A method, system and device for quantifying visual channel resources of a workload

Abstract

The application provides a workload visual channel resource quantification method, system and device, the method comprises the following steps: S1, analyzing the design principle of complex task paradigm, determining the workload visual channel resource assignment method; S2, constructing the mapping relationship between visual channel resource type and task; S3, based on the visual channel resource type and its mapping relationship with the task, constructing the experimental paradigm; S4, building experimental environment and device, constructing experimental process; S5, carrying out experiments, collecting NASA-TLX scale, task completion accuracy and reaction time, pupil diameter and P300 peak value data for principal component and normalization analysis, realizing workload visual channel resource quantification based on multi-resource theory. The application provides a method for quantifying workload visual channel resources based on the change degree of subjective, performance and physiological comprehensive indicators, solving the problem of quantitatively predicting the workload visual channel resources of operators in the system design stage.

Description

Technical Field

[0001] This invention relates to the field of workload quantification analysis, specifically targeting the visual channel among the four channels of vision, hearing, cognition, and psychomotor, to quantify workload visual channel resources, and proposes a method, system, and device for workload visual channel resource quantification. Background Technology

[0002] Operators face complex operating environments and require sustained mental concentration when performing tasks. Excessive workload can lead to operator fatigue, prolonged reaction time, and even operational errors, endangering personal safety. Therefore, scientifically quantifying and predicting workload can provide more reasonable task planning and optimize human-machine interface design, thereby reducing accident risks and ensuring successful task completion.

[0003] Human information processing resources typically consist of four parts: visual, auditory, cognitive, and psychomotor, collectively known as VACP. The VACP method is a widely used workload assessment method. It involves breaking down operational processes layer by layer to the smallest task units and then assessing workload based on the resources required by each unit, using a VACP scale. Due to its superiority in workload assessment for complex tasks, this method is widely used in various fields such as aerospace, rail transportation, nuclear power, and machinery operation. Existing VACP scales were originally designed for the aviation field, particularly for flight mission design, to predict and assess the impact of flight missions on pilot workload. The VACP scale assignment method is simple, intuitive, and a flexible and effective assessment method. Because each resource type is compared with other resource types, the assessment and assignment results are comprehensive. Furthermore, this method can provide quantitative assessments even in the absence of sufficient statistical data and raw materials, making it highly practical. VACP scale scores are determined by system experts based on task requirements, without requiring operators to rate the scores after experiencing the task. This property makes it suitable for predicting operator workload levels during the design phase. However, the accuracy of the expert evaluation method used to obtain the scale depends primarily on the experts' experience, breadth, and depth of knowledge, making it highly subjective and lacking in theoretical and systematic aspects, sometimes making it difficult to guarantee the objectivity and accuracy of the evaluation results. Currently, the VCP scale, generated by the subjective evaluation method of system experts, is commonly used to predict and evaluate the workload brought about by different design schemes, but the results are prone to inconsistencies and distortions. In contrast, with the continuous advancement of physiological measurement technology, physiological indicators are increasingly demonstrating their advantages in sensitivity and objectivity in workload quantification applications, providing more accurate and reliable data support for related fields. Based on the above analysis, there is relatively little research at home and abroad on the quantification of visual channel resources for workload in different industries. This invention provides a method for quantifying visual channel resources for workload based on the degree of change of subjective, performance, and physiological comprehensive indicators, solving the problem of quantitative prediction of operator workload visual channel resources during the system design stage. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the purpose of this 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, explore a method for quantifying workload visual channel resources based on the degree of change of subjective, performance and physiological comprehensive indicators, and reduce operator fatigue and poor performance caused by improper load allocation by predicting and optimizing the system design and task design of workload visual channel resources.

[0005] Specifically, the present invention provides a method for quantifying visual channel resources for workload, which includes the following steps:

[0006] 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, take the experimental paradigms of resource type changes as independent variables, and take the comprehensive index that can reflect workload changes as dependent variables.

[0007] S2. Based on the assignment method determined in step S1, construct the mapping relationship between visual channel resource types and tasks. The specific method is as follows:

[0008] Based on the VCP theory and combined with the task environment and the visual function and motion characteristics of the human eye, the visual tasks of the operator in the process of performing tasks are analyzed, summarized and generalized, resulting in 8 types of visual channel resources; the 8 visual channel resource types are defined as V0-V7, and the remaining resource channel types are fixed to determine the task mapping corresponding to V0-V7.

