Gesture recognition with millimetre wave radar has been extensively researched and many datasets are publicly available. However, datasets with raw data (including voltage levels) are almost not available. These are essential as they allow for recreation of all signal representations, thus allowing evaluation of gesture detection pipelines on the same datasets. This paper presents the design, implementation, and testing of a data recording prototype for hand gesture recognition coupling the Texas Instruments IWR6843ISK radar sensor and magic leap motion sensor. The study emphasizes on the system architecture, system apparatus and implementation to optimize recorded data quality and format flexibility (including voltage levels). Preliminary results demonstrate the prototype’s ability to accurately capture stream of data from both radar sensor and Ultraleap LeapMotion sensor. This report assists researchers and other practitioners in building such a system, thus allowing them to capture high quality datasets on their own.
Attygalle et al. (Sun,) studied this question.