EEG in Neurotech: Advancements, and Applications in the Private Sector

Introduction

Electroencephalography (EEG) has emerged as a powerful tool in the field of neurotechnology, with significant advancements in recent years making it more accessible to the private sector. By measuring electrical activity in the brain, EEG holds great potential for a wide range of applications. This article explores the current state of EEG technology in the private sector, highlighting its relevance and potential applications. We will delve into the challenges of balancing ease of use and data quality, the importance of aesthetics for consumer adoption, the trends in equipment cost, and the role of user experience in EEG-based applications. By addressing these factors, we aim to provide an in-depth overview that inspires the development of innovative neurotech products for the market.

Balancing Ease of Use and Data Quality

Achieving a balance between ease of use and data quality is a critical consideration for companies utilizing EEG technology in the private sector. EEG data collection methods vary in complexity, with high-quality data often requiring more electrodes and a wet system that uses conductive gel

example of eeg gel

to enhance electrode scalp contact. However, such setups are not practical for consumer-grade products. In response, many consumer-focused EEG devices employ a dry system with fewer electrodes. While this compromises data resolution to some extent, it is often sufficient for specific applications, like meditation apps or sleep monitoring. The challenge lies in designing consumer-friendly headwear that ensures ease of use, durability, and adequate data collection for the desired application.

Consumer-grade EEG headsets typically aim for a plug-and-play experience, with minimal setup requirements. These headsets utilize dry electrodes that do not require gel or other conductive substances, simplifying the process for users. However, ensuring a reliable connection between each electrode and the scalp remains a challenge. Companies are exploring innovative approaches such as improved electrode materials, innovative headband designs, and optimized signal processing algorithms to enhance the quality of data captured while maintaining user convenience.

Aesthetics for Consumer Adoption

Aesthetics play a significant role in the consumer adoption of EEG products. Currently, EEG headsets often lack style and can appear bulky or unattractive. To encourage widespread consumer adoption, the integration of EEG sensors into everyday accessories like earphones, over-ear headphones, glasses, or hats is a potential solution. These accessories can incorporate electrodes in specific locations, and additional sensors for recording other biological or

Example of over-ear EEG headphones

environmental data may further enhance EEG data quality. However, as consumer-grade products cannot afford the time-consuming setup process required by medical or research equipment, ensuring a reliable connection between each electrode and the scalp remains a challenge. Striking a balance between aesthetics and functionality is crucial for driving consumer acceptance of EEG technology.

By combining cutting-edge technology with attractive designs, these EEG wearables have the potential to become fashion-forward accessories that consumers willingly incorporate into their daily routines.

Trends in Equipment Cost

Historically, the cost of EEG systems has been prohibitive for the average consumer, with headsets often costing over £100, limiting their adoption in the private sector. However, there is a positive trend towards cost reduction in EEG technology. Some manufacturers now offer EEG processing circuit boards for under £50, and basic consumer-targeted headsets can be found for £200. If this cost reduction trend continues, EEG headsets may reach a point of value justification for consumers by the end of this decade, enabling broader adoption and driving innovation in EEG-based applications.

The reduction in equipment costs is driven by advancements in technology, streamlined manufacturing processes, and economies of scale as demand increases. Open-source EEG projects and developer-friendly platforms have also contributed to cost reduction and sparked innovation by enabling a wider community to experiment, collaborate, and develop new applications for EEG technology. As the private sector invests in EEG research and development, these trends are expected to continue, further democratizing access to EEG technology.

EEG Data Applications in the Private Sector

EEG data collected in the private sector can be broadly categorized into two types: Event-Related Potentials (ERPs) and ongoing neural rhythms. ERPs are time-locked to specific events or stimuli and capture the brain's response to those stimuli. They provide insights into cognitive processes, attention, memory, and emotional responses. ERPs find applications in user research, market research, and neurofeedback-based training programs.

A waveform showing several ERP components, including the N100 (labelled N1) and P300 (labelled P3). The ERP is plotted with negative voltages upward, a common, but not universal, practice in ERP research

One example of using ERPs in the private sector is in user research for product development. Companies can utilize EEG technology to measure and analyse ERPs to gain insights into user preferences, attention, and emotional responses during the testing of new products or user interfaces. By presenting users with specific stimuli or tasks and measuring their brain responses, companies can understand how users engage with their products at a subconscious level. This information can help in optimizing product design, user experience, and marketing strategies to better meet user needs and preferences.

On the other hand, ongoing neural rhythms refer to the continuous patterns of brain activity that occur without specific external triggers. These rhythms, such as alpha, beta, theta, and delta waves, can provide information about an individual's cognitive state, relaxation levels, focus, and sleep stages. Ongoing neural rhythms have applications in meditation and mindfulness training, sleep tracking, stress management, and cognitive enhancement.

