Hand Gesture Recognition based Application using 60 GHz FMCW MIMO Radar

Millimeter wave radar (mm-Wave radar) technology has paved the way for non-contact human-machine interaction using gestures. The proposed work uses a 60 Giga Hertz Frequency Modulated Continuous Wave Multiple Input Multiple Output Radar (FMCW MIMO radar) to perform hand gesture-based applications. In the paper, 2 different gestures namely, forward and backward are classified and used in the application. Data for the aforementioned gestures was extracted using Texas Instrument's 60 GHz FMCW MIMO radar from a group of 10 people. For data classification, the Micro-Doppler signatures of the gesture data are extracted. The classification of these micro-Doppler features is done by using a vanilla Convolutional Neural Network (CNN) algorithm.