Live Demonstration: A Wearable EIT System for Hand Prosthesis Motion Controls

Abstract

A wearable electrical impedance tomography system for hand prosthesis motion control is demonstrated. The system captures the user's hand motion by measuring the impedance alterations caused by muscle and bone movement inside the forearm. These impedance data are sent to an artificial neural network for motion classification which is then used to manipulate a hand prosthesis. During the live demonstration, a sensor band is put on a volunteers' forearm for data acquisition. After signal processing, hand gestures learnt by the neural network can be recognized and the same hand motion can be recreated through the hand prosthesis in real-time. I.