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Detection of P300 and Its Applications
Published in Narayan Panigrahi, Saraju P. Mohanty, Brain Computer Interface, 2022
Narayan Panigrahi, Saraju P. Mohanty
The event-related potential (ERP) was first reported by Sutton (Klobassa et al 2009). An ERP is an electro-physiological response or electro-cortical potentials triggered by a stimulation and firing of neurons. A specific psychological event or a sensor can be employed to generate the stimulation. In general, visual, auditory, and tactile are three major sources of ERP stimulation. For instance, an ERP can be elicited by a surprise appearance of a character on a visual screen, or a “novel” tone presented over earphones, or by suddenly pressing a button by the subject, including myriad other events. The presented stimulus generates a detectable but time-delayed electrical wave in an EEG. An EEG is recorded starting from the time of presenting the stimulus to the time when the EEG settles down. Depending on the necessity, a simple detection method such as ensemble averaging or advanced processes such as linear discriminate analysis or support vector machine algorithms are applied on an EEG to measure the ERP. This chapter discusses the application of an ERP in the brain computer interface (BCI), where a P300 wave from the EEG is of particular interest. An ERP is time-locked to an event and appears as a series of positive and negative voltage fluctuation in the EEG, which are referred to as P300 components.
EEG-Based BCI Systems for Neurorehabilitation Applications
Published in Mridu Sahu, G. R. Sinha, Brain and Behavior Computing, 2021
Muhammad Ahmed Khan, Rig Das, John Paulin Hansen, Sadasivan Puthusserypady
The P300 is an event related potential (ERP) that appears as a positive peak (ranging from 5 to 10 microvolts) around 300 ms after occurrence of a rare or surprising stimulus, which can be visual, tactile or auditory in nature. These activities are strong in the midline areas of the brain and therefore, EEG electrodes are placed over the Fz, Cz and Pz locations to record these signals. The P300 peak is elicited during the “oddball paradigm,” where the series of stimuli is classified into two classes: (i) frequently occurring event and (ii) rare/surprising event. Thus, when the brain encounters a surprising event, it will generate P300 ERP after around 300 ms. It has been found that the P300 is stronger if a person performs some tasks during an experiment. Therefore, it is advised to count the number of rare stimuli during trials to achieve a higher and prominent peak of P300 signals.
Review of the Human Brain and EEG Signals
Published in Teodiano Freire Bastos-Filho, Introduction to Non-Invasive EEG-Based Brain–Computer Interfaces for Assistive Technologies, 2020
Alessandro Botti Benevides, Alan Silva da Paz Floriano, Mario Sarcinelli-Filho, Teodiano Freire Bastos-Filho
The EEG signals are composed of basic components of spontaneous potentials, which may be present throughout the range of frequencies of the EEG signal and are not produced by sensory stimulation. ERP is the change of the EEG potential in response to a particular event. ERP has much lower amplitude than the spontaneous activity, so that it cannot be recognized in the raw EEG. Therefore, average techniques are commonly employed for detecting the ERP. In the average technique, the ERP is considered to occur with an approximately constant delay in relation to the event, and the spontaneous activity is modeled as an additive random noise (Figure 1.29a) [37]. The EEG recordings obtained by repeating the same experiment or trial, under the same conditions, are called epochs, and as the number of epochs, N, used in the calculation of the average increases, the time-locked activity increases and the spontaneous activity decreases, and thus, the ERP can be observed.