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

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

[0011] S4. Based on the task experiment paradigm designed in step S3, build the experimental environment and apparatus, 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 stimuli, and the interval between target stimuli are determined. The experimental sequence adopts a Latin square experimental design.

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

[0014] S51. The performance indicators are determined as the accuracy rate and reaction time of task completion, where the formula for calculating the accuracy rate is shown in Equation (1-1):

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

[0016] In the formula, ACC i Let x be the accuracy of the i-th task; i The number of times the operator makes a correct response to the stimulus shown in the i-th task experiment; N is the total number of times the stimulus appears in the i-th task experiment, N = 40;

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

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

[0019] In the formula, T reac T represents the reaction time of the i-th task in the task phase for a successful trial; press The time the operator presses the button; T onset The duration of presentation of the experimental stimulus material;

[0020] S52. Combining the NASA-TLX scale, pupil diameter, and P300 peak value, principal component analysis is used to reduce the dimensionality of all indicator measurement data to obtain a comprehensive indicator to reflect the operator's workload. This includes the following sub-steps:

[0021] S521. Since the task completion accuracy rate is negatively correlated with the workload rate, equation (1-3) is used to positively process the accuracy rate:

[0022]

[0023] In the formula, x′ i This is the positive-directed value of the accuracy metric for the i-th task;

[0024] S522. Different dimensions are used for each indicator. The data is standardized based on equation (1-4) to eliminate the influence of dimensions:

[0025]

[0026] In the formula, The value is the standardized value; Let j be the sample mean of the j-th indicator, i.e. n is the number of operators; Let be the sample standard deviation of the j-th indicator, i.e.

[0027] S523. Perform the KMO test and Bartlett's test to determine if principal component analysis is suitable. If the KMO value is greater than 0.5 and the significance probability of the Bartlett's test of sphericity is less than 0.05, then principal component analysis is suitable.

[0028] S524. Perform principal component extraction. Based on the component matrix of the principal components, and according to the loading percentage of each factor, the calculation formula for the comprehensive loading index score is as shown in equation (1-5):

[0029] AWL=a0x0+a1x1+a2x2+a3x3+a4x4 (1-5)

[0030] 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; and x4 is the standardized P300 peak value.

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

[0032]

[0033] In the formula, x new The normalized value; x min x is the minimum value among the overall scores of all tasks; max This represents the maximum value among the overall scores for all tasks.

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

[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 / search / monitoring.

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

[0037] Step S31: Based on the relevant descriptions of V0-V7 in the VCP scale and reproduce the typical tasks in the relevant process, map the eight visual channel resource types V0-V7 one by one with the traditional cognitive psychology experimental paradigms to obtain the experimental paradigm selection results.

[0038] Step S32: Based on the screening results of existing experimental paradigms, eight specific experimental paradigms with visual channel resource types V0-V7 that can characterize workload are obtained.

[0039] Preferably, the eight selected experimental paradigms in step S3 are, in order, 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.

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

[0041] S41. The experimenter uses computer equipment to display the purpose of this experiment to the operator and provides background knowledge training.

[0042] S42. The operator adjusts the seat independently, the experimenter adjusts the eye tracker angle, the operator wears an EEG device and performs 9-point calibration and verification of the eye tracker, and checks that the EEG signal output is normal.

[0043] S43. Start the experiment. The operator observes the human-computer interaction interface of the task and conducts a test for a duration of T minutes.

[0044] S44. After the operator is familiar with all tasks and passes the test requirements, the experimenter will be prompted to rest for t minutes via computer equipment.

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

[0046] S46. Begin the formal experimental phase. The duration of a single task for the operator is 2 minutes.

[0047] S47. After a single task is completed, the experimenter collects the operator's resting-state EEG data for t minutes using computer equipment.

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

[0049] 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.

[0050] S410. The experimenter guides the operator to review all tasks using computer equipment and fill in the task workload visual channel resource quantity table, 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 principles of complex task paradigms.

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

[0054] The experimental paradigm construction unit constructs an experimental paradigm based on the obtained visual channel resource types and their corresponding task mapping relationships;

[0055] The experimental process construction unit builds the experimental environment and apparatus 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 procedure, 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 capable of running on a processor.

