Advancing the interaction between humans and AI, the AI Research Centre of Woxsen University has developed an AI-driven Neuro-Adaptive Interface. This system tracks real-time cognitive and behavioural outcomes to enhance the digital landscape for users, reducing excessive cognitive load and ensuring customization across platforms through AI-based features.
By implementing Electroencephalogram (EEG), a reliable technology used to measure brain activity, along with biometric sensing and an AI-powered interface, this innovation elevates the level of collaboration between AI and humans. It is designed to increase efficiency, reduce mental fatigue, and enhance user experience and engagement across various applications.
The AI-driven interface employs real-time tracking of human behaviours using EEG signals, heart rate fluctuations, and pupil movement to detect fatigue and mental stress levels. It features AI-powered adaptive environments that adjust user interface complexity and difficulty levels, minimizing unnecessary workload and optimizing the overall user experience. To ensure reliability, it incorporates ethical AI practices, preventing user addiction while enhancing efficiency and effectiveness.
Dr. Raul Villamarin Rodriguez, Vice President of Woxsen University, stated, “AI should enhance human performance without causing cognitive strain. Our Neuro-Adaptive Interface optimizes digital environments in real-time, ensuring seamless and ethical adaptation across industries.”
He added, “The interface is projected to enhance user performance by 50%, reduce cognitive fatigue by 40%, and significantly improve engagement across digital platforms.”
Designed for seamless application across industries such as gaming, AI-driven education, cognitive therapy, financial trading, autonomous vehicles, and VR/AR experiences, the Neuro-Adaptive Interface showcases a significant leap in human-AI interaction. To process data efficiently, the interface incorporates Graph Neural Networks (GNNs), which analyse multiple users, assess individual workloads, and redistribute tasks among team members to maintain a collaborative environment.
By understanding digital environments and reflecting on user interactions, the system intelligently interprets signals, providing a strategically analysed and optimized experience, all while adhering to ethical AI practices.