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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
Unlike TVEP, SSVEP is the elicited response in the brain (mainly in visual cortex) by light stimuli flickering at a constant frequency. These potentials manifest as an oscillatory component in the EEG signal with the same frequency (and/or its harmonics) of the visual stimulation [56]. SSVEP can normally be evoked up to 90 Hz [57], and three stimuli bands can be identified: low (<12 Hz), medium (12–30 Hz), and high frequencies (>30 Hz) [56,58]. Whereas SSVEPs evoked by low- and medium-frequency stimuli bands are easier to detect (due to their higher energy), stimuli in these bands can produce epileptic seizures, which occur typically from 15 to 25 Hz [64], false positives due to α rhythm (8–13 Hz) [56,65], migraine headaches [66], and visual fatigue [66]. Thus, a suitable stimuli band is the high-frequency band; however, its evoked SSVEP is harder to detect, and literature has reported that approximately only 65% of people are able to operate a BCI based on high-frequency SSVEP [7], meaning that about 35% of people cannot achieve effective control of this kind of BCI system.
Future Soldier-System Design Concepts: Brain–Computer Interaction Technologies
Published in Pamela Savage-Knepshield, John Martin, John Lockett, Laurel Allender, Designing Soldier Systems, 2018
Brent Lance, Jorge Capo, Kaleb McDowell
Communication-based BCIs included applications for dialing telephones (for example, calling 911) and spelling words. In fact, several research groups (Cheng et al. 2002, Wang and Jung 2011) have developed phone dialing systems based on a steady-state visually evoked potential (SSVEP). The SSVEP is a brain signal that is induced by a steadily flashing visual stimulus that is composed of frequency components appearing at the harmonic frequencies of the flashing stimulus, and that is detectable via EEG over the occipital lobe. By displaying the buttons on a phone as a set of visual stimuli on the screen and blinking them at different frequencies, the SSVEP can be used to determine which of the stimuli is being attended to, providing the system with enough information to dial a phone for the user. It is foreseeable that this same type of approach could be applied to operating a system interface or for controls such as sending email.
Affective Natural Interaction Using EEG: Technologies, Applications and Future Directions
Published in Spyrou Evaggelos, Iakovidis Dimitris, Mylonas Phivos, Semantic Multimedia Analysis and Processing, 2017
Charline Hondrou, George Caridakis, Kostas Karpouzis, Stefanos Kollias
Furthermore, there are two important characteristics measured in EEG studies. The first one is the Event-Related Potential (ERP)[164]. An ERP is any measured brain response that is a direct result of a thought or perception. More formally, it is any stereotyped electrophysiological response to an internal or external stimulus. Increased interest has been shown in P300 which is one of the components of an ERP elicited by task-relevant stimuli. It is considered to be an endogenous potential, as its occurrence links to a person’s reaction to the stimulus. It is a positive deflection in voltage (2-5 V) with a latency of about 300-600 ms from the stimulus onset. The second one is the Steady-State Visual Evoked Potential (SSVEP). The SSVEP is a periodic response elicited in the brain by visual spatial attention on a flickering stimulus at frequency of 6 Hz and above. SSVEPs have the same fundamental frequency as the stimulating frequency, but they also include higher and/or subharmonic frequencies in some situations. SSVEPs are usually recorded from the occipital region of the scalp. Compared to other types of EEG features, SSVEPs have a better Signal-to-Noise-Ratio (SNR) [794].
A low-power, low-offset, and power-scalable comparator suitable for low-frequency applications
Published in International Journal of Electronics, 2023
Riyanka Banerjee, M. Santosh, Jai Gopal Pandey
Today, wearable biomedical devices track the medical conditions of patients and provide numerical data for therapeutic diagnosis. According to the applications, devices require biosignals to monitor heart rate and identify the QRS peak in ECG signals, while temperature or pressure sensors may require DC information, as mentioned by Lie et al. (2013). The demand for cardiovascular device monitoring systems is increasing, which has led to the use of low-power non-invasive blood pressure measurement devices with excellent precision. As systolic/diastolic pulses vary in all situations, a tunable hysteresis comparator was proposed in Qian and Teo (2009). In Na et al. (2022), a low-power portable collaborative sensing system based on the TMW-CCA algorithm has been introduced to establish brain-computer interface (BCI) technology Zhang et al. (2018). It helps in medical diagnosis and scientific research by using multiple channels and wet electrodes to obtain high-quality signals. In this system, steady-state visual evoked potential (SSVEP) methods are used to collect signals from the brain. To enable applications such as intelligent wheelchair control Na et al. (2021), robotic arm control Chen et al. (2018), and computer games Wong et al. (2015), the user receives a periodic visual stimulus. Electrodes immediately capture the SSVEP for further processing.
Towards enhanced information transfer rate: a comparative study based on classification techniques
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2020
SSVEP is defined as the presence of steady-state harmonics in the EEG signal recorded over the visual cortex after the subject is subjected to flickering objects of predefined frequencies (Regan 1989). The visual cortex is located over the occipital region, located at the back of the human scalp. This region is identified by locating 10% of the total distance value between Nasion and Inion with reference at Inion. The SSVEP appears in the form of 1st, 2nd and 3rd harmonics of the fundamental flickering frequencies within the EEG with respect to the flickering stimulus (Müller-Putz et al. 2005; Combaz and Van Hulle 2015). In a stereotypical SSVEP paradigm based BCI, the subjects fixed their gaze on one of the multiple decision targets presented on a computer screen, such that each target has a unique flickering frequency. When the subject is focusing on one of the targets, the SSVEP response over that object’s frequency is most significant. Thus the determination of the decision target under consideration can be done by finding the 1st harmonic frequency which has maximum power. Yet another way of eliciting SSVEP is the checker-board paradigm which produces a stronger SSVEP activity (Lalor et al. 2005; Trejo et al. 2006; Martinez et al. 2007). Like P300, SSVEP requires little or no training but it might be annoying for some subjects and might cause seizures in some subjects. However, the numbers of decisions in an SSVEP paradigm which are uniquely represented by different frequencies are limited due to the bandwidth of the frequencies that can elicit SSVEP in a subject. Hence other techniques like phase coding or resorting to hybrid paradigms based on SSVEP are considered for developing and improvement of ADs.
Novel frequency-based approach for detection of steady-state visual evoked potentials for realization of practical brain computer interfaces
Published in Brain-Computer Interfaces, 2022
Mehrnoosh Neghabi, Hamid Reza Marateb, Amin Mahnam
SSVEP is a natural response of the brain to visual stimulation at a particular frequency, which includes the same stimulus frequency and some of its harmonics and subharmonics. SSVEP-based BCI systems recognize the desire of the user when they look at one of several stimuli which flashes with a distinct frequency, by detecting the corresponding frequency (and its harmonics) in the EEG [14].