[0058] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0059] (1) The method of the present invention is based on hierarchical task analysis to systematically analyze and deconstruct real tasks, classify them into specific resource channel levels, identify key variables and influencing factors, and provide database support for the screening of psychological paradigms.

[0060] (2) The method of this invention is based on a psychological paradigm to design specific experiments to simulate real task situations, which can reflect the main characteristics and operation process of real tasks. Based on the description of visual channel resource types in the VCP scale, tasks with matching resource requirements are selected and correspond to specific experimental paradigms, so that the paradigm design and specific tasks have consistent sensory input and operation requirements, which are more in line with the task execution process and the results are more convincing.

[0061] (3) Considering that the theoretical basis of the expert evaluation method is still lacking, and it is sometimes difficult to guarantee the objectivity and accuracy of the evaluation results, the present invention proposes a comprehensive analysis method that combines the NASA-TLX scale, reaction time and accuracy of task completion, pupil diameter and P300 peak value data, and obtains more effective and reliable workload visual channel resource quantification results by using subjective and objective data analysis.

[0062] (4) The method of the present invention designs a psychological paradigm that fits typical human-computer interaction tasks, collects experimental data and performs principal component and normalization analysis to obtain the quantitative results of visual channel resources of workload. The overall trend is consistent with the existing VCP scale trend, indicating 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 VCP scale is optimized to make it more suitable for tasks and system design in different fields in my country. Attached Figure Description

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

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

[0065] Figure 3 This is a schematic diagram illustrating the selection of a reaction-time task paradigm in an embodiment of the present invention;

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

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

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

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

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

[0071] Figure 9 This is a flowchart of the overall experimental process in an embodiment of the present invention;

[0072] Figure 10 This is a schematic block diagram of the computer device of the present invention. Detailed Implementation

[0073] Specifically, on the one hand, the present invention provides a method for quantifying visual channel resources of workload. It designs an experimental paradigm by introducing fixed cognitive and psychomotor resource types and combining them with different visual channel resource types. The experimental paradigm with changes in resource types is used as the independent variable, and a comprehensive index that can reflect changes in workload is used as the dependent variable. The experimental process is carried out to collect index data, and the index data is processed and analyzed by principal component analysis. The results are compared and analyzed with the workload measurement results of the baseline task (task without visual activity) to quantify the visual channel resources of workload.

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

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

[0076] In one specific embodiment, step S1 determines the experimental paradigm of visual channel resource type change as the independent variable, and the dependent variables as NASA-TLX scale, task completion accuracy and reaction time, pupil diameter and P300 peak value.

[0077] S2. Based on the assignment method determined in step S1, construct the mapping relationship between visual channel resource types and tasks. The specific method is as follows:

[0078] Based on VACP theory and combined with the task environment and the visual function and motion characteristics of the human eye, the visual tasks of the operator in the process of performing tasks are analyzed, summarized and generalized, resulting in 8 types of visual channel resources; the 8 visual channel resource types are defined as V0-V7, and the remaining resource channel types are fixed to determine the task mapping corresponding to V0-V7.

[0079] In one 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 / search / 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 descriptions of V0-V7 in the VACP scale and the typical tasks in the relevant process, map the eight visual channel resource types V0-V7 one by one with the traditional cognitive psychology experimental paradigms to obtain the experimental paradigm selection results.

[0082] Step S32: Based on the screening results of existing experimental paradigms, eight specific experimental paradigms with visual channel resource types V0-V7 that can characterize workload are obtained.

[0083] Preferably, the eight selected experimental paradigms in step S3 are, in order, 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.

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

[0085] Based on the experimental paradigms of each flight mission in step S3, the duration of the experimental phase, the number of target stimuli, and the interval between target stimuli are determined, and the experimental sequence adopts a Latin square experimental design.

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

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

[0088] S42. The operator adjusts the seat independently, the experimenter adjusts the eye tracker angle, the operator wears an EEG device and performs 9-point calibration and verification of the eye tracker, and checks that 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 for a duration of T minutes.

[0090] S44. After the operator is familiar with all tasks and passes the test requirements, the experimenter will be prompted to rest for t minutes via computer equipment.

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

[0092] S46. Begin the formal experimental phase. The duration of a single task for the operator is 2 minutes.

