Optimized electroencephalogram and functional near-infrared spectroscopy-based mental workload detection method for practical applications.

BACKGROUND: Mental workload is a critical consideration in complex man-machine systems design. Among various mental workload detection techniques, multimodal detection techniques integrating electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals have attracted considerable attention. However, existing EEG-fNIRS-based mental workload detection methods have certain defects, such as complex signal acquisition channels and low detection accuracy, which restrict their practical application. METHODS: The signal acquisition configuration was optimized by analyzing the feature importance in mental workload recognition model and a more accurate and convenient EEG-fNIRS-based mental workload detection method was constructed. A classical Multi-Task Attribute Battery (MATB) task was conducted with 20 participating volunteers. Subjective scale data, 64-channel EEG data, and two-channel fNIRS data were collected. RESULTS: A higher number of EEG channels correspond to higher detection accuracy. However, there is no obvious improvement in accuracy once the number of EEG channels reaches 26, with a four-level mental workload detection accuracy of 76.25 ± 5.21%. Partial results of physiological analysis verify the results of previous studies, such as that the θ power of EEG and concentration of O2Hb in the prefrontal region increase while the concentration of HHb decreases with task difficulty. It was further observed, for the first time, that the energy of each band of EEG signals was significantly different in the occipital lobe region, and the power of [Formula: see text] and [Formula: see text] bands in the occipital region increased significantly with task difficulty. The changing range and the mean amplitude of O2Hb in high-difficulty tasks were significantly higher compared with those in low-difficulty tasks. CONCLUSIONS: The channel configuration of EEG-fNIRS-based mental workload detection was optimized to 26 EEG channels and two frontal fNIRS channels. A four-level mental workload detection accuracy of 76.25 ± 5.21% was obtained, which is higher than previously reported results. The proposed configuration can promote the application of mental workload detection technology in military, driving, and other complex human-computer interaction systems.

[An overview on sleep research based on functional near infrared spectroscopy].

Sleep is a complex physiological process of great significance to physical and mental health, and its research scope involves multiple disciplines. At present, the quantitative analysis of sleep mainly relies on the "gold standard" of polysomnography (PSG). However, PSG has great interference to the human body and cannot reflect the hemodynamic status of the brain. Functional near infrared spectroscopy (fNIRS) is used in sleep research, which can not only meet the demand of low interference to human body, but also reflect the hemodynamics of brain. Therefore, this paper has collected and sorted out the related literatures about fNIRS used in sleep research, concluding sleep staging research, clinical sleep monitoring research, fatigue detection research, etc. This paper provides a theoretical reference for scholars who will use fNIRS for fatigue and sleep related research in the future. Moreover, this article concludes the limitation of existing studies and points out the possible development direction of fNIRS for sleep research, in the hope of providing reference for the study of sleep and cerebral hemodynamics.

[Research on enhancement of mental rotation ability based on transcranial direct current stimulation].

Transcranial direct current stimulation (tDCS) is a non-invasive low-current brain stimulation technique, which is mainly based on the different polarity of electrode stimulation to make the activation threshold of neurons different, thereby regulating the excitability of the cerebral cortex. In this paper, healthy subjects were randomly divided into three groups: anodal stimulation group, cathodal stimulation group and sham stimulation group, with 5 subjects in each group. Then, the performance data of the three groups of subjects were recorded before and after stimulation to test their mental rotation ability, and resting state and task state electroencephalogram (EEG) data were collected. Finally, through comparative analysis of the behavioral data and EEG data of the three groups of subjects, the effect of electrical stimulation of different polarities on the three-dimensional mental rotation ability was explored. The results of the study found that the correct response time/accuracy rate and the accuracy rate performance of the anodal stimulation group were higher than those of the cathodal stimulation and sham stimulation groups, and there was a significant difference ( P < 0.05). The alpha wave power analysis found that the mental rotation mainly activates the frontal lobe, central area, parietal lobe and occipital lobe. In the anodal stimulation group, the alpha wave power changed significantly in the frontal lobe and occipital lobe ( P < 0.05). The results of this paper show that anodal stimulation group can improve the mental rotation ability of the subjects to a certain extent. The results of this paper can provide important theoretical support for further research on the mechanism of tDCS on mental rotation ability.

[Review of cognitive enhancement techniques based on the combination of cognitive training and transcranial direct current stimulation].

Cognitive enhancement refers to the technology of enhancing or expanding the cognitive and emotional abilities of people without psychosis based on relevant knowledge of neurobiology. The common methods of cognitive enhancement include transcranial direct current stimulation (tDCS) and cognitive training (CT). tDCS takes effect quickly, with a short effective time, while CT takes longer to work, requiring several weeks of training, with a longer effective time. In recent years, some researchers have begun to use the method of tDCS combined with CT to regulate the cognitive function. This paper will sort out and summarize this topic from five aspects: perception, attention, working memory, decision-making and other cognitive abilities. Finally, the application prospect and challenges of technology are prospected.