EEG signal has five frequency bands; delta (0.5-4Hz), theta (4-8 Hz), alpha (8-14 Hz), beta (14-30Hz) and gamma (above 30Hz)

An example of leveraging ongoing neural rhythms in the private sector is in the development of stress management applications. EEG technology can capture brainwave patterns associated with stress levels, such as increased beta wave activity. Companies can utilize this data to develop wearable devices or smartphone applications that provide real-time feedback on an individual's stress levels. By analysing the ongoing neural rhythms and providing personalized recommendations, such as guided breathing exercises, meditation techniques, or suggestions for stress reduction activities, these applications can assist individuals in managing and reducing their stress levels in real-time. This use case can be particularly beneficial in corporate wellness programs or mental health applications, helping individuals achieve a better work-life balance and overall well-being.

The Role of User Experience in EEG Applications

User experience (UX) plays a pivotal role in the success of EEG-based applications. The challenge lies in translating complex brainwave data into meaningful and actionable insights without overwhelming the user. Effective visualization techniques, intuitive interfaces, and engaging feedback are crucial for conveying information derived from EEG signals in a user-friendly manner.

Companies in the private sector must invest in designing user-friendly applications that provide valuable feedback and actionable recommendations. User engagement is essential for ensuring long-term adoption of EEG-based technologies. By leveraging data analytics, machine learning, and artificial intelligence, EEG applications can offer personalized insights and recommendations to users, empowering them to make informed decisions regarding their mental well-being, cognitive performance, or sleep quality.

Moreover, the integration of EEG technology with existing consumer devices, such as smartphones, smartwatches, or virtual reality headsets, can enhance user experience and accessibility. This integration allows users to seamlessly interact with EEG applications and incorporate them into their daily routines, further increasing engagement and the potential for impactful outcomes.

Conclusion

EEG technology is rapidly advancing in the private sector, driven by the increasing demand for consumer-friendly neurotech products. As companies strive to strike a balance between ease of use and data quality, improve aesthetics, and reduce equipment costs, EEG is poised to find its place in various applications beyond traditional research and healthcare domains. By focusing on user experience, visualizations, and meaningful insights, private sector innovators can unlock the full potential of EEG technology and offer compelling products that enrich users' lives. With further advancements on the horizon, EEG-based neurotech is set to revolutionize industries and empower individuals to better understand and interact with their own cognitive processes. By embracing these opportunities, the private sector can drive the next wave of EEG innovation, creating products that have a positive impact on society as a whole.

The Hidden Depths of Perception: Unveiling Implicit and Explicit Measures in Social Interactions

Imagine the feeling of complete control as you navigate through a task, making decisions and witnessing the outcomes of your actions. This sense of agency, or the subjective experience of being in control of one's actions and their consequences, is a fundamental aspect of human perception and behaviour. But what happens when we engage in joint actions, collaborating with others to achieve a shared goal? Does our sense of agency change in the context of these social interactions? These questions led us to conduct a scientific study aiming to explore the relationship between self-agency and joint-agency.

To delve into this intriguing topic, we recruited 40 participants and had them complete two distinct tasks. The first task, known as the intentional binding task, sought to measure participants' implicit sense of control over their actions. In this task, participants were asked to estimate the interval between their voluntary action (such as pressing a button) and the subsequent outcome (such as a visual or auditory feedback). This measure of intentional binding captures the phenomenon where individuals perceive the time between their actions and their outcomes to be compressed, indicating a heightened sense of control (see image above).

The second task, the joint haptic task, aimed to assess participants' sense of control in a joint action scenario. Here, participants engaged in a task together with with another person, or by themselves. The task involved working together in order to move a pole to either side of a box and required thinking counter-intuitively in order to complete effectively. After each trial they were asked to rate their perceived sense of control on a 7-point Likert scale. This provided insights into the experience of joint agency and how it compared to their experience of self-agency.

The results of our study were intriguing and shed light on the nuances of self-agency and joint-agency. Firstly, participants exhibited the intentional binding effect, perceiving the interval between their actions and outcomes to be significantly shorter in the volitional condition compared to the non-volitional condition. This finding replicated previous research, reaffirming the reliability of the intentional binding phenomenon.

Intriguingly, participants rated their sense of control to be significantly higher when acting independently compared to when acting with another person. This divergence in perceived control suggests that the experience of joint agency may differ from that of self-agency, and interestingly, the two may be inversely related. In other words, when engaged in joint actions, individuals may experience a diminished sense of personal control.