[0093] S47. After a single task is completed, the experimenter collects the operator's resting-state EEG data for t minutes using computer equipment.

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

[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 using computer equipment and fill in the task workload visual channel resource quantity table, and then ends the experiment.

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

[0098] S51. The performance indicators are determined as the accuracy rate and reaction time of task completion, where the formula for calculating the accuracy rate is shown in Equation (1-1):

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

[0100] In the formula, ACC i Let x be the accuracy of the i-th task; i The number of times the operator makes a correct response to the stimulus shown in the i-th task experiment; N is the total number of times the stimulus appears in the i-th task experiment, N = 40;

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

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

[0103] In the formula, T reac T represents the reaction time of the i-th task in the task phase for a successful trial; press The time the operator presses the button; T onset The duration of the presentation of the experimental stimulus material.

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

[0105] S521. Since the task completion accuracy rate is negatively correlated with the workload rate, equation (1-3) is used to positively process the accuracy rate:

[0106]

[0107] In the formula, x′ i This is the positive-directed value of the accuracy metric for the i-th task.

[0108] S522. Different dimensions are used for each indicator. The data is standardized based on equation (1-4) to eliminate the influence of dimensions:

[0109]

[0110] In the formula, The value is the standardized value; Let j be the sample mean of the j-th indicator, i.e. n is the number of operators; Let be the sample standard deviation of the j-th indicator, i.e.

[0111] S523. Perform the KMO test and Bartlett's test to determine if principal component analysis is suitable. If the KMO value is greater than 0.5 and the significance probability of the Bartlett's test of sphericity is less than 0.05, then principal component analysis is suitable.

[0112] S524. Perform principal component extraction. Based on the component matrix of the principal components, and according to the loading percentage of each factor, the calculation formula for the comprehensive loading index score is as shown in equation (1-5):

[0113] AWL=a0x0+a1x1+a2x2+a3x3+a4x4 (1-5)

[0114] 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; and x4 is the standardized P300 peak value.

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

[0116]

[0117] In the formula, x new The normalized value; x min x is the minimum value among the overall scores of all tasks; max This represents the maximum value among the overall scores for all tasks.

[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 principles of complex task paradigms.

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

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

[0122] The experimental process construction unit builds the experimental environment and apparatus and constructs the experimental process based on the constructed task experimental paradigm.

[0123] The workload visual channel resource quantification unit conducts experiments according to the constructed experimental procedure, collects NASA-TLX scale data, task completion accuracy and reaction time, pupil diameter and P300 peak data, performs 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 capable of running on a processor.

[0125] like Figure 10 As shown, the computer device includes a processor, memory, input / output interface, and communication interface. The processor, memory, and 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 provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores transactions to be processed. The input / output interface is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals via a network connection.

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

[0127] Example 1

[0128] This embodiment provides a method for quantifying visual channel resources for workload, such as... Figure 1 As shown, the method includes the following steps:

[0129] S1. To accurately understand the characteristics of visual channel resource types and the differences between them, this study summarizes the definition and characteristics of each visual channel resource type, maps its linguistic anchors to relevant psychological paradigms 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 linguistic anchors, more effective and reliable quantitative results of workload visual channel resources are obtained based on the degree of change in the operator's comprehensive indicators. Workload cognitive and psychomotor channel resources are introduced into the task design, with the load levels of these two channels used as control variables and set to fixed levels. The workload induced by tasks corresponding to different visual channel resources is measured, and the index data is processed and analyzed using principal component analysis. The results are compared with the workload measurement results of the baseline task (task without visual activity). The quantitative results of visual channel resource types are obtained through normalization analysis. Since the existing VCP scale is a 7-point scale, for ease of comparison and discussion, the normalized quantitative results are multiplied by 7 to obtain the final result.

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

[0131] S2. Based on VCP theory and combined with the flight mission environment, as well as the visual function and motion characteristics of the human eye, the visual tasks of pilots during mission execution are analyzed, summarized, and generalized. The following eight types of visual channel resources can comprehensively describe the visual perception requirements of all visual-related tasks during flight:

[0132] Actions without visual requirements, perception / detection (detecting the appearance of an image), visual discrimination (detecting visual differences), visual inspection / verification (discrete inspection / static conditions), visual positioning / alignment (selective orientation), visual tracking / following (maintaining orientation), visual reading (symbols), and visual scanning / search / monitoring (continuous / serial inspection, multiple conditions).

