Hand Gesture Recognition Using Three-Dimensional Electrical Impedance Tomography

Abstract

This brief presents a 16-electrode electrical impedance tomography (EIT) system for hand gesture recognition. The hardware of the system is based on integrated circuits including a 12-bit high spectral purity current-steering DAC implemented in $0.18~\mu \text{m}$ CMOS technology, a current driver and an instrumentation amplifier in $0.35~\mu \text{m}$ CMOS technology. Both 2D and 3D EIT electrode arrangements were tested for hand gesture recognition. It is shown that using machine learning algorithms, eight hand gestures can be distinguished from the measured bio-impedance data with an accuracy of 97.9% when the electrodes are placed on a single wristband, and an accuracy of 99.5% with the same number of electrodes distributed on two wristbands for 3D EIT measurement. In particular 3D EIT demonstrated significant superiority in its ability to discriminate between gestures with similar muscle contractions.