Fusion of EEG and EMG Signals for Home Automation Based on Convolutional Neural Networks with Portable devices

Society's advancement is marked by improved quality of life, but challenges faced by individuals with limited mobility due to injuries cannot be overlooked. These challenges, coupled with potential safety risks like unattended gas stoves leading to fires, highlight the need for solutions. To address this, this paper proposed an innovative smart home system for controlling LED light by detecting specific real-time EEG and EMG signals from portable devices. The system uses Bluetooth to transfer the real-time signals of EEG attention and EMG gestures and a convolutional neural network for binary classifications. Through analyzing real-time EEG attention and EMG gestures, our approach enables seamless control of smart devices. By merging technology with EEG and EMG analysis, our project empowers limited mobility individuals for an enhanced quality of life.