[0133] Based on hierarchical task analysis, and referencing existing literature, flight operation tasks were decomposed and organized. Combining the analysis of resource types and task requirements, a mapping between flight tasks and resource types was achieved. On this basis, flight operation tasks with visual channel resource levels ranging from 0 to 7 were compiled. Table 1 summarizes the descriptions of specific flight tasks with visual channel load levels of V0-V7, cognitive channel load level of C2, and psychomotor channel load level of P2, serving as the task basis for psychological paradigm selection.

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

[0135]

[0136]

[0137] S3. Based on the visual channel resource types and their task mapping relationship obtained in step S2, construct the experimental paradigm. The specific steps are as follows:

[0138] S31. Based on the relevant descriptions of V0-V7 in the VCP scale and reproducing typical tasks in relevant models, the eight visual channel resource types V0-V7 are mapped one-to-one with traditional cognitive psychology experimental paradigms to obtain the experimental paradigm selection results. The specific mapping process is as follows:

[0139] This invention, combining specific descriptions of four resource channel types with typical flight missions in relevant aircraft models, selected eight experimental paradigms from the perspectives of human-computer interaction interface and mission resource requirements. These paradigms characterize different resource types V0-V7 of the visual channel for workload, with the cognitive channel at C2 and the psychomotor channel at P2. Through literature review and in conjunction with the description of visual channel resource types in step S2, the experimental paradigms used in this experiment were determined to be, in order: 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 selection results of experimental paradigms corresponding to different resource types of the visual channel for workload are shown in Table 2.

[0140] Table 2. Results of experimental paradigm selection for visual channel resource types.

[0141]

[0142]

[0143] S32. Based on the existing experimental paradigm selection results, eight specific experimental paradigms with visual channel resource types V0-V7 that can characterize workload were obtained. The specific design of each flight mission (hereinafter referred to as each Block i mission) was determined in conjunction with the actual scenario as follows:

[0144] Block 0 task

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

[0146] Block 1 mission

[0147] The Block 1 task requirements are V1+C2+P2. Based on the paradigm selection results, the experimental paradigm that meets the Block 1 task requirements is determined to be the detection-response task. For example... Figure 2 As shown, in this task, the operator first observes the cross-shaped fixation point appearing on the screen for a random number T1 between 500-800ms. To prevent the operator from predicting the timing of the stimulus instead of noticing it and responding, a blank screen is displayed for a period of time before the stimulus is shown, with the blank screen lasting for a random number T2 between 200ms-500ms. Then, the operator needs to pay attention to the position of the yellow disc appearing on the screen. If the yellow disc appears at the position of the first light, the operator needs to press the number key "1" as quickly as possible; if the yellow disc appears at the position of the second light, the operator needs to press the number key "2" as quickly as possible. The system records the operator's reaction time T3 for this trial. To ensure that each trial lasts 15 seconds, a blank screen appears after the operator's response. The display time T of the blank screen is calculated as shown in equation (3-1):

[0148] T = 15000ms - T1 - T2 - T3 (3-1)

[0149] The display timing of the gaze point and blank screen in Blocks 2-7 follows the same pattern as in Block 1.

[0150] Block 2 mission

[0151] The resource requirements for Block 2 are V2+C2+P2. Based on the paradigm selection results, the experimental paradigm that meets the requirements of Block 2 is determined to be a reaction time task. For example... Figure 3 As shown, in this task, the operator needs to observe the Z or M stimulus that appears on the screen and respond by pressing the corresponding Z and M keys as quickly as possible.

[0152] Block 3 mission

[0153] The resource requirements for Block 3 are V3+C2+P2. Based on the paradigm selection results, the visual search experimental paradigm was determined to meet the requirements of Block 3. For example... Figure 4 As shown, in this task, the operator needs to observe the four numbers appearing on the screen and find the position of the number 1 as quickly as possible, then press the corresponding number key 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 for the Block 4 task are V4+C2+P2. Based on the paradigm selection results, the visual matching experimental paradigm was confirmed as the one that meets the requirements of the Block 4 task. Figure 5 As shown, in this task, the operator needs to observe the randomized numeric keypad on the screen and find the target number as quickly as possible, then press the corresponding number key. When the target number appears in the bottom left corner, the operator's correct response is to press the number key 1; when the target number appears in the second position from the left 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 for the Block 5 task are V5+C2+P2. Based on the paradigm selection results, the visual tracking experimental paradigm was confirmed as the one that meets the requirements of the Block 5 task. Figure 6 As shown in the image. In this task, the screen displays nine intertwined curves, with the endpoints of the curves labeled from left to right with numbers 1-9. A red arrow above indicates the starting point of a line. The operator needs to visually follow the line to see the endpoint and press the corresponding number key.

