Wireless EEG: A survey of systems and studies

Niso, Guiomar; Romero, Elena de Luis; Moreau, Jeremy T; Araújo, Álvaro; Krol, Laurens R.

doi:10.1016/j.neuroimage.2022.119774

Cited by 100 publications

(57 citation statements)

References 149 publications

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“…Zhang et al used the wireless, inexpensive, commercially available Emotiv EPOC, whereas we used the wired, clinical-grade g.tec BCI system. The two systems differ in the number, placement, and types of EEG electrodes, as well as ampli cation, impedance, sampling rate and resolution, size and weight (43). Moreover, the signal processing and classi cation methods differ as well, with Emotiv using Probabilistic Neural Network and Radial Basis Function to classify ERDs, while the g.tec mindBEAGLE software uses CSP and LDA (19).…”

Section: Discussionmentioning

confidence: 99%

Brain-Computer Interfaces for Children: A Comparative Study of Five Common EEG-based Paradigms

Kelly

Zewdie

Carlson

et al. 2023

Preprint

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Background Quadriplegic cerebral palsy (QCP), the most severe form of cerebral palsy (CP), affects millions of individuals worldwide. Children with QCP often have intact cognitive function but face challenges in communication or interaction with their environments, which may result in a condition similar to "locked-in syndrome." Brain-computer interfaces (BCIs) hold potential to help, but pediatric BCI research has been limited. This study aimed to establish baseline performance of common BCI paradigms in typically developing children to support applications in children with disabilities.Methods Performance on five BCI paradigms, including visual (P300), auditory (AEP), and vibro-tactile (VTP2 and VTP3) event-related potentials, and sensorimotor rhythm (SMR) modulation using motor imagery, was evaluated in thirty school-age children using tasks with predefined goals. Two commercially available EEG-based BCI systems, Mindbeagle® and intendiX®, were used. The primary outcome was online classification accuracy. Potential factors affecting performance, including age, sex, motivation, tolerability, and fatigue, were also explored.Results We found that most children were able to demonstrate competency on multiple BCI paradigms with favorable tolerability and no serious adverse events. Mean accuracy across all paradigms was 77.03%, with 73% achieving BCI competency. Performance on P300-based paradigms was better than the SMR paradigm, with the highest performance observed in the VTP2 paradigm (89.48%), and the lowest in the SMR paradigm (55.68%). Significant differences in accuracy and fatigue were observed across the paradigms, with the visual P300 spelling paradigm showing the highest motivation and lowest fatigue. Age was correlated only with AEP BCI performance, while no other factors appeared to influence performance across paradigms.Conclusion We conclude that evoked potential BCI paradigms are generally effective in children as young as 6 years of age in a laboratory setting for potentially meaningful tasks, such as communication, recreation, and computer operation. The research contributes to the limited knowledge on non-invasive BCI performance in children and offers insights into factors affecting performance. More research is needed to understand how these BCI paradigms can be optimized for children and implemented in real-world environments and as assistive technology for youth with disabilities.

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Section: Discussionmentioning

confidence: 99%

Brain-Computer Interfaces for Children: A Comparative Study of Five Common EEG-based Paradigms

Kelly

Zewdie

Carlson

et al. 2023

Preprint

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“…This technique is especially useful for studying social cognition in more ecologically valid settings (Hari & Kujala, 2009; Konvalinka & Roepstorff, 2012). While hyperscanning can be conducted with various types of physiological measurements, such as brain and heart activity, EEG has been the most commonly used method due to its high temporal resolution and portability (Niso et al, 2023).…”

Section: Mobile Brain/body Imaging (Mobi): a Technico-methodological ...mentioning

confidence: 99%

The Future of Psychotherapy Research and Neuroscience: Introducing the 4E/MoBI Approach to the Study of Patient–Therapist Interaction

