Wireless Sensors for Brain Activity—A Survey

Abstract

Over the last decade, the area of electroencephalography (EEG) witnessed a progressive move from high-end large measurement devices, relying on accurate construction and providing high sensitivity, to miniature hardware, more specifically wireless wearable EEG devices. While accurate, traditional EEG systems need a complex structure and long periods of application time, unwittingly causing discomfort and distress on the users. Given their size and price, aside from their lower sensitivity and narrower spectrum band(s), wearable EEG devices may be used regularly by individuals for continuous collection of user data from non-medical environments. This allows their usage for diverse, nontraditional, non-medical applications, including cognition, BCI, education, and gaming. Given the reduced need for standardization or accuracy, the area remains a rather incipient one, mostly driven by the emergence of new devices that represent the critical link of the innovation chain. In this context, the aim of this study is to provide a holistic assessment of the consumer-grade EEG devices for cognition, BCI, education, and gaming, based on the existing products, the success of their underlying technologies, as benchmarked by the undertaken studies, and their integration with current applications across the four areas. Beyond establishing a reference point, this review also provides the critical and necessary systematic guidance for non-medical EEG research and development efforts at the start of their investigation.

Information Security Risk Assessment

“…Another approach that can simplify and speed up the process of risk assessment is using ontology-based modeling [43][44][45][46][47]. This approach uses semantic elements defined during risk analysis and provides an easy way of duplicating the data once the object or process has been described.…”

Brain Waves Signal Modeling for Object Classification Using Random Forest Method

“…Today, EEG is utilized in many technical areas such as health, computer games, natural language processing, and education (Tajdini et al, 2020). Thus, several recent works in this area are explained in detail.…”

Promise for Personalized Diagnosis? Assessing the Precision of Wireless Consumer-Grade Electroencephalography across Mental States

“…In laboratory research settings, EEG has been used extensively for cognitive neuroscience research, and in medical settings, it is considered the most robust method of diagnosing seizures and epilepsy [1,2]. In the last decade, however, there has been significant growth in the interest and application of using EEG outside of the laboratory and medical settings [3]. EEG has become the most widely used neuroimaging technique for brain-computer interfaces (BCI).…”

“…Sci. 2022, 12, 6430 2 of 19 One challenge in developing outside lab EEG applications, however, is that traditional research-and medical-grade EEG devices are costly (~US$50,000+), typically stationary, fully wired, and time consuming to properly set up, in that electrode application may typically take 30-60 min depending on the type and number of wet (gel-based) sensors [3]. For example, one research-grade EEG device is the Brainvision EEG headset.…”

“…For instance, all of these factors make using traditional EEG challenging in more ecological settings (i.e., educational and training health settings). In response to these challenges, over the last decade or so, wearable, portable, cost-efficient EEG headsets have been developed [3]. To date, the most recent and exhaustive review of consumer grade EEG devices impressively covering applications in cognition, brain computer interfaces, education research, and game development has been published by Sawangjai et al [20].…”