[0158] Block 6 mission

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

[0160] Block 7 mission

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

[0162] S4. Based on the experimental paradigm design in step S3, the experimental phase was set to last for 10 minutes, during which a total of 40 target stimuli were presented, averaging once every 15 seconds. The experimental sequence adopted a Latin square experimental design to eliminate the influence of factors such as fatigue on the operator.

[0163] In this embodiment, as Figure 9 As shown, the overall experimental procedure is as follows:

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

[0165] S42. The operator should adjust the seat independently, and the experimenter should adjust the eye tracker angle accordingly. The operator should then be fitted with the EEG device. The operator should cooperate in performing the 9-point calibration and verification of the eye tracker. The experimenter should check that the EEG signal output is normal.

[0166] S43. Start the experiment. The operator first observes the human-computer interaction interface of the task and conducts a test that takes a total of 16 minutes.

[0167] S44. Once the operator is familiar with all tasks and passes the test requirements, the operator is forced to take a 5-minute silent rest.

[0168] S45. After the operator has finished resting and indicated that he / she is in good condition, collect 5 minutes of resting-state EEG data from the operator.

[0169] S46. Begin the formal experiment. Operators should strive for the best performance. Each task lasts for 10 minutes.

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

[0171] S48. Please have the operator use the NASA-TLX scale to evaluate the subjective workload of this mission.

[0172] S49. Change the experimental task and repeat steps S43 to S47 to carry out the task until all resource type measurement task data are fully collected; to avoid the fatigue effect caused by the task order leading to changes in the operator's fatigue level, the task order is balanced among operators.

[0173] S410. Under the guidance of the experimenter, the operator reviews all tasks and fills in the task workload visual channel resource table, thus ending the experiment process for one operator.

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

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

[0176] In the formula, ACC i x represents the accuracy of the Block i task; i The number of times the operator correctly responded to the stimulus shown in the Block i experiment; N is the total number of times the stimulus appeared in the Block i experiment, N = 40.

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

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

[0179] In the formula, T reac T is the reaction time for the number of successful trials in the Block i task phase; press The time the operator presses the button; T onset The duration of the presentation of the experimental stimulus material.

[0180] To more comprehensively and accurately reflect the characteristics and variation patterns of operator workload, we considered combining multiple indicators such as the NASA-TLX scale, pupil diameter, and P300 peak value. Principal component analysis was used to reduce the dimensionality of the measurement data of all indicators, and finally obtained a comprehensive indicator to reflect the operator workload.

[0181] S51. Since the task completion accuracy rate index and the load index are negatively correlated, the accuracy rate index is positively processed using formula (1-3).

[0182]

[0183] In the formula, x′ i This is the positive-positive value of the accuracy metric for the Block i task.

[0184] S52. Different dimensions are used for each indicator. The data is standardized based on equation (1-4) to eliminate the influence of dimensions.

[0185]

[0186] In the formula, The value is the standardized value; Let j be the sample mean of the j-th indicator, i.e. n is the number of operators. Let be the sample standard deviation of the j-th indicator, i.e.

[0187] S53. Perform the KMO test and Bartlett's test to determine if principal component analysis is suitable. The KMO value is 0.64, which is greater than 0.5, indicating a certain correlation between the variables. The significance probability of the Bartlett's test of sphericity is 0.000, which is less than 0.05. These tests demonstrate that the experimental data is suitable for principal component analysis.

[0188] S54. Principal component extraction is performed, yielding the component matrix of the principal components, also known as factor loadings. Based on the loading percentage of each factor, the formula for calculating the Aggregative Workload (AWL) score is shown in equation (1-5):

[0189] AWL=0.218x0+0.217x1+0.204x2+0.207x3+0.207x4 (1-5)

[0190] 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; and x4 is the standardized P300 peak value.