Costa-Cordella,

Grasso-Cladera,

Parada

2024

Review of General Psychology

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The integration of neuroscience and psychotherapy research has long been a topic of interest in the field of mental health. A significant challenge in psychotherapy research is understanding the dyadic interaction between patient and therapist. This interaction is complex, emerging from a myriad of multi-level factors such as gestures, verbal communication, mentalization, and environmental influences. This article aims to present a roadmap for the future integration of neuroscience and psychotherapy research, addressing the complexities of human interaction. We introduce the 4E/MoBI approach, a framework that combines theoretical and methodological tools to study the dynamics of the brain, body, and environment in real-world settings. This approach emphasizes the use of physiological systems (e.g., heart and brain), behavioral interactions (e.g., conversations and eye-tracking), and environmental video recordings. Additionally, the scalable experimental design (SED) heuristic is discussed as a method to blend controlled experiments with real-world scenarios, allowing for the parametric testing of neurobehavioral markers. As a practical demonstration of the SED heuristic within the 4E/MoBI framework, a concrete experimental example using the N170 event-related potential (ERP) component is presented. While the N170 ERP component is not posited as the foundational marker in the field, it serves to illustrate the application of hypothesis-driven designs and analyses. The 4E/MoBI approach offers a promising avenue for the integration of neuroscience and psychotherapy research. By addressing existing gaps, such as the physiology and phenomenology of expertise in psychotherapy, this framework can foster a virtuous relationship between the two disciplines, paving the way for more comprehensive and nuanced understandings of therapeutic interactions.

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“…It is feasible to integrate other sensors such as PPG (to measure heart rate and heart rate variability), a pulse oximeter (respiration rate and oxygen saturation), electrodermal activity (EDA) sensor (to measure skin conductance), ambient light, ambient noise, and accelerometer sensors to a headband to have a more complete system for sleep measurement. While various EEG wearables are available for consumers (see Niso et al, 2023), Table 1 reviews the ones tailored for citizen neuroscience projects: Our selection encompasses EEG wearables with an appropriate design for sleep studies (e.g., reasonable battery life and amplifier location), which can be utilized independently by the citizen neuroscientists with minimal help and assistance required from researchers. As an example, the ZMax headband employs two frontal EEG channels, F7–AFz and F8–AFz, that are attached to the forehead with a wet hydrogel patch.…”

Section: From Citizen Science To Citizen Neurosciencementioning

confidence: 99%

Citizen neuroscience: Wearable technology and open software to study the human brain in its natural habitat

Jafarzadeh Esfahani,

Sikder,

ter Horst

et al. 2024

Eur J of Neuroscience

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Citizen science allows the public to participate in various stages of scientific research, including study design, data acquisition, and data analysis. Citizen science has a long history in several fields of the natural sciences, and with recent developments in wearable technology, neuroscience has also become more accessible to citizen scientists. This development was largely driven by the influx of minimal sensing systems in the consumer market, allowing more do‐it‐yourself (DIY) and quantified‐self (QS) investigations of the human brain. While most subfields of neuroscience require sophisticated monitoring devices and laboratories, the study of sleep characteristics can be performed at home with relevant noninvasive consumer devices. The strong influence of sleep quality on waking life and the accessibility of devices to measure sleep are two primary reasons citizen scientists have widely embraced sleep research. Their involvement has evolved from solely contributing to data collection to engaging in more collaborative or autonomous approaches, such as instigating ideas, formulating research inquiries, designing research protocols and methodology, acting upon their findings, and disseminating results. In this article, we introduce the emerging field of citizen neuroscience, illustrating examples of such projects in sleep research. We then provide overviews of the wearable technologies for tracking human neurophysiology and various open‐source software used to analyse them. Finally, we discuss the opportunities and challenges in citizen neuroscience projects and suggest how to improve the study of the human brain outside the laboratory.

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Wireless EEG: A survey of systems and studies

Cited by 100 publications

References 149 publications

Brain-Computer Interfaces for Children: A Comparative Study of Five Common EEG-based Paradigms

Brain-Computer Interfaces for Children: A Comparative Study of Five Common EEG-based Paradigms

The Future of Psychotherapy Research and Neuroscience: Introducing the 4E/MoBI Approach to the Study of Patient–Therapist Interaction

Citizen neuroscience: Wearable technology and open software to study the human brain in its natural habitat

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