Christoph Guger
The Biosignals-HUB project requires much more than a wearable EEG system. It requires a scalable multimodal biosignal acquisition platform capable of evolving from exploratory research to large-scale deployment while maintaining a common software environment. Based on more than 25 years of experience in brain-computer interfaces (BCIs), neurotechnology, and multimodal biosignal acquisition, g.tec proposes exactly such a platform.
Rather than recommending a single fixed hardware configuration from the outset, we propose a three-stage scalable platform strategy.
Stage 1 – High-End Research Platform
The project begins with the most flexible multimodal research platform based on g.Nautilus PRO wireless EEG, high-density fNIRS, IMU, PPG, microphone, speaker, eye tracking, and additional synchronized sensors. Combined with g.HIsys Professional, this platform enables rapid prototyping, flexible sensor configurations, synchronized acquisition, and real-time processing.
The goal of this phase is to identify which sensing modalities, sensor locations, and channel configurations provide the highest scientific value for the planned AI applications. Starting with the most capable platform minimizes technical risk and enables evidence-based system optimization before committing to large-scale deployment.
Stage 2 – Optimization
Based on the results of the research phase, the platform can be optimized by reducing unnecessary sensors, channels, weight, complexity, and cost while preserving the complete software environment. This results in a comfortable and robust wearable system suitable for everyday operation.
Stage 3 – Large-Scale Deployment
The optimized hardware is then deployed in the large pilot study. Depending on the final requirements, this platform may be based on Unicorn, g.Nautilus, or a customized integrated multimodal system. Since all hardware platforms share the same software architecture, no redevelopment of applications or data processing pipelines is required.
If the scientific requirements are already well understood at the start of the project, it is not necessary to begin with the high-end research platform. In this case, the project can immediately deploy the Unicorn platform, which provides a significantly lower-cost, lightweight, and easy-to-use solution while maintaining compatibility with the same software ecosystem, APIs, synchronization framework, and development tools. This enables a rapid transition to large-scale studies without sacrificing software compatibility or future expandability.
One of the major strengths of the g.tec ecosystem is that all hardware configurations are controlled through the same software environment. Regardless of whether researchers use Unicorn, g.Nautilus, or a future integrated multimodal platform, the same APIs, synchronization framework, and software tools remain available. Researchers therefore do not lose months of software development when moving from a laboratory prototype to an optimized wearable platform.
The proposed platform supports the multimodal acquisition of EEG, fNIRS, IMU, PPG, audio, and additional sensors while providing precise synchronization of all data streams. Open interfaces including Python, Unity, Simulink, C/C++, C#, Android, Lab Streaming Layer (LSL), UDP, and TCP/IP enable seamless integration into existing AI workflows and external software environments. g.Pype allows rapid prototyping of complete multimodal acquisition and processing pipelines with minimal programming effort.
The modular architecture supports future expansion with additional sensors such as eye tracking, ECG, EMG, pressure sensors, temperature sensors, or other physiological modalities without redesigning the overall software architecture.
The proposed solution has been developed for real-world applications. Wireless operation, robust communication, motion artifact suppression, intuitive self-application, and scalable manufacturing have been central design goals throughout the development of our systems. g.tec technologies are used worldwide in neuroscience, neuroengineering, rehabilitation, education, and clinical research and have proven their reliability in both laboratory and real-world environments.
Rather than proposing a single device, g.tec proposes a complete multimodal biosignal ecosystem that allows researchers to start with maximum flexibility, optimize based on scientific evidence, and deploy hundreds of systems while preserving a common hardware and software platform.
Alternatively, projects with well-defined requirements can immediately leverage the Unicorn platform for cost-effective large-scale deployment while benefiting from exactly the same software environment. We believe this strategy provides the greatest scientific flexibility, minimizes development risk, protects software investments, and offers the best long-term value for the Biosignals-HUB project.
