As Neuroadaptivity for Autonomous Systems (NAFAS) continues to evolve, we want to share some updates on this groundbreaking project that aims to change our relationship with technology.

During the four-year project, NAFAS will develop secure neurotechnological prototypes to simplify communication between humans and computers. And to enable artificial intelligence to learn directly from the human brain in order to adopt skills and understand human cognitive states and values.

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At a time when technology is so increasingly intertwined with our daily lives, we need technology to assist us better and more safely. With Project NAFAS, we seek to overcome many of the limitations we face when transitioning brain-computer interfaces and artificial intelligence to real-world applications.

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To achieve this goal of seamless integration, we will drive the following research initiatives:

Mobile EEG sensors:

The usability of electroencephalogram (EEG) devices has traditionally been a significant bottleneck, characterized by the wearability of the devices and the time-consuming calibration processes required for each user at each session.

The NAFAS project aims to overcome these limitations by developing user-friendly, unobtrusive and comfortable mobile EEG sensors, in combination with universal classifiers. It promises to deliver a more accessible and convenient BCI technology that removes key barriers to adoption.

Universal classifiers:

Another significant challenge of BCI technology is the real-time interpretation of brain activity across diverse individuals without the need to train or calibrate a classifier for each individual user without compromising its accuracy.

The project aims to address this challenge by developing universal classifiers,  enabled by large-scale data collection, without individual calibration requirements to improve efficiency and applicability.

Multidimensional mental states (MDMS) and context awareness:

While universal classifiers provide insights into mental processes, they often lack context, obstructing the machine's ability to discern the underlying reasons for certain specific mental states.

For example, a system cannot recognize whether  a loss of attention is due to fatigue or distraction in order to adapt accordingly. However, if we combine a set of classifiers with context awareness (and create multidimensional states), the system can infer the user's intentions, needs and preferences.

If a system can understand the context and infer the reason for a mental state (such as loss of attention) it can automatically adapt accordingly, enabling a more personalized and insightful technological experience.

Privacy and Cybersecurity:

The NAFAS project focuses on ensuring user privacy and cyber security when handling sensitive brain data. The project emphasizes user autonomy and transparency,  so that individuals have maximum authority over what data and information is shared, and what is not. And it will use robust data protection measures to ensure that a person’s sensitive brain data does not leave the device or the person.

By breaking down barriers through these innovations, we come closer to expanding the capabilities of artificial intelligence and realizing our vision of creating a technology that combines human cognition and values with the potential of artificial intelligence.

As we embark on the NAFAS project, we are aware that we face numerous challenges that can only be overcome through innovative solutions. However, we are optimistic about the exploration of a new level of human-machine interaction.

Within this journey, NAFAS presents a substantial opportunity for us to take significant strides forward. This transformative partnership between human intelligence and AI promises a future where machines can engage in interactions that recognize, respect and respond to human privacy, preferences and capabilities.

Stay tuned for more updates on the NAFAS project, with which we strive to shape the future of personalized and insightful BCI applications.

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