Mental workload online detection method based on forehead electroencephalogram signals

Abstract

The invention discloses a mental workload online detection method based on forehead electroencephalogram signals. The method comprises the following steps that the forehead electroencephalogram signals are collected with a silver / silver chloride electrode as a sensor; an electroencephalogram amplifier is used for carrying out amplification and filtering on the forehead electroencephalogram signals, then data preprocessing is carried out, and the processed forehead electroencephalogram signals are acquired; a stimulation task is compiled as n-back; wavelet multiscale entropy features are extracted from the processed forehead electroencephalogram signals; model recognition is carried out on the wavelet multiscale entropy features through a support vector machine, and an obtained result is the mental workload level and recognition accuracy of data. The experiment process of the method is carried out on the forehead, the need for washing the head before and after the process is avoided, the operation is facilitated, and meanwhile the influence on signal collection by the hair and the scalp is avoided. The method can effectively improve the accuracy and convenience of a mental workload detection system and obtain considerable social benefits and economic benefits.

Description

technical field [0001] The invention relates to the field of mental load detection, in particular to an online detection method of mental load based on forehead electroencephalogram signals. Background technique [0002] In recent years, with the rapid development of information technology, the degree of human mental load in operation tasks has been increasing, and mental load has become an important subject that must be considered in system design, and its detection technology has attracted widespread attention. Mental load refers to the amount of attention paid by the operator to achieve the performance standard, which involves the work requirements, time pressure, ability and effort of the operator when completing a certain task, and the frustration when the task is not smooth. [0003] It can be known from the definition that mental load is a multidimensional concept. Currently, there are four main methods for measuring mental load: (1) Subjective measurement method: Thi...

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Problems solved by technology

[0005] The traditional EEG signal acquisition method needs to be equipped with multi-lead electrode caps, and conductive paste needs to be applied during the experiment. The operation is more complicated, and it brings discomfort to the subjects, which affects their operational performance. These are online detection of mental load Development of methods and instruments presents challenges

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