-TLX scale, pupil diameter and P300 peak were considered, and principal component analysis was used to reduce the dimension of the measurement data of all indicators, and finally a comprehensive indicator was obtained to reflect the operator workload.

[0181] S51. Since the task completion accuracy index is negatively correlated with the load index, formula (1-3) is used to positively process the accuracy index.

[0182]

[0183] In the formula, x′ i It is the value of the correctness index of the Block i task after positive conversion.

[0184] S52. Each indicator uses a different dimension, and the data is standardized based on formula (1-4) to eliminate the impact of the dimension.

[0185]

[0186] In the formula, is the standardized value; is the sample mean of the jth indicator, that is, n is the number of operators. is the sample standard deviation of the jth indicator, that is

[0187] S53, KMO test and Bartlett test were performed to determine whether principal component analysis was suitable. The KMO value was 0.64, which was greater than 0.5, indicating that there was a certain correlation between the variables. The significance probability of Bartlett's sphericity test was 0.000, which was less than 0.05. The above tests showed that the experimental data were suitable for principal component analysis.

[0188] S54, extract the principal components and give the component matrix of the principal components, also known as factor loading. According to the loading percentage of each factor, the calculation formula of the load comprehensive index (Aggregative Workload, AWL) score is shown in formula (1-5):

[0189] AWL = 0.218x 0 +0.217x 1 +0.204x 2 +0.207x 3 +0.207x 4 (1-5)

[0190] In the formula, x 0 is the standardized NASA-TLX scale score; x 1 is the standardized reaction time; x 2 is the correct rate after standardization; x 3 is the standardized pupil diameter; x 4 is the normalized P300 peak value.

[0191] S55. Normalize the comprehensive scores of each task according to formula (1-5). Since the task resource requirements of tasks Block0-Block7 designed in this experiment are V0+C2+P2, V1+C2+P2, …, V7+C2+P2, the xx in the normalization formula is min , V0+C2+P2 is subtracted from all the task scores of V1-V7, and the normalized result multiplied by 7 is the quantization result corresponding to V1~V7.

[0192]

[0193] In the formula, x new is the normalized value; x min is the minimum value of the comprehensive score of each task; xmax It is the maximum value of the comprehensive scores of each task.

[0194] By designing a psychological paradigm that fits the human-computer interaction flight mission, the experimental data were collected and comprehensively analyzed to obtain the quantification results of the workload visual channel resources. The overall trend is consistent with the trend of the existing VACP scale, which shows the rationality of the paradigm design. The overall task difficulty is on an upward trend in the visual channel. After further analysis of the data, the effectiveness of the design method is verified, and the existing VACP scale is optimized to make it more suitable for my country's flight missions and system design.

[0195] Example 2

[0196] This embodiment provides a quantization system and a computer device. The quantization system includes: a computer device and a computer program stored on the computer device and executable on a processor. Fig.10 As shown. The computer device includes a processor, a memory, an input / output interface and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store pending transactions. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a workload visual channel resource quantification method in Example 1 is implemented.

[0197] It should be noted that the object information (including but not limited to object device information, object personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the present invention are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0198] Through the above analysis, the effectiveness of the workload visual channel resource quantification method based on the psychological paradigm provided by the present invention has been proved. The present invention performs equivalent mapping of complex intelligent human-computer interaction tasks based on the psychological paradigm, uses a combination of subjective and objective methods to measure the workloads of different intensities brought by different types of human-computer interaction tasks, obtains more effective and reliable workload visual channel resource type evaluation results, realizes the workload visual channel resource quantification and prediction suitable for the characteristics of Chinese operators in the system design stage, better understands the requirements of tasks on people, optimizes task design, and improves work efficiency and safety.

