Mental workload assessment method based on multi-physiological parameter method integration

Abstract

The invention discloses a mental workload assessment method based on multi-physiological parameter method integration. The method includes the steps of 1, designing controlled variable experiments oriented to five characters of a target complex task, acquiring functional physiological data of the experiments, and preprocessing the acquired functional physiological data; 2, completing the extraction of sensitive physiological characteristics reflecting the changes of different characters on mental workloads from the physiological data; 3, screening the physiological characteristics to remove interference information in the physiological characteristics; 4, integrating physiological indexes under different characters to obtain a comprehensive physiological parameter characteristic system; 5,according to the physiological characteristics under different characters, conducting regression on the physiological data under the task characters by machine learning; 6, according to the comprehensive physiological indexes, describing the mental workload level of a current operator. By means of the method, the operation result can be directly evaluated, and high real-time performance is achieved; besides, the accuracy is high, and the status of task execution personnel can be monitored in real time.

Description

Technical field [0001] The invention relates to a mental load assessment method based on the fusion of multiple physiological parameter methods. Background technique [0002] Mental workload detection is an important research content of ergonomics, which has an important impact on the safety and reliability of human-machine systems. The mental load includes tasks such as decision-making, control, and monitoring. On the one hand, the complexity of the manned spacecraft system and operating task environment has caused the amount of information to be processed by astronauts has increased sharply, and the cognitive resources occupied by astronauts are often high. Load level, which induces rapid fatigue, decreased perception, increased human error and negative emotions, resulting in decision-making errors and decreased performance. On the other hand, missions such as surveillance will cause astronauts to be out of the loop, decrease their attention, and neglect risk factors to cause ...

AI Technical Summary

Problems solved by technology

A single measurement method cannot fully reflect the characteristics of mental load changes, and the method of multi-physiological integration can solve the problem of mental load measurement from multiple levels

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