[0191] S55. Normalize the overall score of each task according to equation (1-5). Since the resource requirements for tasks Block 0-Block 7 in this experiment are V0+C2+P2, V1+C2+P2, ..., V7+C2+P2 respectively, the normalization formula uses xx... min The scores of tasks V1-V7 are all subtracted from V0+C2+P2. The normalized result is multiplied by 7 to obtain the quantization result corresponding to V1 to V7.

[0192]

[0193] In the formula, x new The normalized value; x min x is the minimum value among the overall scores of all tasks; max This represents the maximum value among the overall scores for all tasks.

[0194] By designing a psychological paradigm that fits human-computer interaction flight missions, and collecting and comprehensively analyzing experimental data, the quantitative results of visual channel resources for workload were obtained. The overall trend is consistent with the existing VCP scale, indicating the rationality of the paradigm design. The overall task difficulty shows an upward trend in the visual channel. Further data analysis verifies the effectiveness of the design method and optimizes the existing VCP scale to make it more suitable for flight missions and system design in my country.

[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. The internal structure of the computer device is shown in the figure below. Figure 10 As shown, the computer device includes a processor, memory, input / output interfaces, and a communication interface. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores pending transactions. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a workload visual channel resource quantization method as described in Embodiment 1.

[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, data stored, data displayed, etc.) involved in this invention are all information and data authorized by the object or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0198] The above analysis demonstrates the effectiveness of the workload visual channel resource quantification method based on a psychological paradigm provided in this invention. This invention uses a psychological paradigm to perform equivalent mapping of complex intelligent human-computer interaction tasks, employing a combination of subjective and objective methods to measure the workload of different types of human-computer interaction tasks with varying intensities. This yields more effective and reliable evaluation results of workload visual channel resource types, enabling workload visual channel resource quantification and prediction applicable to the characteristics of Chinese operators during the system design phase. This leads to a better understanding of task requirements, optimized task design, and improved work efficiency and safety.

[0199] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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 document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

[0201] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for quantifying visual channel resources for workload, characterized in that: Specifically, it includes the following steps: 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, take the experimental paradigms of resource type changes as independent variables, and take the comprehensive index that can reflect workload changes as dependent variables. S2. Based on the assignment method determined in step S1, construct the mapping relationship between visual channel resource types and tasks. The specific method is as follows: Based on the VCP theory and combined with the task environment and the visual function and motion characteristics of the human eye, the visual tasks of the operator in the process of performing tasks are analyzed, summarized and generalized, resulting in 8 types of visual channel resources; the 8 visual channel resource types are defined as V0-V7, and the remaining resource channel types are fixed to determine the task mapping corresponding to V0-V7. S3. Based on the visual channel resource types and their corresponding task mapping relationships obtained in step S2, construct the experimental paradigm. The specific method is as follows: The task mapping results were used as the basis for screening psychological paradigms. Based on the relevant descriptions of V0-V7 in the VCP scale and the typical tasks in the relevant process, the eight visual channel resource types V0-V7 were mapped one by one with the traditional cognitive psychology experimental paradigms to obtain the experimental paradigm screening results. The experimental paradigms for each specific task were determined in combination with the actual scenario. S4. Based on the task experiment paradigm designed in step S3, build the experimental environment and apparatus, 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 stimuli, and the interval between target stimuli are determined. The experimental sequence adopts a Latin square experimental design. S5. Conduct the experiment according to the experimental procedure constructed in step S4, collect NASA-TLX scale data, task completion accuracy and reaction time, pupil diameter and P300 peak data, and perform principal component and normalization analysis to realize the quantification of visual channel resources of workload based on multi-resource theory. This includes the following sub-steps: S51. The performance indicators are determined as the accuracy rate and reaction time of task completion, where the formula for calculating the accuracy rate is shown in Equation (1-1): ACC i =x i / N(1-1) In the formula, ACC i Let x be the accuracy of the i-th task; i The number of times the operator makes a correct response to the stimulus shown in the i-th task experiment; N is the total number of times the stimulus appears in the i-th task experiment, N = 40; The formula for calculating the reaction time is shown in equation (1-2): T reac =T press -T onset (1-2) In the formula, T reac T represents the reaction time of the i-th task in the task phase for a successful trial; press The time the operator presses the button; T onset The duration of presentation of the experimental stimulus material; S52. Combining the NASA-TLX scale, pupil diameter, and P300 peak value, principal component analysis is used to reduce the dimensionality of all indicator measurement data to obtain a comprehensive indicator to reflect the operator's workload. This includes the following sub-steps: S521. Since the task completion accuracy rate is negatively correlated with the workload rate, equation (1-3) is used to positively process the accuracy rate: In the formula, x′ i This is the positive-directed value of the accuracy metric for the i-th task; S522. Different dimensions are used for each indicator. The data is standardized based on equation (1-4) to eliminate the influence of dimensions: In the formula, The value is the standardized value; Let j be the sample mean of the j-th indicator, i.e. n is the number of operators; Let be the sample standard deviation of the j-th indicator, i.e. S523. Perform the 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 the Bartlett sphericity test is less than 0.05, then principal component analysis is suitable. S524. Perform principal component extraction. Based on the component matrix of the principal components, and according to the loading percentage of each factor, the calculation formula for the comprehensive loading index score is as shown in equation (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; and x4 is the standardized P300 peak value. S525. Normalize the comprehensive score of each task according to equation (1-5). Multiply the normalized result by 7 to get the quantization result corresponding to V1 to V7. The normalization is shown in equation (1-6): In the formula, x new The normalized value; x min x is the minimum value among the overall scores of all tasks; max This represents the maximum value among the overall scores for all tasks.

