Review of EEG and ERP studies of extraversion personality for baseline and cognitive tasks

Roslan, Nur Syahirah; Izhar, Lila Iznita; Faye, Ibrahima; Saad, Mohamad Naufal Mohamad; Sivapalan, Subarna; Rahman, Mohammad Abdul

doi:10.1016/j.paid.2017.07.040

Cited by 27 publications

(11 citation statements)

References 61 publications

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“…For human motion imagination signals, the motion characteristics based on the two modes: event-related potential (ERP) [13][14][15][16] and steady-state visual evoked potential (SSVEP) [17,18], are relatively obvious, which are widely used in BCI technology research. Many teams of scientists have carried out research on the application of BCI technology.…”

Section: Introductionmentioning

confidence: 99%

Research on Home-Auxiliary Robot System Based on Characteristics of Human Physiological and Motion Signals

Wang

Zhang

2020

Complexity

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A home-auxiliary robot system based on characteristics of the electrooculogram (EOG) and tongue signal is developed in the current study, which can provide daily life assistance for people with physical mobility disabilities. It relies on five simple actions (blinking twice in a row, tongue extension, upward tongue rolling, and left and right eye movements) of the human head itself to complete the motions (moving up/down/left/right and double-click) of a mouse in the system screen. In this paper, the brain network and BP neural network algorithms are used to identify these five types of actions. The result shows that, for all subjects, their average recognition rates of eye blinks and tongue movements (tongue extension and upward tongue rolling) were 90.17%, 88.00%, and 89.83%, respectively, and after training, the subjects can complete the five types of movements in sequence within 12 seconds. It means that people with physical disabilities can use the system to quickly and accurately complete life self-help, which brings great convenience to their lives.

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Section: Introductionmentioning

confidence: 99%

Research on Home-Auxiliary Robot System Based on Characteristics of Human Physiological and Motion Signals

Wang

Zhang

2020

Complexity

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“…BCI technology is a direct communication method established between the brain and a controlled device, which makes it possible to use the human brain to directly control external devices to assist humans in performing related operations [ 1 , 2 , 3 , 4 ]. The characteristics of human motion, which were collected in previous studies using models of the Event-Related Potential (ERP) [ 5 , 6 , 7 , 8 ] and the Steady-State Visual Evoked Potential (SSVEP) [ 9 , 10 ], are obvious. Additionally, these two models, which have strong anti-interference ability, are widely used in BCI technology research.…”

Section: Introductionmentioning

confidence: 99%

Study of the Home-Auxiliary Robot Based on BCI

Wang

Zhang

et al. 2018

Sensors

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A home-auxiliary robot platform is developed in the current study which could assist patients with physical disabilities and older persons with mobility impairments. The robot, mainly controlled by brain computer interface (BCI) technology, can not only perform actions in a person’s field of vision, but also work outside the field of vision. The wavelet decomposition (WD) is used in this study to extract the δ (0~4 Hz) and θ (4~8 Hz) sub-bands of subjects’ electroencephalogram (EEG) signals. The correlation between pairs of 14 EEG channels is determined with synchronization likelihood (SL), and the brain network structure is generated. Then, the motion characteristics are analyzed using the brain network parameters clustering coefficient (C) and global efficiency (G). Meanwhile, the eye movement characteristics in the F3 and F4 channels are identified. Finally, the motion characteristics identified by brain networks and eye movement characteristics can be used to control the home-auxiliary robot platform. The experimental result shows that the accuracy rate of left and right motion recognition using this method is more than 93%. Additionally, the similarity between that autonomous return path and the real path of the home-auxiliary robot reaches up to 0.89.

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“…Until now, this problem remains open. According to the recent review [ 23 ], the conclusions of the ERP studies of personality were contradictory, probably caused by differences in experimental protocols, sample size, and subject age. Other methods were only focused on the EEG power spectrum analysis.…”

Section: Introductionmentioning

confidence: 99%

Human personality reflects spatio-temporal and time-frequency EEG structure

Maksimenko¹,

Runnova²,

Zhuravlev³

et al. 2018

PLoS ONE

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The reliable and objective assessment of intelligence and personality has been a topic of increasing interest of contemporary neuroscience and psychology. It is known that intelligence can be measured by estimating the mental speed or velocity of information processing. This is usually measured as a reaction time during elementary cognitive task processing, while personality is often assessed by means of questionnaires. On the other hand, human personality affects the way a subject accomplishes elementary cognitive tasks and, therefore, some personality features can define intelligence. It is expected that these features, as well as mental abilities in performing cognitive tasks are associated with the brain’s electrical neural activity. Although several studies reported correlation between event-related potentials, mental ability and intelligence, there is a lack of information about time-frequency and spatio-temporal structures of neural activity which characterize this relation. In the present work, we analyzed human electroencephalograms (EEG) recorded during the performance of elementary cognitive tasks using the Schulte test, which is a paper-pencil based instrument for assessing elementary cognitive ability or mental speed. According to particular features found of the EEG structure, we divided the subjects into three groups. For subjects in each group, we applied the Sixteen Personality Factor Questionnaire (16PF) to assess the their personality traits. We demonstrated that each group exhibited a different score on the personality scale, such as warmth, reasoning, emotional stability and dominance. Summing up, we found a link between EEG features, mental abilities and personality traits. The obtained results can be of great interest for testing human personality to create automatized intelligent programs which combine simple tests and EEG measurements for real estimation of human personality traits and mental abilities.

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Review of EEG and ERP studies of extraversion personality for baseline and cognitive tasks

Cited by 27 publications

References 61 publications

Research on Home-Auxiliary Robot System Based on Characteristics of Human Physiological and Motion Signals

Research on Home-Auxiliary Robot System Based on Characteristics of Human Physiological and Motion Signals

Study of the Home-Auxiliary Robot Based on BCI

Human personality reflects spatio-temporal and time-frequency EEG structure

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