Furthermore, we found a noteworthy negative correlation between intentional binding and control ratings. This indicates that individuals who exhibited higher levels of intentional binding, reflecting a stronger implicit sense of self-agency, tended to report lower levels of perceived control when acting with another person. These findings suggest that implicit measures, such as intentional binding, may provide a more accurate reflection of the experience of agency in joint action, compared to explicit measures.

The findings from our study offer valuable insights into the complex dynamics of self-agency and joint-agency within a social context. They underscore the notion that the experience of agency in joint action may deviate from the experience of self-agency, and that these two experiences may be inversely related. The study also emphasizes the importance of employing both implicit and explicit measures to comprehensively understand the phenomenology of joint action. Implicit measures, such as intentional binding, can reveal subtle aspects of agency perception that explicit measures may not capture fully.

It is important to acknowledge that our study had a relatively small sample size, which may limit the generalizability of the findings. Future research endeavours should aim to replicate these findings using larger samples and explore the relationship between self-agency and joint-agency across various types of joint actions.

In conclusion, the project shed light on the intricate interplay between self-agency and joint-agency. By utilizing measures of intentional binding and control ratings, we gained a deeper understanding of the nuanced experience of agency in joint actions.

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The Power of We: Exploring Shared Agency and Group Flow in Collaborative Actions

Whilst completing my PhD, I conducted complex and highly novel research project to assess the intricate connection between the sense of agency and group flow in the context of joint action. Joint action, a pivotal aspect of our social interactions, involves a multitude of cognitive mechanisms that generate unique and often deeply rewarding subjective experiences. My objective was to unravel the fundamental factors underlying joint agency and to elucidate why individuals feel a sense of shared agency rather than individual agency when engaged in collaborative activities. To accomplish this, I employed a virtual herding task as the experimental paradigm, wherein two participants collaboratively herded a group of virtual sheep into a central containment area within a simulated game environment. Each participant controlled a sheep-dog within the game-space using a handheld puck, while the sheep were programmed to flee from the sheep-dog, enabling the participants to collectively corral them into the containment space.

My hypothesis posited a positive correlation between the sense of agency and task performance. Furthermore, I anticipated that the agentic state would be linked to movement behaviour, whereby an augmented sense of joint agency would be observed when participants' movements exhibited characteristics indicative of a coupled oscillatory movement strategy. Additionally, I predicted that group flow would be influenced by participants' movement behaviour, with a greater sense of group flow reported when their movements aligned with a coupled oscillatory movement strategy. Moreover, I expected a positive correlation between the sense of agency and group flow. Lastly, I hypothesized that experiences of shared agency would be heightened during episodes of group flow compared to individual agency.

To explore these hypotheses, I recruited a total of 54 participants from the Goldsmiths community, forming 27 pairs of subjects. Utilizing the virtual herding task, I assessed the relationship between agency and flow during joint action by employing self-report measures that tapped into the cognitive mechanisms underlying these phenomena. Participants completed a series of self-report measures comprising three surveys and several single-point questions. The first survey employed the short version of the Flow State Scale - 2, which gauged the experience of flow. The second survey utilized the Flow Synchronization Scale, encompassing five subcomponents that evaluated group flow. The third survey employed the Sense of Agency Scale, which encompassed two sub-components: Sense of Positive Agency and Sense of Negative Agency. Finally, participants responded to four questions aimed at capturing their experiences of control and harmony.

The findings of my study revealed a significant positive correlation between the sense of agency and task performance. This suggests that a heightened sense of agency contributes to improved performance in joint action contexts. Furthermore, I discovered a notable correlation between the agentic state and movement behaviour, demonstrating that participants experienced a greater sense of joint agency when their movements exhibited characteristics indicative of a coupled oscillatory movement strategy. This aligns with the notion that movement synchronization plays a pivotal role in fostering shared agency during collaborative activities. Moreover, I observed that group flow was influenced by participants' movement behaviour, with heightened levels of group flow reported when their movements displayed indications of a coupled oscillatory movement strategy.

Importantly, my research unveiled a positive correlation between the sense of agency and group flow, suggesting that these two constructs are intertwined and mutually reinforcing during joint action. Finally, I discovered that experiences of shared agency were more prevalent during episodes of group flow compared to individual agency, underscoring the vital role of group flow in facilitating a collective sense of agency.

In conclusion, my study delved into the captivating domain of joint action, shedding light on the intricate relationship between the sense of agency and group flow. By employing a virtual herding task and employing a range of self-report measures, I unravelled the various factors influencing the emergence of joint agency and its connection to the phenomenon of group flow. These findings deepen our understanding of human behaviour and provide valuable insights into the mechanisms underlying collaborative experiences.

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