Wearable Sign-Language Translator Using Myo Armband and Smartphone

Description:
This project presents a low-cost wearable system that translates hand gestures into spoken and written words to assist communication for deaf-mute individuals. The system uses a Myo armband to capture surface electromyographic (sEMG) signals from the forearm and a smartphone to process, classify, and display the recognized gestures in real time.
The armband wirelessly streams muscle activity data via Bluetooth to the smartphone, where the signals are processed using discrete wavelet transforms and classified using a neural network. Each recognized gesture is mapped to a predefined word, which is displayed on the screen and played back as audio, enabling seamless interaction with people unfamiliar with sign language.
Designed with minimal hardware and a user-friendly interface, the system demonstrates how wearable sensing, signal processing, and machine learning can be combined into an affordable assistive communication tool. Extensive experimental testing with users validated the reliability and practicality of the approach for everyday communication support.