Mental workload online detection method based on forehead electroencephalogram signals

An EEG signal and brain load technology, applied in diagnostic recording/measurement, medical science, psychological devices, etc., can solve problems such as complex operation, affecting operation performance, subject discomfort, etc., to achieve convenient operation and convenient online detection. , the effect of improving accuracy and simplicity

Active Publication Date: 2014-03-05
禹锡科技(天津)有限公司
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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 comp

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  • Mental workload online detection method based on forehead electroencephalogram signals
  • Mental workload online detection method based on forehead electroencephalogram signals
  • Mental workload online detection method based on forehead electroencephalogram signals

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Embodiment Construction

[0029] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0030] see figure 1 with figure 2 , different from the classic EEG analysis method, this method calculates the wavelet multi-scale information entropy of EEG, which combines the advantages of wavelet transform and information entropy, can characterize the complexity of the EEG sequence, and thus obtain a higher classification accuracy , see the description below:

[0031] 101: Using silver / silver chloride electrodes as sensors to collect forehead EEG signals;

[0032] It is a non-invasive electrode with strong anti-interference ability, which can ensure reliable recording of slow potential. For electrode placement see figure 1 As shown in the black rectangle box in , they are the forehead two-lead acquisition electrode and the lef...

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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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Application Information

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IPC IPC(8): A61B5/00A61B5/16A61B5/0476
Inventor 明东李南南王坤柯余峰綦宏志周鹏张力新赵欣万柏坤
Owner 禹锡科技(天津)有限公司
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