P300 Brain Waves Instigated Semi Supervised Video Surveillance for Inclusive Security Systems

Singh, Anurag; Jotheeswaran, Jeevanandam

doi:10.1007/978-3-030-00563-4_18

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…In future work, more effective classification and fusion methods will be further studied. These studies could provide valuable references for the practical applications of hybrid BCI based on eye-tracking, such as RSVP speller [6,7], Satellite image retrieval [3,4], screening of targets by supervisors [5], and so on.…”

Section: E Future Workmentioning

confidence: 99%

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ERP and Pupillometry Synchronization Analysis on Rapid Serial Visual Presentation of Words, Numbers, Pictures

Luo

Lin

Rong-xiao

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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Hybrid brain-computer interfaces (HBCI) combining eye-tracker has attracted the attentions of researchers in target recognition. However, there are still many issues to be addressed in rapid sequence visual presentation (RSVP) tasks, such as the effect of presentation rates and target types on event-related potentials (ERP) and pupillometry, synchronization analysis of electroencephalography (EEG) and eyetracking, and so on. In this study, the RSVP experiments with three different target types of pictures, words and numbers at the presentation rates of 100 and 200 ms were conducted. EEG data and pupillometry data were synchronously collected from 20 university students. The results of ERP analysis showed that, among three different target types at the presentation rate of 100 ms, the picture P300 component had the largest amplitude and the longest latency. From the 100 ms presentation rates to 200 ms one for the three target types, the P300 amplitudes became smaller, and the P300 latencies became shorter. The results of pupillometry analysis showed that, at the presentation rates of 100 and 200 ms, the pupil dilation of pictures had the smallest amplitude and the shortest latency. At the two presentation rates, no significant differences of pupil size and latency were found for the three target types. For the early pupil dilation within 1000 ms, the picture pupil size was significantly smaller than the other ones, and the picture pupil acceleration had the largest average amplitude and the shortest latency. These pupillometry features within 1000 ms combining with the P300 features could be taken as the effective ones for target classification. Through synchronization analysis of the EEG data and pupillometry data, the effects of target type and presentation rate on ERP and pupil dilation were different. These results could contribute to developing the fusion methods between EEG and eye-tracking, and

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Section: E Future Workmentioning

confidence: 99%

“…RSVP based brain-computer interfaces (BCI) is used to target detection with a RSVP paradigm by analyzing subjects' EEG data. RSVP-BCIs have received extensive researchers' attentions and have broad application prospects, such as Satellite image retrieval [3,4], screening of targets by supervisors [5], RSVP speller [6,7], and so on.…”

Section: Introductionmentioning

confidence: 99%

ERP and Pupillometry Synchronization Analysis on Rapid Serial Visual Presentation of Words, Numbers, Pictures

Luo

Lin

Rong-xiao

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

View full text Add to dashboard Cite

show abstract

“…In the applications that benefit from this paradigm, computers are unable to analyze and understand images with deep semantic and unstructured features as successfully as humans, and the manual analysis tools are slow, which makes the study of RSVP-BCI more and more popular in recent decades. RSVP-BCI has been used in counterintelligence, police, and health care that require professionals to review objects, scenes, people, and other relevant information contained in a large number of images ( Huang et al, 2017 ; Singh and Jotheeswaran, 2018 ; Wu et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

A Benchmark Dataset for RSVP-Based Brain–Computer Interfaces

Zhang

Wang

Zhang³

et al. 2020

Front. Neurosci.

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This paper reports on a benchmark dataset acquired with a brain–computer interface (BCI) system based on the rapid serial visual presentation (RSVP) paradigm. The dataset consists of 64-channel electroencephalogram (EEG) data from 64 healthy subjects (sub1,…, sub64) while they performed a target image detection task. For each subject, the data contained two groups (“A” and “B”). Each group contained two blocks, and each block included 40 trials that corresponded to 40 stimulus sequences. Each sequence contained 100 images presented at 10 Hz (10 images per second). The stimulus images were street-view images of two categories: target images with human and non-target images without human. Target images were presented randomly in the stimulus sequence with a probability of 1∼4%. During the stimulus presentation, subjects were asked to search for the target images and ignore the non-target images in a subjective manner. To keep all original information, the dataset was the raw continuous data without any processing. On one hand, the dataset can be used as a benchmark dataset to compare the algorithms for target identification in RSVP-based BCIs. On the other hand, the dataset can be used to design new system diagrams and evaluate their BCI performance without collecting any new data through offline simulation. Furthermore, the dataset also provides high-quality data for characterizing and modeling event-related potentials (ERPs) and steady-state visual evoked potentials (SSVEPs) in RSVP-based BCIs. The dataset is freely available from http://bci.med.tsinghua.edu.cn/download.html .

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Visual field inhomogeneous in brain–computer interfaces based on rapid serial visual presentation

Zhang¹,

Chen²,

Wang³

et al. 2022

J. Neural Eng.

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Objective. Visual attention is not homogeneous across the visual field, while how to mine the effective EEG characteristics that are sensitive to the inhomogeneous of visual attention and further explore applications such as the performance of brain-computer interface (BCI) are still distressing explorative scientists. Approach. Images were encoded into a rapid serial visual presentation (RSVP) paradigm, and were presented in three visuospatial patterns (central, left/right, upper/lower) at the stimulation frequencies of 10Hz, 15Hz and 20Hz. The comparisons among different visual fields were conducted in the dimensions of subjective behavioral and EEG characteristics. Furthermore, the effective features (e.g. SSVEP, N2pc and P300) that sensitive to visual-field asymmetry were also explored. Results. The visual fields had significant influences on the performance of RSVP target detection, in which the performance of central was better than that of peripheral visual field, the performance of horizontal meridian was better than that of vertical meridian, the performance of left visual field was better than that of right visual field, and the performance of upper visual field was better than that of lower visual field. Furthermore, stimuli of different visual fields had significant effects on the spatial distributions of EEG, in which N2pc and P300 showed left-right asymmetry in occipital and frontal regions, respectively. In addition, the evidences of SSVEP characteristics indicated that there was obvious overlap of visual fields on the horizontal meridian, but not on the vertical meridian. Significance. The conclusions of this study provide insights into the relationship between visual field inhomogeneous and EEG characteristics. In addition, this study has the potential to achieve precise positioning of the target's spatial orientation in RSVP-BCIs.

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P300 Brain Waves Instigated Semi Supervised Video Surveillance for Inclusive Security Systems

Cited by 3 publications

References 7 publications

ERP and Pupillometry Synchronization Analysis on Rapid Serial Visual Presentation of Words, Numbers, Pictures

ERP and Pupillometry Synchronization Analysis on Rapid Serial Visual Presentation of Words, Numbers, Pictures

A Benchmark Dataset for RSVP-Based Brain–Computer Interfaces

Visual field inhomogeneous in brain–computer interfaces based on rapid serial visual presentation

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