2. The method for quantifying visual channel resources of workload according to claim 1, characterized in that: In step S1, the experimental paradigm with the independent variable being the change in visual channel resource type was determined, and the dependent variables were the NASA-TLX scale, the accuracy and reaction time of task completion, pupil diameter, and P300 peak value.

3. The method for quantifying workload visual channel resources according to claim 1, characterized in that: 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 / search / monitoring.

4. The method for quantifying visual channel resources of workload according to claim 1, characterized in that: Step S3 specifically includes the following sub-steps: Step S31: Based on the relevant descriptions of V0-V7 in the VCP scale and reproduce the typical tasks in the relevant process, map the eight visual channel resource types V0-V7 one by one with the traditional cognitive psychology experimental paradigms to obtain the experimental paradigm selection results. Step S32: Based on the screening results of existing experimental paradigms, eight specific experimental paradigms with visual channel resource types V0-V7 that can characterize workload are obtained.

5. The method for quantifying visual channel resources of workload according to claim 1, characterized in that: The eight experimental paradigms selected in step S3 are, in order, 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.

6. The method for quantifying workload visual channel resources according to claim 1, characterized in that: The experimental procedure constructed in step S4 includes the following sub-steps: S41. The experimenter uses computer equipment to display the purpose of this experiment to the operator and provides background knowledge training. S42. The operator adjusts the seat independently, the experimenter adjusts the eye tracker angle, the operator wears an EEG device and performs 9-point calibration and verification of the eye tracker, and checks that the EEG signal output is normal. S43. Start the experiment. The operator observes the human-computer interaction interface of the task and conducts a test for a duration of T minutes. S44. After the operator is familiar with all tasks and passes the test requirements, the experimenter will be prompted to rest for t minutes via computer equipment. S45. After the operator has finished resting and indicated that he is in good condition, the experimenter collects resting-state EEG data for t minutes using computer equipment. S46. Begin the formal experimental phase. The duration of a single task for the operator is 2 minutes. S47. After a single task is completed, the experimenter collects the operator's resting-state EEG data for t minutes using computer equipment. S48. The operator uses the NASA-TLX scale to evaluate the subjective workload of this mission; 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. S410. The experimenter guides the operator to review all tasks using computer equipment and fill in the task workload visual channel resource quantity table, and then ends the experiment.

7. The method for quantifying workload visual channel resources according to claim 1, characterized in that: In step S1, the baseline is considered to be the task when there is no 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 and 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 principles of complex task paradigms. The mapping relationship construction unit between visual channel resource types and tasks constructs the mapping relationship between visual channel resource types and tasks according to the determined assignment method; The experimental paradigm construction unit constructs an experimental paradigm based on the obtained visual channel resource types and their corresponding task mapping relationships; The experimental process construction unit builds the experimental environment and apparatus 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 procedure, 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 of claim 1, characterized in that: It includes: Computer equipment and optimized systems stored on computer equipment and capable of running on a processor.

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