NeuroNav: Brainwave Controlled Smart Assistant

NeuroNav is a low-cost, brainwave-inspired human-computer interface (HCI) designed to translate human thought patterns into voice or device control actions. Unlike traditional EEG-based brain-computer interfaces (BCIs), which are costly and require complex equipment, NeuroNav employs Electromyography (EMG) and pulse sensors to capture neuromuscular and physiological signals related to thought activity. The system processes these signals using machine learning models such as Random Forest, Support Vector Machine (SVM), and Convolutional Neural Networks (CNN) to recognize specific mental patterns. The prototype integrates both hardware and software components, utilizing Arduino for signal acquisition and Python-based algorithms for interpretation and response generation. Results demonstrate high accuracy, real-time responsiveness, and strong potential for assistive communication and smart device control. This research highlights an affordable and practical approach to bridging neuroscience, AI, and human-computer interaction for students, makers, and researchers.