[0199] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0200] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the method and core ideas of the present invention. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

[0201] The embodiments described above are only descriptions of the preferred implementation modes of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A workload visual channel resource quantification method, characterized by: It specifically includes the following steps: S1. Analyze the design principle of complex task paradigm, determine the method of assigning workload visual channel resources, introduce fixed cognitive and psychomotor resource types and design experimental paradigms in combination with different visual channel resource types, take the experimental paradigm of resource type change as the independent variable, and the comprehensive index that can reflect the workload change as the dependent variable; S2. According to the assignment method determined in step S1, a mapping relationship between the visual channel resource type and the task is constructed. The specific method is: Based on the VACP theory and combined with the task environment, the visual function and motion characteristics of the human eye, the visual tasks of the operator during the task execution were analyzed, summarized and generalized, and 8 visual channel resource types were obtained; the 8 visual channel resource types were defined as V0-V7, and the remaining resource channel types were fixed to determine the task mapping corresponding to V0-V7; S3. Based on the visual channel resource types obtained in step S2 and their corresponding task mapping relationships, an experimental paradigm is constructed. The specific method is as follows: The task mapping results were used as the basis for screening psychological paradigms. Based on the description of V0-V7 in the VACP scale and the reproduction of typical tasks in related processes, the eight visual channel resource types V0-V7 were mapped one by one with traditional cognitive psychology experimental paradigms to obtain the experimental paradigm screening results, and the experimental paradigms of each specific task were determined in combination with actual scenarios. S4. Based on the task experimental paradigm designed in step S3, build the experimental environment and equipment, and construct the experimental process; Based on the experimental paradigms of each task in step S3, the duration of the experimental phase, the number of target stimulations, and the target stimulation interval were determined, and the experimental sequence adopted the Latin square experimental design; S5. Conduct experiments according to the experimental process constructed in step S4, collect NASA-TLX scale, task completion accuracy and reaction time, pupil diameter and P300 peak data for principal component and normalization analysis, and realize workload visual channel resource quantification based on multi-resource theory, which specifically includes the following sub-steps: S51. Determine the performance indicators as the accuracy and reaction time of task completion, where the calculation formula for the accuracy is shown in formula (1-1): ACC i =x i / N(1-1) Where, ACC i is the accuracy of the i-th task; x i is the number of correct responses made by the operator according to the stimulus displayed in the ith task experiment; N is the total number of stimulus appearances in the ith task experiment, N = 40; The calculation formula for the reaction is shown in formula (1-2): T reac =T press -T onset (1-2) Where, T reac is the reaction time of successful trials in the task phase of the ith task; T press The time the operator presses the button; T onset The time for presentation of experimental stimulus materials; S52. Combining the NASA-TLX scale, pupil diameter, and P300 peak, the principal component analysis method was used to reduce the dimension of the measurement data of all indicators to obtain a comprehensive indicator to reflect the operator workload, which specifically includes the following sub-steps: S521. Since the task completion accuracy index is negatively correlated with the load index, the accuracy index is positively processed using formula (1-3): In the formula, x′ i is the value of the correctness index of the i-th task after positive conversion; S522. Each indicator uses a different dimension. The data is standardized based on formula (1-4) to eliminate the impact of the dimension: In the formula, is the standardized value; is the sample mean of the jth indicator, that is, n is the number of operators; is the sample standard deviation of the jth indicator, that is S523, perform KMO test and Bartlett test to determine whether principal component analysis is appropriate; if the KMO value is greater than 0.5 and the significance probability of Bartlett's sphericity test is less than 0.05, principal component analysis is appropriate; S524, extract the principal components, and based on the component matrix of the principal components and the load percentage of each factor, obtain the calculation formula of the load comprehensive index score as shown in formula (1-5): AWL=a0x0+a1x1+a2x2+a3x3+a4x4 (1-5) In the formula, x0 is the standardized NASA-TLX scale score; x1 is the standardized reaction time; x2 is the standardized accuracy; x3 is the standardized pupil diameter; x4 is the standardized P300 peak value; S525. Normalize the comprehensive scores of each task according to formula (1-5). Multiply the normalized result by 7 to obtain the quantization result corresponding to V1 to V7. The normalization is shown in formula (1-6): In the formula, x new is the normalized value; x min is the minimum value of the comprehensive score of each task; x max It is the maximum value of the comprehensive scores of each task.

