Sleep staging is essential for assessing sleep and sleep disorders, but conventional approaches often rely on complex laboratory setups and expert analysis. This study investigated whether automatic sleep scoring could be simplified while maintaining reliable performance.

Using a convolutional neural network (CNN), the researchers analyzed four open-access datasets from healthy participants and people with obstructive sleep apnea. The results showed that a single frontal EEG channel can provide reliable sleep-stage classification, with only minimal improvements when additional 

 channels or biosignals such as EOG, EMG and ECG are introduced.

The study also compared offline methods with causal approaches suitable for real-time use. Real-time sleep scoring achieved performance close to offline methods, supporting its potential for applications that need to identify sleep stages as they occur.

New study advances real-time sleep scoring with single-channel EEG

The post underlines its role in aligning neural activity with experimental events and stimuli, enabling reliable analysis of event-related potentials and other time-sensitive measures.

EEG synchronization involves accurately marking when events occur and aligning recordings from multiple devices. For example, combining EEG with 

 requires researchers to match brain activity to the moment a participant fixates on a target.

How EEG synchronization improves the reliability of research data

In a new edition of Bitbrain’s In the Lab series, design researcher 

 discusses how EEG and other physiological measures are helping researchers study these effects in increasingly realistic environments.

Valentine’s research examines the built environment not simply as a backdrop, but as an exposure that may influence attention, cognitive load and stress over time. Her work includes research into biophilic design and how architectural characteristics may be reflected in physiological and neural responses.

, preliminary research has explored whether different architectural environments can be reflected in brain activity. The findings remain exploratory, highlighting both the potential of EEG for neuroarchitecture and the importance of careful interpretation.

Exploring neuroarchitecture with EEG: how spaces influence the brain

One of the highlighted studies titled “𝘌𝘹𝘱𝘭𝘰𝘳𝘪𝘯𝘨 𝘶𝘯𝘤𝘰𝘯𝘴𝘤𝘪𝘰𝘶𝘴 𝘶𝘴𝘦𝘳 𝘳𝘦𝘴𝘱𝘰𝘯𝘴𝘦𝘴 𝘵𝘰 𝘢𝘧𝘧𝘦𝘤𝘵𝘪𝘷𝘦 𝘤𝘰𝘮𝘱𝘶𝘵𝘪𝘯𝘨 𝘪𝘯 𝘪𝘯𝘵𝘦𝘳𝘢𝘤𝘵𝘪𝘷𝘦 𝘱𝘳𝘰𝘵𝘰𝘵𝘺𝘱𝘦𝘴: 𝘢 𝘤𝘰𝘯𝘴𝘶𝘮𝘦𝘳 𝘯𝘦𝘶𝘳𝘰𝘴𝘤𝘪𝘦𝘯𝘤𝘦 𝘴𝘵𝘶𝘥𝘺”, conducted by researchers from the 

 and the Autonomous University of Madrid. It examines how users react to emotionally adaptive systems in real time. The investigation employed a multimodal setup: 

 Pro Nano eye tracker, all synchronized with 

: a character that adapts facial expressions to the user’s emotions, and a children’s storytelling task that progresses only when happiness is detected. 

The study showed that emotion-responsive systems produce stronger engagement, higher cognitive effort, and more intense emotional responses than non-adaptive versions, while 

 data revealed distinct visual attention patterns depending on emotional expression.

 Bitbrain is recognized as Tobii’s key partner in 2025

S-CEReBrO introduces a Windowed Alternating Attention mechanism designed to maintain constant attention-memory requirements as recordings become longer. According to the authors, the approach can process signals up to 100 times longer than full self-attention and three times longer than the low-rank linear-attention alternative evaluated in the study. 

The model was pre-trained on more than 25,000 hours of EEG from over 12,000 individuals and achieved leading results in seven of 11 downstream tasks. Its architecture contains 2.4 million parameters. 

Open sleep data supports advances in continuous EEG monitoring

López Valdés studied Mathematics at the University of Zaragoza and later earned a PhD in Computational Engineering, followed by an MBA from IE Business School. In 2010, she founded Bitbrain, a neurotechnology company focused on brain monitoring and brain–computer interfaces. Bitbrain’s products are widely used in neuroscience investigation and practical human-behavior studies, supporting applications in cognitive science, neurotechnology, and human–machine interaction. Its 

 and biosignal systems enable the analysis of brain activity, attention, cognitive workload, and user engagement across both research and practical contexts.

What began as an academic initiative in Zaragoza has evolved into an international reference in neurotechnology, applied in analysis, healthcare, and industry.

María López Valdés Recognized as “Influential Woman of the Year” in Aragón

The certification provided both theoretical and practical training in 

 methods, emphasizing the application of advanced research techniques and transforming data into meaningful insights. During the event, Human Behaviour Research Product Specialist 

 presented the value of combining Eye Tracking with EEG and other biometric signals to support 

 and uncover both conscious and unconscious aspects of human experience. 

Bitbrain participates in the international eye tracking certification in Mexico 

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