A Functional BCI Model by the P2731 working group: Physiology
Published in Brain-Computer Interfaces, 2021
Ali Hossaini, Davide Valeriani, Chang S. Nam, Raffaele Ferrante, Mufti Mahmud
Event-related potentials (ERP) are voltage fluctuations generated when regions of the brain respond to stimuli, prepare for a movement or perform mental operations such as imagining movement. When sensed by EEG, ERPs are detected as consistent changes in micro-voltage levels on the scalp, but these changes are usually masked by higher amplitude background noise. To compensate, ‘time locked signal averaging is necessary to extract ERPs from the raw data’ [85]. This method requires researchers to segment a recording into a series of ‘epochs’ that begin with the stimulus that causes the ERP [86]. ERPs are time-locked to stimuli, so an epoch should be long enough to include the stimulus, a precursor period of background data, and sufficient time to capture the ERP under scrutiny. Averaging a set of epochs allows the time-locked signal to emerge by decreasing the relative amplitude of noise [87]. ERPs have been identified for different sense modalities, but localizing their neural generators has proven difficult because of the head’s conductive properties [88,89]. ERP names are created by combining their polarity – P for positive, N for negative – with their peak latency, namely the time between a stimulus and their maximum amplitude measured in milliseconds (e.g. N250, P300) or the order in which they appear (e.g. P1, N2, P2). Note that both the onset and the maximum amplitude of an ERP are in reality variable, and it is the stereotypical waveform combined with temporal proximity to an hypothetical post-stimulus peak that enables researchers to categorize it [90–93].
How User’s First Impression Forms on Mobile user Interface?: An ERPs Study
Published in International Journal of Human–Computer Interaction, 2020
Fu Guo, Xue-Shuang Wang, Hao Shao, Xiao-Rong Wang, Wei-Lin Liu
Event-related potentials (ERPs), which can measure cerebral activities according to brain signals recording, are a high temporal resolution and noninvasive technology (Picton et al., 2000). ERPs have already used to explore the process of esthetic and usability evaluation with an explicit task (Muñoz & Martín-Loeches, 2015; Righi, Orlando, & Marzi, 2014). Other studies show that humans can make an implicit esthetic assessment to the stimuli like logos, pictures, geometric graphs, architectures, pendant and Chinese characters without any explicit evaluation or decision-making guidance (Bargh & Ferguson, 2000; Handy, Smilek, Geiger, Liu, & Schooler, 2010; Höfel & Jacobsen, 2007; Li, Qin, Zhang, Wu, & Zhou, 2015; Ma, Hu, & Wang, 2015; Wang, Huang, Ma, & Li, 2012). Moreover, ERPs have proved to be a useful method to explore the underlying neural mechanism of users’ first impression formation from different dimensions. Kim, Koo, Yoon, and Cho (2016) conducted a pilot study to investigate the neural mechanism of users’ first impression formation with an explicit evaluation of usability and esthetics on the websites. In addition, the website logos’ impression was also explored by ERPs from the perspective of usefulness and enjoyment evaluation, during the experiment subjects were asked to evaluate these logos on only one dimension at a time, and the results showed that enjoyment that could be automatically evaluated was a critical component in the impression formation process (Huang, Kuo, Luu, Tucker, & Hsieh, 2015). To sum up, ERPs might be an effective tool to measure the process of users’ first impression formation.
Authentication framework for security application developed using a pictorial P300 speller
Published in Brain-Computer Interfaces, 2020
Nikhil Rathi, Rajesh Singla, Sheela Tiwari
Brain-Computer Interfaces are designated according to the type of brain activity used for monitoring. Previously, researchers have studied, several EEG-based BCIs including, P300 potential [23], steady-state visual evoked potential (SSVEP) [24], event-related de-synchronization (ERD), and slow cortical potential [25]. Evoked potentials are electrical signals generated by the subject when he/she receives outside stimuli [26]. The outcomes obtained from evoked potentials are being averaged with a presentation of repeated stimuli as the amplitude of potentials measured is small. The well-known evoked signals are Steady-State Visual Evoked Potentials (SSVEP) and P300 potentials and commonly used stimuli are visual (e.g., a flash of light), auditory (sound related), and sensory [27]. Development of BCI relies upon the selection of signals, data acquisition methods, and feature extraction methods, development of training strategies, protocols, and choice of application and user group. In this paper, P300 is used as the control signal for the development of BCI based authentication system. The P300 ERP is a positive deflection in the EEG signal that appears almost 300 ms after, the subject is exposed to the infrequently occurring or surprising tasks. This signal is usually generated through an ‘odd-ball’ paradigm where the user is asked to attend a random sequence of stimuli in which one is much less frequent than the other [28]. At whatever point relevant stimuli appear on the screen, it triggers the P300 signals of the user. The main advantage of using P300 is that it doesn’t require training of the subject, but it requires repetitive stimuli for better outcomes [29].