This work presents a high-accuracy hand gesture recognition platform for robotic hand control. The platform consists of a flexible 8-electrode band, a high-performance electrical impedance tomography (EIT) system, a compact customised neural network deployed on a laptop and a robotic hand. The EIT system captures the bioimpedance features from muscle contraction and bone movement in the upper arm. After training, the customised neural network can predict hand gestures using bioimpedance features. The visitor will experience smooth control of a robotic hand by performing desired gestures using this demo platform
