Discover the Why of the Brain

Electroencephalography (EEG) is a non-invasive neuroimaging technique that measures the electrical activity of the brain through electrodes placed on the scalp. EEG can be used for various research applications, including studying brain function and activity, identifying neurological disorders, and investigating the effects of drugs or other interventions on brain activity. EEG is particularly useful for studying brain activity in real-time and identifying the timing and location of brain activity associated with specific cognitive processes or behaviors. It can also be used in clinical settings to diagnose and monitor neurological disorders such as epilepsy, sleep disorders, and traumatic brain injuries. Additionally, EEG can be used to investigate the effects of various interventions, such as cognitive training or neurofeedback, on brain activity and function.


What Causes the "Stoke" in Surfing?

For surfers, catching the perfect wave can induce a state of pure ecstasy known as the “stoke”. But what’s happening in the brain during this ultimate ride? Wearable Sensing created a custom dry EEG system that measures brainwaves during surfing. They partnered with Red Bull to use this technology on professional surfers to uncover the neurophysiological aspects of surfing. The dry EEG system is worn on the head like a swimming cap, and it allows for the measurement of brain activity in real-time during surfing. By studying the brainwaves of surfers during their best rides, researchers hope to understand what goes on in the brain during moments of flow and peak performance, and ultimately unlock the secrets to achieving that elusive state of “stoke”.

Predicting hypoxic hypoxia using machine learning and wearable sensors

In this study, wearable sensors and machine learning-based algorithms were used to predict hypoxia in-flight. The group used Wearable Sensing’s dry-EEG technology to collect sensor data from 85 participants during a two-phase study. Participants wore aviation flight masks, which regulated their oxygen intake while performing cognitive tests and simulated flying tasks. EEG data was collected and analyzed using principal component analysis and machine learning algorithms, including Naïve Bayes, decision tree, random forest, and neural network algorithms, to classify the data as normal or hypoxic. The results showed high sensitivity and specificity, indicating potential for developing a real-time, in-flight hypoxia detection system.

An experimental protocol for exploration of stress in an immersive VR scenario with EEG

This paper proposes a protocol for assessing stress using wearable sensing technology, including Electroencephalography (EEG), Electrocardiography (ECG), and the Perceived Stress Scale, in combination with a Virtual Reality phobia induction setting. Wearable Sensing’s dry EEG technology is used to measure brain activity and investigate functional brain connectivity associated with stress. The proposed protocol can be expanded with the incorporation of machine learning algorithms for automatic stress level classification.



All of Wearable Sensing's Dry EEG systems can be utilized for Brain Computer Interfaces

NeuSenW High-Density EEG

All of Wearable Sensing's Wet EEG systems can be utilized for Brain Computer Interfaces



Machine learning algorithms for cognitive state classification, such as mental workload, engagement, and fatigue

3rd Party Compatible Software

List of compatible software, including Neurofeedback, BCI, EEG Analysis, SDK's, and more


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Li, Jian; Masullo, Massimiliano; Maffei, Luigi; Pascale, Aniello; Chau, Chi-kwan; Lin, Minqi

Improving informational-attentional masking of water sound on traffic noise by spatial variation settings: An in situ study with brain activity measurements Journal Article

In: Applied Acoustics, vol. 218, pp. 109904, 2024.

Abstract | Links | BibTeX

Kim, Sanghee; Ryu, Jihye; Lee, Yujeong; Park, Hyejin; Lee, Kweonhyoung

Methods for Selecting Design Alternatives through Integrated Analysis of Energy Performance of Buildings and the Physiological Responses of Occupants Journal Article

In: Buildings, vol. 14, no. 1, pp. 237, 2024.

Abstract | Links | BibTeX

Klee, Daniel; Memmott, Tab; Oken, Barry

The Effect of Jittered Stimulus Onset Interval on Electrophysiological Markers of Attention in a Brain–Computer Interface Rapid Serial Visual Presentation Paradigm Journal Article

In: Signals, vol. 5, no. 1, pp. 18–39, 2024.

Abstract | Links | BibTeX


Park, Jaeyoung; Wang, Soyoung; Lee, Seungji; Seo, Seungbeom; Lee, Nayoung; Kim, Seongcheol

Viewer Emotional Response to Webtoon-Based Drama: An EEG Analysis Journal Article

In: International Journal of Human–Computer Interaction, pp. 1–15, 2023.

Abstract | Links | BibTeX

Liu, F.; Yang, P.; Shu, Y.; Liu, N.; Sheng, J.; Luo, J.; Wang, X.; Liu, Y.

Emotion Recognition from Few-Channel EEG Signals by Integrating Deep Feature Aggregation and Transfer Learning Journal Article

In: IEEE Transactions on Affective Computing, no. 01, pp. 1-17, 2023, ISSN: 1949-3045.

Abstract | Links | BibTeX

Chan, Melody MY; Choi, Coco XT; Tsoi, Tom CW; Shea, Caroline KS; Yiu, Klaire WK; Han, Yvonne MY

Effects of multisession cathodal transcranial direct current stimulation with cognitive training on sociocognitive functioning and brain dynamics in ASD: A double-blind, sham-controlled, randomized EEG study Journal Article

In: Brain Stimulation, vol. 16, iss. 8, pp. P1604-1616, 2023.

Abstract | Links | BibTeX

Kamti, Mukesh Kumar; Iqbal, Rauf; Kakoti, Pallabjyoti

Eeg-based mental states assessment of three-wheeler drivers in different environments and traffic conditions Journal Article

In: Transportation Research Part F: Traffic Psychology and Behaviour, vol. 99, pp. 98–112, 2023.

Abstract | Links | BibTeX

Mizrahi, Dor; Laufer, Ilan; Zuckerman, Inon

Modulation of Beta Power as a Function of Attachment Style and Feedback Valence Conference

International Conference on Brain Informatics, Springer 2023.

Abstract | Links | BibTeX

Georgiadis, Kostas; Kalaganis, Fotis P; Oikonomou, Vangelis P; Nikolopoulos, Spiros; Laskaris, Nikos A; Kompatsiaris, Ioannis

Harneshing the Potential of EEG in Neuromarketing with Deep Learning and Riemannian Geometry Conference

International Conference on Brain Informatics, Springer 2023.

Abstract | Links | BibTeX

Chiossi, Francesco; Turgut, Yagiz; Welsch, Robin; Mayer, Sven

Adapting Visual Complexity Based on Electrodermal Activity Improves Working Memory Performance in Virtual Reality Journal Article

In: Proc. ACM Hum.-Comput. Interact, vol. 7, 2023.

Abstract | Links | BibTeX

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