Armband Device to Predict Gestures and Control Prosthetic Hands

Researchers from UC Berkeley  have developed a new device that combines wearable biosensors with AI software to help recognize what hand gesture a person intends to make based on electrical signal patterns in the forearm. The device paves the way for better prosthetic control and more seamless interaction with electronic devices. The flexible armband design can read the electrical signals at 64 different points on the forearm. These electrical signals are then fed into an electrical chip, which is programmed with an AI algorithm that can associate these signal patterns in the forearm with specific hand gestures. The team has demonstrated that the system can classify up to 21 different hand signals, including a thumbs-up, a fist, a flat hand, holding up individual fingers, and counting numbers.