AI-Powered Brain-Computer Interface App

Overview

This mobile app functions as a Brain-Computer Interface (BCI), utilizing EEG signals to support adaptive and deep learning processes and enhance knowledge retention. It monitors cognitive metrics such as concentration, stress levels, and cognitive load. 

Challenge

• Adapting to any Learning Content
• AI-Driven Chatbot Dialogue
• Identification of Confident Responses
• Detection of Guessing
• Verification of Knowledge Accuracy
• Attention Management
• Stress Management
• Cognitive Load Control

Key Functionality

• Brain-Computer Interface (BCI) Feature
• AI-Driven Chatbot Module
• Real-Time Neurofeedback Analyser
• Confident Response Detection Feature
• Guess Detection and Response Adjustment Feature
• Knowledge Accuracy Verification Module
• Progress Tracking Feature
• Attention, Stress, and Cognitive Load Management Features

Value Delivered

• Enhanced Learning Efficiency for Users
  The app provides users with a unique tool that leverages their biological responses for real-time feedback on their learning process. By analyzing EEG signals, it offers precise insights on concentration, cognitive load, and stress levels.
• Guided Self-Improvement
  Users benefit from targeted recommendations and personalized note-taking features that focus on their identified weaknesses. 
• Autonomous Performance Support
  The app’s autonomous functions, such as stress, attention, and cognitive load management, serve as ongoing assistants. These features support users beyond educational contexts, making the app useful for enhancing productivity in various activities, especially those requiring focus and mental resilience.
• Increased User Engagement and Retention
  The app boosts user engagement by providing personalized, science-backed guidance. Its cost-effective and scalable design supports expansion into various educational sectors, from schools to corporate training, enhancing product appeal and driving wider market adoption.

For a more in-depth look at this case study, please visit the SEVEN website.