2. The workload visual channel resource quantification method according to claim 1, characterized in that: In step S1, the independent variable is determined to be the experimental paradigm of changes in the type of visual channel resources, and the dependent variables are the NASA-TLX scale, the accuracy and reaction time of task completion, pupil diameter and P300 peak.

3. The workload visual channel resource quantification method according to claim 1, characterized in that: The eight visual channel resource types in step S2 are behavior without visual requirements, perception / detection, visual discrimination, visual inspection / verification, visual positioning / alignment, visual tracking / following, visual reading, and visual scanning / searching / monitoring.

4. The workload visual channel resource quantification method according to claim 1, characterized in that: Step S3 specifically includes the following sub-steps: Step S31, based on the relevant description of V0-V7 in the VACP scale and reproducing the typical tasks in the relevant process, the eight visual channel resource types V0-V7 are mapped one by one with the traditional cognitive psychology experimental paradigm to obtain the experimental paradigm screening results; Step S32: According to the screening results of the existing experimental paradigms, 8 specific experimental paradigms capable of characterizing the workload visual channel resource types V0-V7 are obtained.

5. The workload visual channel resource quantification method according to claim 1, characterized in that: The eight experimental paradigms selected in step S3 are intermittent production task, detection response task, choice reaction time, visual search task, visual matching task, visual tracking task, coordinate confirmation task and signal detection task.

6. The workload visual channel resource quantification method according to claim 1, characterized in that: The experimental process constructed in step S4 includes the following sub-steps: S41. The experimenter displays the purpose of the experiment to the operator through the computer equipment and provides background knowledge training; S42. The operator adjusts the seat by himself, and the experimenter adjusts the angle of the eye tracker. The operator wears the EEG device and performs 9-point calibration and verification of the eye tracker to check that the EEG signal output is normal. S43, the experiment starts, the operator observes the human-computer interaction interface of the task, and conducts a test session lasting T minutes; S44. After the operator is familiar with all tasks and has passed the test requirements, the experimenter prompts the operator to rest for t minutes through the computer device; S45. After the operator has finished resting and indicated that he is in good condition, the experimenter collects t minutes of resting EEG data through the computer equipment; S46, the formal experiment phase begins, and the operator's single task lasts for 2t minutes; S47. After a single task is completed, the experimenter collects t minutes of resting EEG data of the operator through a computer device; S48. The operator uses the NASA-TLX scale to evaluate the subjective workload of this task; S49, change the experimental task, repeat steps S43-S47 to carry out the task, until all resource type measurement task data are completely collected; S410. The experimenter guides the operator to review all tasks through computer equipment and fill in the task workload visual channel resource scale, and then ends the experiment.

7. The workload visual channel resource quantification method according to claim 1, characterized in that: The baseline in step S1 is considered to be the task without visual activity.

8. An optimization system for the workload visual channel resource quantification method of claim 1, characterized in that: It includes a workload visual channel resource assignment determination unit, a visual channel resource type and task mapping relationship construction unit, an experimental paradigm construction unit, an experimental process construction unit and a workload visual channel resource quantification unit; The workload visual channel resource assignment determination unit determines the workload visual channel resource assignment method by analyzing the design principle of the complex task paradigm; The mapping relationship construction unit of the visual channel resource type and the task constructs the mapping relationship between the visual channel resource type and the task according to the determined assignment method; The experimental paradigm construction unit constructs an experimental paradigm according to the obtained visual channel resource type and its corresponding task mapping relationship; The experimental process construction unit builds the experimental environment and equipment and constructs the experimental process according to the constructed task experimental paradigm; The workload visual channel resource quantification unit conducts experiments according to the constructed experimental process, collects NASA-TLX scale, task completion accuracy and reaction time, pupil diameter and P300 peak data for principal component and normalization analysis, and realizes workload visual channel resource quantification based on multi-resource theory.

9. An optimization device for the workload visual channel resource quantification method according to claim 1, characterized in that: It includes: A computer device and an optimized system stored on the computer device and operable on a processor.

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