BrainiakAI™

Our revolutionary adaptive learning system that uses EEG and BCI technology to analyze brainwave data and personalize the learning experience.

Key Features

  • EEG-Based Learning Strategy Assessment: Powered by the BrainiakAI™ EEG Headset (1 channel EEG) and Advanced BrainiakAI™ EEG Headset (4 channel EEG: O1, O2, T3, T4), BrainiakAI™ analyzes brain activity to identify personalized learning strategies.
  • Brainwave Analysis: Utilizes EEG and BCI technology to analyze student brainwave patterns during learning.
  • Learning Strategy Identification: Identifies each student's optimal learning strategy based on cognitive patterns.
  • Real-time Adaptation: Adjusts content delivery and difficulty in real-time based on brainwave feedback.
  • Cognitive Load Monitoring: Prevents cognitive overload by pacing content delivery according to brain activity.
  • Attention Tracking: Monitors student attention levels and adjusts content to maintain optimal engagement.

Benefits

  • Personalized Learning: Truly personalized education based on individual brain function and cognitive patterns.
  • Improved Retention: Up to 85% increase in knowledge retention through optimized learning strategies.
  • Accelerated Learning: Reduce learning time by delivering content in the most effective way for each student.
  • Reduced Frustration: Minimize student frustration by adapting to their cognitive state in real-time.
  • Data-Driven Insights: Gain unprecedented insights into how students learn and process information.

How BrainiakAI™ Works

1. Brainwave Monitoring

Non-invasive EEG sensors monitor brain activity while students interact with learning materials, collecting data on cognitive processes.

2. AI Analysis

Our proprietary AI algorithms analyze brainwave patterns to identify optimal learning strategies and cognitive states for each student.

3. Adaptive Response

The system adapts content delivery, pacing, and difficulty in real-time based on the analyzed brainwave data to optimize learning.

Acknowledgements

NSF Logo

The development of the technology was funded by NSF SBIR grant 1632481